Support vector machines and a Kalman-like observer are used for fault detection and isolation in a variable speed horizontalaxis wind turbine composed of three blades and a full converter. The support vector approach ...Support vector machines and a Kalman-like observer are used for fault detection and isolation in a variable speed horizontalaxis wind turbine composed of three blades and a full converter. The support vector approach is data-based and is therefore robust to process knowledge. It is based on structural risk minimization which enhances generalization even with small training data set and it allows for process nonlinearity by using flexible kernels. In this work, a radial basis function is used as the kernel. Different parts of the process are investigated including actuators and sensors faults. With duplicated sensors, sensor faults in blade pitch positions,generator and rotor speeds can be detected. Faults of type stuck measurements can be detected in 2 sampling periods. The detection time of offset/scaled measurements depends on the severity of the fault and on the process dynamics when the fault occurs. The converter torque actuator fault can be detected within 2 sampling periods. Faults in the actuators of the pitch systems represents a higher difficulty for fault detection which is due to the fact that such faults only affect the transitory state(which is very fast) but not the final stationary state. Therefore, two methods are considered and compared for fault detection and isolation of this fault: support vector machines and a Kalman-like observer. Advantages and disadvantages of each method are discussed. On one hand, support vector machines training of transitory states would require a big amount of data in different situations, but the fault detection and isolation results are robust to variations in the input/operating point. On the other hand, the observer is model-based, and therefore does not require training, and it allows identification of the fault level, which is interesting for fault reconfiguration. But the observability of the system is ensured under specific conditions, related to the dynamics of the inputs and outputs. The whole fault detection and isolation scheme is evaluated using a wind turbine benchmark with a real sequence of wind speed.展开更多
This paper investigates the consensus tracking control problem for high order nonlinear multi-agent systems subject to non-affine faults,partial measurable states,uncertain control coefficients,and unknown external di...This paper investigates the consensus tracking control problem for high order nonlinear multi-agent systems subject to non-affine faults,partial measurable states,uncertain control coefficients,and unknown external disturbances.Under the directed topology conditions,an observer-based finite-time control strategy based on adaptive backstepping and is proposed,in which a neural network-based state observer is employed to approximate the unmeasurable system state variables.To address the complexity explosion problem associated with the backstepping method,a finite-time command filter is incorporated,with error compensation signals designed to mitigate the filter-induced errors.Additionally,the Butterworth low-pass filter is introduced to avoid the algebraic ring problem in the design of the controller.The finite-time stability of the closed-loop system is rigorously analyzed with the finite-time Lyapunov stability criterion,validating that all closed-loop signals of the system remain bounded within a finite time.Finally,the effectiveness of the proposed control strategy is verified through a simulation example.展开更多
This paper investigates the adaptive optimal tracking control(AOTC)for underactuated surface vessels(USVs).Compared to the majority of existing studies,the control strategy in this paper innovatively combines an exten...This paper investigates the adaptive optimal tracking control(AOTC)for underactuated surface vessels(USVs).Compared to the majority of existing studies,the control strategy in this paper innovatively combines an extended state observer(ESO)with reinforcement learning(RL).The designed ESO has high estimation accuracy and robust disturbance rejection capabilities for the unmeasurable information for USVs.To obtain the AOTC,the actor–critic(AC)networks based on RL are constructed to solve the Hamilton–Jacobi–Bellman(HJB)equations.Due to the uncertainties,it is challenging to obtain the optimal controller by directly solving the HJB equations.To address this issue,this paper employs neural networks(NNs)to approximate the uncertainties and solves the optimal controller via AC-RL and ESO.In addition,the adaptive parameters of the optimal controller is trained in parallel with AC networks,which can ensure that the trained networks can further improve tracking performance.The boundedness of AOTC for USVs is shown by Lyapunov stability theorem.Finally,simulation results demonstrate the effectiveness of the proposed algorithm.展开更多
This paper presents an artificial intelligence(AI)-based observer that combines fuzzy logic and neural networks to detect abnormalities in sensors embedded in an electrolyser.Electrolysers are hydrogen production plan...This paper presents an artificial intelligence(AI)-based observer that combines fuzzy logic and neural networks to detect abnormalities in sensors embedded in an electrolyser.Electrolysers are hydrogen production plants that require effective maintenance to guarantee suitable operation,prevent degradation,and avoid loss of efficiency.In this sense,predictive maintenance arises as one of the most advisable techniques for maintenance in electrolysers by using sensor data to predict potential abnormalities.However,if the sensor fails,there will be an incorrect forecasting of abnormalities.Among the different types of operational faults that sensors can present are drift-related faults,which are probably the most difficult to detect due to a slow but progressive loss of accuracy in measurements.Another problem with predictive maintenance is that it often requires enormous training data,which is not available at the early stage of plant operation.The developed fuzzy system is responsible for detecting faulty readings arising from drift sensor signals,while the neural network complements the function of the fuzzy system by predicting sensor signals when enough training data are available.The AI-based observer and the fuzzy rules are validated in an experimental case study with a 1 Nm^(3)/h electrolyser.The selected variables are electrolyser temperature and efficiency.Experimental results show that the rules of the fuzzy component of the AI-based observer guarantee an accuracy of±0.25 within the range of 0 to 1,and the neural network component predicted correct sensor values with a root mean square error(RMSE)as low as 0.0016.The authors’approach helps to determine drift faults without additional sensors or components installed in the plant.展开更多
In permanent magnet synchronous motor(PMSM)control,the jitter problem affects the system performance,so a novel reaching lawis proposed to construct a non-singular fast terminal slidingmode controller(NFTSMC)to reduce...In permanent magnet synchronous motor(PMSM)control,the jitter problem affects the system performance,so a novel reaching lawis proposed to construct a non-singular fast terminal slidingmode controller(NFTSMC)to reduce the jitter.To enhance the immunity of the system,a disturbance observer is designed to observe and compensate for the disturbance to the sliding mode controller.In addition,considering that the controller parameters are difficult to adjust,and the traditional zebra optimization algorithm(ZOA)is prone to converge prematurely and fall into local optimum when solving the optimal solution,the improved zebra optimization algorithm(IZOA)is proposed,and the ability of the IZOA in practical applications is verified by using international standard test functions.To verify the performance of IZOA,firstly,the adjustment time of IZOA is reduced by 71.67%compared with ZOA through the step response,and secondly,the tracking error of IZOA is reduced by 51.52%compared with ZOA through the sinusoidal signal following.To verify the performance of the designed controller based on disturbance observer,the designed controller reduces the speed overshoot from 2.5%to 0.63%compared with the traditional NFTSMC in the speed mutation experiment,which is a performance improvement of 70.8%,and the designed controller outperforms the traditional NFTSMC in the load mutation experiment,which is a performance improvement of 60.0%in the case of sudden load addition,and a performance improvement of 90.0%in the case of load release,which verifies that the designed controller outperforms the traditional NFTSMC.展开更多
This study offers an empirical comparison of the Linear Quadratic Regulator(LQR)and Fractional Order LQR(FOLQR)controllers that were implemented on a two-degrees-offreedom(2-DOF)Quanser Aero 2 helicopter platform.It e...This study offers an empirical comparison of the Linear Quadratic Regulator(LQR)and Fractional Order LQR(FOLQR)controllers that were implemented on a two-degrees-offreedom(2-DOF)Quanser Aero 2 helicopter platform.It employs both full and reduced-order observer designs to facilitate trajectory monitoring and stabilisation.The Aero 2 platform is dynamically modelled using Euler-Lagrange equations to develop a multi-input multi-output(MIMO)system.This system comprises two inputs and four state equations.In collaboration with observers,the LQR and FOLQR controllers approximate states that are not directly measurable by utilising the system model and available data.This procedure effectively overcomes the practical limitations of sensors.The enhanced performance of FOLQR in terms of tracking precision and stability has been depicted from the experimental results,showing real-time execution on the Aero 2 platform.This paper provides rigorous insights into control engineering and advanced observer-based control design for underactuated systems.展开更多
This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hype...This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.展开更多
We present a new perspective on the P vs NP problem by demonstrating that its answer is inherently observer-dependent in curved spacetime, revealing an oversight in the classical formulation of computational complexit...We present a new perspective on the P vs NP problem by demonstrating that its answer is inherently observer-dependent in curved spacetime, revealing an oversight in the classical formulation of computational complexity theory. By incorporating general relativistic effects into complexity theory through a gravitational correction factor, we prove that problems can transition between complexity classes depending on the observer’s reference frame and local gravitational environment. This insight emerges from recognizing that the definition of polynomial time implicitly assumes a universal time metric, an assumption that breaks down in curved spacetime due to gravitational time dilation. We demonstrate the existence of gravitational phase transitions in problem complexity, where an NP-complete problem in one reference frame becomes polynomially solvable in another frame experiencing extreme gravitational time dilation. Through rigorous mathematical formulation, we establish a gravitationally modified complexity theory that extends classical complexity classes to incorporate observer-dependent effects, leading to a complete framework for understanding how computational complexity transforms across different spacetime reference frames. This finding parallels other self-referential insights in mathematics and physics, such as Gödel’s incompleteness theorems and Einstein’s relativity, suggesting a deeper connection between computation, gravitation, and the nature of mathematical truth.展开更多
Driven by practical applications, the achievement of distributed observers for nonlinear systems has emerged as a crucial advancement in recent years. However, existing theoretical advancements face certain limitation...Driven by practical applications, the achievement of distributed observers for nonlinear systems has emerged as a crucial advancement in recent years. However, existing theoretical advancements face certain limitations: They either fail to address more complex nonlinear phenomena, rely on hard-to-verify assumptions, or encounter difficulties in solving system parameters.Consequently, this paper aims to address these challenges by investigating distributed observers for nonlinear systems through the full-measured canonical form(FMCF), which is inspired by full-measured system(FMS) theory. To begin with, this study addresses the fact that the FMCF can only be obtained through the observable canonical form(OCF) in existing FMS theories.The paper demonstrates that a class of nonlinear systems can directly obtain FMCF through state space equations, independent of OCF. Also, a general method for solving FMCF in such systems is provided. Furthermore, based on the FMCF, A distributed observer is developed for nonlinear systems under two scenarios: Lipschitz conditions and open-loop bounded conditions.The paper establishes their asymptotic omniscience and demonstrates that the designed distributed observer in this study has fewer design parameters and is more convenient to construct than existing approaches. Finally, the effectiveness of the proposed methods is validated through simulation results on Van der Pol oscillators and microgrid systems.展开更多
Numerous clustering algorithms are valuable in pattern recognition in forest vegetation,with new ones continually being proposed.While some are well-known,others are underutilized in vegetation science.This study comp...Numerous clustering algorithms are valuable in pattern recognition in forest vegetation,with new ones continually being proposed.While some are well-known,others are underutilized in vegetation science.This study compares the performance of practical iterative reallocation algorithms with model-based clustering algorithms.The data is from forest vegetation in Virginia(United States),the Hyrcanian Forest(Asia),and European beech forests.Practical iterative reallocation algorithms were applied as non-hierarchical methods and Finite Gaussian mixture modeling was used as a model-based clustering method.Due to limitations on dimensionality in model-based clustering,principal coordinates analysis was employed to reduce the dataset’s dimensions.A log transformation was applied to achieve a normal distribution for the pseudo-species data before calculating the Bray-Curtis dissimilarity.The findings indicate that the reallocation of misclassified objects based on silhouette width(OPTSIL)with Flexible-β(-0.25)had the highest mean among the tested clustering algorithms with Silhouette width 1(REMOS1)with Flexible-β(-0.25)second.However,model-based clustering performed poorly.Based on these results,it is recommended using OPTSIL with Flexible-β(-0.25)and REMOS1 with Flexible-β(-0.25)for forest vegetation classification instead of model-based clustering particularly for heterogeneous datasets common in forest vegetation community data.展开更多
Extended state observer(ESO)is heavily limited by the unknown disturbance and its derivative,which requires high observing gains to decrease estimating error,resulting in serious noise sensitivity.To modify the distur...Extended state observer(ESO)is heavily limited by the unknown disturbance and its derivative,which requires high observing gains to decrease estimating error,resulting in serious noise sensitivity.To modify the disturbance estimation characteristics encountered by the observer,the active compression extended state observer(ACESO)is proposed in this study.The ACESO decreases the bound of residual lumped disturbance and its derivative by actively compressing the initial lumped disturbance,without relying on prior knowledge.The stability constraint and convergence results of ACESO are analyzed and compared with ESO theoretically.The results show that the ACESO mitigates the trade-off between noise sensitivity and high-gain observation.Benefiting from active compression,the ACESO has substantially less noise sensitivity than the ESO,while obtaining the same and even better estimating performance than the ESO.In addition,the nonlinear ACESO is discussed,which automatically balances the contradiction between estimation and convergence.Simulations and experiments demonstrate the effectiveness of the proposed methods.展开更多
When the proton exchange membrane fuel cell(PEMFC)system is running,there will be a condition that does not require power output for a short time.In order to achieve zero power output under low power consumption,it is...When the proton exchange membrane fuel cell(PEMFC)system is running,there will be a condition that does not require power output for a short time.In order to achieve zero power output under low power consumption,it is necessary to consider the diversity of control targets and the complexity of dynamic models,which brings the challenge of high-precision tracking control of the stack output power and cathode intake flow.For system idle speed control,a modelbased nonlinear control framework is constructed in this paper.Firstly,the nonlinear dynamic model of output power and cathode intake flow is derived.Secondly,a control scheme combining nonlinear extended Kalman filter observer and state feedback controller is designed.Finally,the control scheme is verified on the PEMFC experimental platform and compared with the proportion-integration-differentiation(PID)controller.The experimental results show that the control strategy proposed in this paper can realize the idle speed control of the fuel cell system and achieve the purpose of zero power output.Compared with PID controller,it has faster response speed and better system dynamics.展开更多
Unlike traditional propeller-driven underwater vehicles,blended-wing-body underwater gliders(BWBUGs)achieve zigzag gliding through periodic adjustments of their net buoyancy,enhancing their cruising capabilities while...Unlike traditional propeller-driven underwater vehicles,blended-wing-body underwater gliders(BWBUGs)achieve zigzag gliding through periodic adjustments of their net buoyancy,enhancing their cruising capabilities while mini-mizing energy consumption.However,enhancing gliding performance is challenging due to the complex system design and limited design experience.To address this challenge,this paper introduces a model-based,multidisciplinary system design optimization method for BWBUGs at the conceptual design stage.First,a model-based,multidisciplinary co-simulation design framework is established to evaluate both system-level and disciplinary indices of BWBUG performance.A data-driven,many-objective multidisciplinary optimization is subsequently employed to explore the design space,yielding 32 Pareto optimal solutions.Finally,a model-based physical system simulation,which represents the design with the largest hyper-volume contribution among the 32 final designs,is established.Its gliding perfor-mance,validated by component behavior,lays the groundwork for constructing the entire system’s digital prototype.In conclusion,this model-based,multidisciplinary design optimization method effectively generates design schemes for innovative underwater vehicles,facilitating the development of digital prototypes.展开更多
This paper presents a novel active disturbance rejection control(ADRC)scheme based on a cascade connection of generalized proportional integral observers(GPIOs)with internal models designed to estimate both polynomial...This paper presents a novel active disturbance rejection control(ADRC)scheme based on a cascade connection of generalized proportional integral observers(GPIOs)with internal models designed to estimate both polynomial and resonant disturbances.In this estimator structure,referred to as Cascade GPIO(CGPIO),the total disturbance sensitivity is the product of the sensitivities at each cascade level.This approach improves system performance against both periodic and non-periodic disturbances and enhances robustness under frequency variations in harmonic components.Additionally,the decoupled nature of the estimator reduces the order of the GPIOs,thereby simplifying tuning and limiting observer gains.The proposed control scheme is supported by a frequency-domain analysis and is experimentally validated in the current control of a grid-connected converter subject to control gain uncertainties,harmonic distortion,frequency deviations,and measurement noise.Experimental results demonstrate that the CGPIO-based ADRC outperforms benchmark solutions,including proportional-integral(PI)and proportional-resonant(PR)controllers.展开更多
This paper studies the problem of designing a modelbased decentralized dynamic periodic event-triggering mechanism(DDPETM)for networked control systems(NCSs)subject to packet losses and external disturbances.Firstly,t...This paper studies the problem of designing a modelbased decentralized dynamic periodic event-triggering mechanism(DDPETM)for networked control systems(NCSs)subject to packet losses and external disturbances.Firstly,the entire NCSs,comprising the triggering mechanism,packet losses and output-based controller,are unified into a hybrid dynamical framework.Secondly,by introducing dynamic triggering variables,the DDPETM is designed to conserve network resources while guaranteeing desired performance properties and tolerating the maximum allowable number of successive packet losses.Thirdly,some stability conditions are derived using the Lyapunov approach.Differing from the zero-order-hold(ZOH)case,the model-based control sufficiently exploits the model information at the controller side.Between two updates,the controller predicts the plant state based on the models and received feedback information.With the model-based control,less transmission may be expected than with ZOH.Finally,numerical examples and comparative experiments demonstrate the effectiveness of the proposed method.展开更多
Automated valet parking systems based on parking automated guided vehicles(P-AGVs)are effective for improving parking convenience and increasing parking density.The ability of P-AGVs to move towards any position and a...Automated valet parking systems based on parking automated guided vehicles(P-AGVs)are effective for improving parking convenience and increasing parking density.The ability of P-AGVs to move towards any position and attain any orientation simultaneously due to their mecanum wheels makes it convenient to transport vehicles in a parking lot.In this study,a nonlinear disturbance observer-based sliding mode controller for the trajectory tracking problem of a P-AGV is proposed.The kinematic and dynamic models for a P-AGV tracking trajectory are first analyzed in sequence and the influences of disturbing forces considered.Subsequently,a nonlinear disturbance observer(NDO)is designed to estimate the disturbing forces and torques generated by the caster wheels.Based on the designed NDO,a robust nonsingular terminal sliding-mode(NTSM)controller is used to track reference trajectories.The stabilities of the NDO and NDO-NTSM control systems are theoretically verified using their Lyapunov functions.Finally,simulations and experiments are performed to verify the effectiveness of the proposed control scheme.The experimental results show that the proposed NDO-NTSM controller can improve the trajectory tracking stability by 42-68%compared to a traditional NTSM controller.The NDO-based sliding mode controller for trajectory tracking proposed in this study can effectively reduce the impact of disturbances on trajectory tracking accuracy.展开更多
In semiconductor precision packaging and other applications involving alignment of automated equipment,the nonlinear motion caused by structural characteristics and friction effects on torque-type rotating motion stag...In semiconductor precision packaging and other applications involving alignment of automated equipment,the nonlinear motion caused by structural characteristics and friction effects on torque-type rotating motion stages seriously affects output accuracy and stability.To solve this problem,the motion characteristics of a rotating stage and the mechanism by which friction nonlinearity influences accuracy are analyzed in detail.In addition,a compound control strategy based on a kinematic model and the Stribeck friction model is designed.A friction disturbance observer based on output position feedback is improved for simple parameter tuning.Finally,an experimental system is constructed to carry out validation tests,including identification of nonlinear characteristics and performance comparisons.The experimental results show that the linear tracking error of the torque-type rotating stage is less than 1.47µm after adoption of the proposed model-based composite control strategy,and the corresponding rotary angle deviation is less than 0.0153°.The linearity of output motion is increased to 97.59%and the error compensation effect is improved by 51.6%compared with the PID control method.The experimental results confirm that the analysis method adopted here and the proposed compensation strategy can effectively reduce frictional nonlinearity and improve motion accuracy.The proposed method can also be applied to other precision electromechanical systems.展开更多
This paper investigates the observer-based prescribed-time time-varying output formation-containment(PT-TV-OFC)control problem for heterogeneous multi-agent systems in which the different agents have different state d...This paper investigates the observer-based prescribed-time time-varying output formation-containment(PT-TV-OFC)control problem for heterogeneous multi-agent systems in which the different agents have different state dimensions.The system comprises one tracking leader,multiple formation leaders,and followers,where two types of leaders are used to generate a reference trajectory for movement and achieve specific formation,respectively.Firstly,a prescribed-time dynamics observer is constructed for the formation leaders to estimate the tracking leader's dynamic model and state.On this basis,a prescribed-time control protocol is designed for the formation leaders to achieve time-varying output formation.Then,a prescribed-time convex hull observer is designed for the followers to estimate information regarding the convex hull formed by the formation leaders.Using the estimated convex hull information,a prescribed-time containment control protocol is designed to ensure the followers converge into the convex hull.Furthermore,using Lyapunov stability theory,the stability of systems is proved in detail,which implies that the heterogeneous multi-agent systems can achieve PT-TV-OFC control.Finally,numerical simulations validate the feasibility of the theoretical results.展开更多
In order to enhance the dynamic control precision of inertial stabilization platform(ISP),a disturbance sliding mode observer(DSMO)is proposed in this paper suppressing disturbance torques inherent within the system.T...In order to enhance the dynamic control precision of inertial stabilization platform(ISP),a disturbance sliding mode observer(DSMO)is proposed in this paper suppressing disturbance torques inherent within the system.The control accuracy of ISP is fundamentally circumscribed by various disturbance torques in rotating shaft.Therefore,a dynamic model of ISP incorporating composite perturbations is established with regard to the stabilization of axis in the inertial reference frame.Subsequently,an online estimator for control loop uncertainties based on the sliding mode control algorithm is designed to estimate the aggregate disturbances of various parameters uncertainties and other unmodeled disturbances that cannot be accurately calibrated.Finally,the proposed DSMO is integrated into a classical proportional-integral-derivative(PID)control scheme,utilizing feedforward approach to compensate the composite disturbance in the control loop online.The effectiveness of the proposed disturbance observer is validated through simulation and hardware experimentation,demonstrating a significant improvement in the dynamic control performance and robustness of the classical PID controller extensively utilized in the field of engineering.展开更多
Intercepting high-maneuverability hypersonic targets in near-space environments poses significant challenges due to their extreme speeds and evasive capabilities.To address these challenges,this study presents an inte...Intercepting high-maneuverability hypersonic targets in near-space environments poses significant challenges due to their extreme speeds and evasive capabilities.To address these challenges,this study presents an integrated approach that combines a Three-Dimensional Finite-Time Optimal Cooperative Guidance Law(FTOC)with an Information Fusion Anti-saturation Predefined-time Observer(IFAPO).The proposed FTOC guidance law employs a nonlinear,non-quadratic finite-time optimal control strategy designed for rapid convergence within the limited timeframes of near-space interceptions,avoiding the need for remaining flight time estimation or linear decoupling inherent in traditional methods.To complement the guidance strategy,the IFAPO leverages multi-source information fusion theory and incorporates anti-saturation mechanisms to enhance target maneuver estimation.This method ensures accurate and real-time prediction of target acceleration while maintaining predefined convergence performance,even under complex interception conditions.By integrating the FTOC guidance law and IFAPO,the approach optimizes cooperative missile positioning,improves interception success rates,and minimizes fuel consumption,addressing practical constraints in military applications.Simulation results and comparative analyses confirm the effectiveness of the integrated approach,demonstrating its capability to achieve cooperative interception of highly maneuvering targets with enhanced efficiency and reduced economic costs,aligning with realistic combat scenarios.展开更多
文摘Support vector machines and a Kalman-like observer are used for fault detection and isolation in a variable speed horizontalaxis wind turbine composed of three blades and a full converter. The support vector approach is data-based and is therefore robust to process knowledge. It is based on structural risk minimization which enhances generalization even with small training data set and it allows for process nonlinearity by using flexible kernels. In this work, a radial basis function is used as the kernel. Different parts of the process are investigated including actuators and sensors faults. With duplicated sensors, sensor faults in blade pitch positions,generator and rotor speeds can be detected. Faults of type stuck measurements can be detected in 2 sampling periods. The detection time of offset/scaled measurements depends on the severity of the fault and on the process dynamics when the fault occurs. The converter torque actuator fault can be detected within 2 sampling periods. Faults in the actuators of the pitch systems represents a higher difficulty for fault detection which is due to the fact that such faults only affect the transitory state(which is very fast) but not the final stationary state. Therefore, two methods are considered and compared for fault detection and isolation of this fault: support vector machines and a Kalman-like observer. Advantages and disadvantages of each method are discussed. On one hand, support vector machines training of transitory states would require a big amount of data in different situations, but the fault detection and isolation results are robust to variations in the input/operating point. On the other hand, the observer is model-based, and therefore does not require training, and it allows identification of the fault level, which is interesting for fault reconfiguration. But the observability of the system is ensured under specific conditions, related to the dynamics of the inputs and outputs. The whole fault detection and isolation scheme is evaluated using a wind turbine benchmark with a real sequence of wind speed.
基金supported in part by the Beijing Natural Science Foundation under Grant 4252050in part by the National Science Fund for Distinguished Young Scholars under Grant 62425304in part by the Basic Science Center Programs of NSFC under Grant 62088101.
文摘This paper investigates the consensus tracking control problem for high order nonlinear multi-agent systems subject to non-affine faults,partial measurable states,uncertain control coefficients,and unknown external disturbances.Under the directed topology conditions,an observer-based finite-time control strategy based on adaptive backstepping and is proposed,in which a neural network-based state observer is employed to approximate the unmeasurable system state variables.To address the complexity explosion problem associated with the backstepping method,a finite-time command filter is incorporated,with error compensation signals designed to mitigate the filter-induced errors.Additionally,the Butterworth low-pass filter is introduced to avoid the algebraic ring problem in the design of the controller.The finite-time stability of the closed-loop system is rigorously analyzed with the finite-time Lyapunov stability criterion,validating that all closed-loop signals of the system remain bounded within a finite time.Finally,the effectiveness of the proposed control strategy is verified through a simulation example.
基金supported by the National Natural Science Foundation of China under Grants 62203338,62173259 and U1913602Zhejiang Provincial Natural Science Foundation of China under Grant LZ24F0390006the Postdoctoral Science Foundation of China under Grant 2022M722485.
文摘This paper investigates the adaptive optimal tracking control(AOTC)for underactuated surface vessels(USVs).Compared to the majority of existing studies,the control strategy in this paper innovatively combines an extended state observer(ESO)with reinforcement learning(RL).The designed ESO has high estimation accuracy and robust disturbance rejection capabilities for the unmeasurable information for USVs.To obtain the AOTC,the actor–critic(AC)networks based on RL are constructed to solve the Hamilton–Jacobi–Bellman(HJB)equations.Due to the uncertainties,it is challenging to obtain the optimal controller by directly solving the HJB equations.To address this issue,this paper employs neural networks(NNs)to approximate the uncertainties and solves the optimal controller via AC-RL and ESO.In addition,the adaptive parameters of the optimal controller is trained in parallel with AC networks,which can ensure that the trained networks can further improve tracking performance.The boundedness of AOTC for USVs is shown by Lyapunov stability theorem.Finally,simulation results demonstrate the effectiveness of the proposed algorithm.
基金support of(1)Grant Ref.PID2023-148456OB-C41 and(2)Grant Ref.RED2022-134588-T found by MICIU/AEI/10.13039/501100011033。
文摘This paper presents an artificial intelligence(AI)-based observer that combines fuzzy logic and neural networks to detect abnormalities in sensors embedded in an electrolyser.Electrolysers are hydrogen production plants that require effective maintenance to guarantee suitable operation,prevent degradation,and avoid loss of efficiency.In this sense,predictive maintenance arises as one of the most advisable techniques for maintenance in electrolysers by using sensor data to predict potential abnormalities.However,if the sensor fails,there will be an incorrect forecasting of abnormalities.Among the different types of operational faults that sensors can present are drift-related faults,which are probably the most difficult to detect due to a slow but progressive loss of accuracy in measurements.Another problem with predictive maintenance is that it often requires enormous training data,which is not available at the early stage of plant operation.The developed fuzzy system is responsible for detecting faulty readings arising from drift sensor signals,while the neural network complements the function of the fuzzy system by predicting sensor signals when enough training data are available.The AI-based observer and the fuzzy rules are validated in an experimental case study with a 1 Nm^(3)/h electrolyser.The selected variables are electrolyser temperature and efficiency.Experimental results show that the rules of the fuzzy component of the AI-based observer guarantee an accuracy of±0.25 within the range of 0 to 1,and the neural network component predicted correct sensor values with a root mean square error(RMSE)as low as 0.0016.The authors’approach helps to determine drift faults without additional sensors or components installed in the plant.
基金supported by the Key Technology of Flexible Regulation of Energy in Green High-Efficiency/Carbon-Efficient Buildings under the Smart Park System of PowerChina Guiyang Co.,Ltd.(YJ2022-12)the Science and Technology Support Plan of Guizhou Province“Research and Application Development of Key Technologies for Flexible Regulation of Energy in High-Efficiency/Carbon-Efficient Buildings”(Guizhou Science and Technology Cooperation Support[2023]General 409).
文摘In permanent magnet synchronous motor(PMSM)control,the jitter problem affects the system performance,so a novel reaching lawis proposed to construct a non-singular fast terminal slidingmode controller(NFTSMC)to reduce the jitter.To enhance the immunity of the system,a disturbance observer is designed to observe and compensate for the disturbance to the sliding mode controller.In addition,considering that the controller parameters are difficult to adjust,and the traditional zebra optimization algorithm(ZOA)is prone to converge prematurely and fall into local optimum when solving the optimal solution,the improved zebra optimization algorithm(IZOA)is proposed,and the ability of the IZOA in practical applications is verified by using international standard test functions.To verify the performance of IZOA,firstly,the adjustment time of IZOA is reduced by 71.67%compared with ZOA through the step response,and secondly,the tracking error of IZOA is reduced by 51.52%compared with ZOA through the sinusoidal signal following.To verify the performance of the designed controller based on disturbance observer,the designed controller reduces the speed overshoot from 2.5%to 0.63%compared with the traditional NFTSMC in the speed mutation experiment,which is a performance improvement of 70.8%,and the designed controller outperforms the traditional NFTSMC in the load mutation experiment,which is a performance improvement of 60.0%in the case of sudden load addition,and a performance improvement of 90.0%in the case of load release,which verifies that the designed controller outperforms the traditional NFTSMC.
文摘This study offers an empirical comparison of the Linear Quadratic Regulator(LQR)and Fractional Order LQR(FOLQR)controllers that were implemented on a two-degrees-offreedom(2-DOF)Quanser Aero 2 helicopter platform.It employs both full and reduced-order observer designs to facilitate trajectory monitoring and stabilisation.The Aero 2 platform is dynamically modelled using Euler-Lagrange equations to develop a multi-input multi-output(MIMO)system.This system comprises two inputs and four state equations.In collaboration with observers,the LQR and FOLQR controllers approximate states that are not directly measurable by utilising the system model and available data.This procedure effectively overcomes the practical limitations of sensors.The enhanced performance of FOLQR in terms of tracking precision and stability has been depicted from the experimental results,showing real-time execution on the Aero 2 platform.This paper provides rigorous insights into control engineering and advanced observer-based control design for underactuated systems.
基金supported by the National Natural Science Foundation of China(12072090).
文摘This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.
文摘We present a new perspective on the P vs NP problem by demonstrating that its answer is inherently observer-dependent in curved spacetime, revealing an oversight in the classical formulation of computational complexity theory. By incorporating general relativistic effects into complexity theory through a gravitational correction factor, we prove that problems can transition between complexity classes depending on the observer’s reference frame and local gravitational environment. This insight emerges from recognizing that the definition of polynomial time implicitly assumes a universal time metric, an assumption that breaks down in curved spacetime due to gravitational time dilation. We demonstrate the existence of gravitational phase transitions in problem complexity, where an NP-complete problem in one reference frame becomes polynomially solvable in another frame experiencing extreme gravitational time dilation. Through rigorous mathematical formulation, we establish a gravitationally modified complexity theory that extends classical complexity classes to incorporate observer-dependent effects, leading to a complete framework for understanding how computational complexity transforms across different spacetime reference frames. This finding parallels other self-referential insights in mathematics and physics, such as Gödel’s incompleteness theorems and Einstein’s relativity, suggesting a deeper connection between computation, gravitation, and the nature of mathematical truth.
基金supported by the National Natural Science Foundation of China(62133008,62303273,62188101,62373226,62473173)Young Taishan Scholars Program of Shandong Province of China(tsqn202408206)+2 种基金a Project of Shandong Province Higher Educational Youth and Innovation Talent Introduction and Education Programthe Natural Science Foundation of Shandong Province,China(ZR2023QF072)China Postdoctoral Science Foundation(2022M721932)
文摘Driven by practical applications, the achievement of distributed observers for nonlinear systems has emerged as a crucial advancement in recent years. However, existing theoretical advancements face certain limitations: They either fail to address more complex nonlinear phenomena, rely on hard-to-verify assumptions, or encounter difficulties in solving system parameters.Consequently, this paper aims to address these challenges by investigating distributed observers for nonlinear systems through the full-measured canonical form(FMCF), which is inspired by full-measured system(FMS) theory. To begin with, this study addresses the fact that the FMCF can only be obtained through the observable canonical form(OCF) in existing FMS theories.The paper demonstrates that a class of nonlinear systems can directly obtain FMCF through state space equations, independent of OCF. Also, a general method for solving FMCF in such systems is provided. Furthermore, based on the FMCF, A distributed observer is developed for nonlinear systems under two scenarios: Lipschitz conditions and open-loop bounded conditions.The paper establishes their asymptotic omniscience and demonstrates that the designed distributed observer in this study has fewer design parameters and is more convenient to construct than existing approaches. Finally, the effectiveness of the proposed methods is validated through simulation results on Van der Pol oscillators and microgrid systems.
基金financially supported by the vice chancellor for research and technology of Urmia University
文摘Numerous clustering algorithms are valuable in pattern recognition in forest vegetation,with new ones continually being proposed.While some are well-known,others are underutilized in vegetation science.This study compares the performance of practical iterative reallocation algorithms with model-based clustering algorithms.The data is from forest vegetation in Virginia(United States),the Hyrcanian Forest(Asia),and European beech forests.Practical iterative reallocation algorithms were applied as non-hierarchical methods and Finite Gaussian mixture modeling was used as a model-based clustering method.Due to limitations on dimensionality in model-based clustering,principal coordinates analysis was employed to reduce the dataset’s dimensions.A log transformation was applied to achieve a normal distribution for the pseudo-species data before calculating the Bray-Curtis dissimilarity.The findings indicate that the reallocation of misclassified objects based on silhouette width(OPTSIL)with Flexible-β(-0.25)had the highest mean among the tested clustering algorithms with Silhouette width 1(REMOS1)with Flexible-β(-0.25)second.However,model-based clustering performed poorly.Based on these results,it is recommended using OPTSIL with Flexible-β(-0.25)and REMOS1 with Flexible-β(-0.25)for forest vegetation classification instead of model-based clustering particularly for heterogeneous datasets common in forest vegetation community data.
基金supported by the Special Research Assistant Program,Chinese Academy of Sciences,China(E329691C21)Sichuan Science and Technology Program,China(2024NSFSC1481)National Natural Science Foundation of China(92471204,62271109).
文摘Extended state observer(ESO)is heavily limited by the unknown disturbance and its derivative,which requires high observing gains to decrease estimating error,resulting in serious noise sensitivity.To modify the disturbance estimation characteristics encountered by the observer,the active compression extended state observer(ACESO)is proposed in this study.The ACESO decreases the bound of residual lumped disturbance and its derivative by actively compressing the initial lumped disturbance,without relying on prior knowledge.The stability constraint and convergence results of ACESO are analyzed and compared with ESO theoretically.The results show that the ACESO mitigates the trade-off between noise sensitivity and high-gain observation.Benefiting from active compression,the ACESO has substantially less noise sensitivity than the ESO,while obtaining the same and even better estimating performance than the ESO.In addition,the nonlinear ACESO is discussed,which automatically balances the contradiction between estimation and convergence.Simulations and experiments demonstrate the effectiveness of the proposed methods.
基金Supported by the Major Science and Technology Projects in Jilin Province and Changchun City(20220301010GX).
文摘When the proton exchange membrane fuel cell(PEMFC)system is running,there will be a condition that does not require power output for a short time.In order to achieve zero power output under low power consumption,it is necessary to consider the diversity of control targets and the complexity of dynamic models,which brings the challenge of high-precision tracking control of the stack output power and cathode intake flow.For system idle speed control,a modelbased nonlinear control framework is constructed in this paper.Firstly,the nonlinear dynamic model of output power and cathode intake flow is derived.Secondly,a control scheme combining nonlinear extended Kalman filter observer and state feedback controller is designed.Finally,the control scheme is verified on the PEMFC experimental platform and compared with the proportion-integration-differentiation(PID)controller.The experimental results show that the control strategy proposed in this paper can realize the idle speed control of the fuel cell system and achieve the purpose of zero power output.Compared with PID controller,it has faster response speed and better system dynamics.
基金supported by the Postdoctoral Fellowship Program of CPSF(Grant No.GZC20242194)the National Natural Science Foundation of China(Grant Nos.52175251 and 52205268)+1 种基金the Industry Key Technology Research Fund Project of Northwestern Polytechnical University(Grant No.HYGJXM202318)the National Basic Scientific Research Program(Grant No.JCKY2021206B005).
文摘Unlike traditional propeller-driven underwater vehicles,blended-wing-body underwater gliders(BWBUGs)achieve zigzag gliding through periodic adjustments of their net buoyancy,enhancing their cruising capabilities while mini-mizing energy consumption.However,enhancing gliding performance is challenging due to the complex system design and limited design experience.To address this challenge,this paper introduces a model-based,multidisciplinary system design optimization method for BWBUGs at the conceptual design stage.First,a model-based,multidisciplinary co-simulation design framework is established to evaluate both system-level and disciplinary indices of BWBUG performance.A data-driven,many-objective multidisciplinary optimization is subsequently employed to explore the design space,yielding 32 Pareto optimal solutions.Finally,a model-based physical system simulation,which represents the design with the largest hyper-volume contribution among the 32 final designs,is established.Its gliding perfor-mance,validated by component behavior,lays the groundwork for constructing the entire system’s digital prototype.In conclusion,this model-based,multidisciplinary design optimization method effectively generates design schemes for innovative underwater vehicles,facilitating the development of digital prototypes.
文摘This paper presents a novel active disturbance rejection control(ADRC)scheme based on a cascade connection of generalized proportional integral observers(GPIOs)with internal models designed to estimate both polynomial and resonant disturbances.In this estimator structure,referred to as Cascade GPIO(CGPIO),the total disturbance sensitivity is the product of the sensitivities at each cascade level.This approach improves system performance against both periodic and non-periodic disturbances and enhances robustness under frequency variations in harmonic components.Additionally,the decoupled nature of the estimator reduces the order of the GPIOs,thereby simplifying tuning and limiting observer gains.The proposed control scheme is supported by a frequency-domain analysis and is experimentally validated in the current control of a grid-connected converter subject to control gain uncertainties,harmonic distortion,frequency deviations,and measurement noise.Experimental results demonstrate that the CGPIO-based ADRC outperforms benchmark solutions,including proportional-integral(PI)and proportional-resonant(PR)controllers.
基金supported by the National Natural Science Foundation of China(U21A20477,61722302,61573069,61903290)the Fundamental Research Funds for the Central Universities(DUT19ZD218).
文摘This paper studies the problem of designing a modelbased decentralized dynamic periodic event-triggering mechanism(DDPETM)for networked control systems(NCSs)subject to packet losses and external disturbances.Firstly,the entire NCSs,comprising the triggering mechanism,packet losses and output-based controller,are unified into a hybrid dynamical framework.Secondly,by introducing dynamic triggering variables,the DDPETM is designed to conserve network resources while guaranteeing desired performance properties and tolerating the maximum allowable number of successive packet losses.Thirdly,some stability conditions are derived using the Lyapunov approach.Differing from the zero-order-hold(ZOH)case,the model-based control sufficiently exploits the model information at the controller side.Between two updates,the controller predicts the plant state based on the models and received feedback information.With the model-based control,less transmission may be expected than with ZOH.Finally,numerical examples and comparative experiments demonstrate the effectiveness of the proposed method.
基金Supported by National Key R&D Program of China(Grant No.2018YFB0105102)Anhui Provincial Natural Science Foundation(Grant No.2208085QE153).
文摘Automated valet parking systems based on parking automated guided vehicles(P-AGVs)are effective for improving parking convenience and increasing parking density.The ability of P-AGVs to move towards any position and attain any orientation simultaneously due to their mecanum wheels makes it convenient to transport vehicles in a parking lot.In this study,a nonlinear disturbance observer-based sliding mode controller for the trajectory tracking problem of a P-AGV is proposed.The kinematic and dynamic models for a P-AGV tracking trajectory are first analyzed in sequence and the influences of disturbing forces considered.Subsequently,a nonlinear disturbance observer(NDO)is designed to estimate the disturbing forces and torques generated by the caster wheels.Based on the designed NDO,a robust nonsingular terminal sliding-mode(NTSM)controller is used to track reference trajectories.The stabilities of the NDO and NDO-NTSM control systems are theoretically verified using their Lyapunov functions.Finally,simulations and experiments are performed to verify the effectiveness of the proposed control scheme.The experimental results show that the proposed NDO-NTSM controller can improve the trajectory tracking stability by 42-68%compared to a traditional NTSM controller.The NDO-based sliding mode controller for trajectory tracking proposed in this study can effectively reduce the impact of disturbances on trajectory tracking accuracy.
基金funded by the European Union’s Horizon 2020 Research and Innovation Program under the Marie Sklodowska-Curie Grant Agreement(Grant No.101026104)by the National Natural Science Foundation of China(Grant No.U20A6004)in part by the State Key Laboratory of Precision Electronics Manufacturing Technology and Equipment(Grant No.JMDZ202314).
文摘In semiconductor precision packaging and other applications involving alignment of automated equipment,the nonlinear motion caused by structural characteristics and friction effects on torque-type rotating motion stages seriously affects output accuracy and stability.To solve this problem,the motion characteristics of a rotating stage and the mechanism by which friction nonlinearity influences accuracy are analyzed in detail.In addition,a compound control strategy based on a kinematic model and the Stribeck friction model is designed.A friction disturbance observer based on output position feedback is improved for simple parameter tuning.Finally,an experimental system is constructed to carry out validation tests,including identification of nonlinear characteristics and performance comparisons.The experimental results show that the linear tracking error of the torque-type rotating stage is less than 1.47µm after adoption of the proposed model-based composite control strategy,and the corresponding rotary angle deviation is less than 0.0153°.The linearity of output motion is increased to 97.59%and the error compensation effect is improved by 51.6%compared with the PID control method.The experimental results confirm that the analysis method adopted here and the proposed compensation strategy can effectively reduce frictional nonlinearity and improve motion accuracy.The proposed method can also be applied to other precision electromechanical systems.
基金supported in part by the National Natural Science Foundation of China(Grant Nos.62473135 and 62173121)。
文摘This paper investigates the observer-based prescribed-time time-varying output formation-containment(PT-TV-OFC)control problem for heterogeneous multi-agent systems in which the different agents have different state dimensions.The system comprises one tracking leader,multiple formation leaders,and followers,where two types of leaders are used to generate a reference trajectory for movement and achieve specific formation,respectively.Firstly,a prescribed-time dynamics observer is constructed for the formation leaders to estimate the tracking leader's dynamic model and state.On this basis,a prescribed-time control protocol is designed for the formation leaders to achieve time-varying output formation.Then,a prescribed-time convex hull observer is designed for the followers to estimate information regarding the convex hull formed by the formation leaders.Using the estimated convex hull information,a prescribed-time containment control protocol is designed to ensure the followers converge into the convex hull.Furthermore,using Lyapunov stability theory,the stability of systems is proved in detail,which implies that the heterogeneous multi-agent systems can achieve PT-TV-OFC control.Finally,numerical simulations validate the feasibility of the theoretical results.
基金supported by the National Natural Science Foundation of China(61803015).
文摘In order to enhance the dynamic control precision of inertial stabilization platform(ISP),a disturbance sliding mode observer(DSMO)is proposed in this paper suppressing disturbance torques inherent within the system.The control accuracy of ISP is fundamentally circumscribed by various disturbance torques in rotating shaft.Therefore,a dynamic model of ISP incorporating composite perturbations is established with regard to the stabilization of axis in the inertial reference frame.Subsequently,an online estimator for control loop uncertainties based on the sliding mode control algorithm is designed to estimate the aggregate disturbances of various parameters uncertainties and other unmodeled disturbances that cannot be accurately calibrated.Finally,the proposed DSMO is integrated into a classical proportional-integral-derivative(PID)control scheme,utilizing feedforward approach to compensate the composite disturbance in the control loop online.The effectiveness of the proposed disturbance observer is validated through simulation and hardware experimentation,demonstrating a significant improvement in the dynamic control performance and robustness of the classical PID controller extensively utilized in the field of engineering.
基金supported by the National Natural Science Foundation of China(Grant No.61773142).
文摘Intercepting high-maneuverability hypersonic targets in near-space environments poses significant challenges due to their extreme speeds and evasive capabilities.To address these challenges,this study presents an integrated approach that combines a Three-Dimensional Finite-Time Optimal Cooperative Guidance Law(FTOC)with an Information Fusion Anti-saturation Predefined-time Observer(IFAPO).The proposed FTOC guidance law employs a nonlinear,non-quadratic finite-time optimal control strategy designed for rapid convergence within the limited timeframes of near-space interceptions,avoiding the need for remaining flight time estimation or linear decoupling inherent in traditional methods.To complement the guidance strategy,the IFAPO leverages multi-source information fusion theory and incorporates anti-saturation mechanisms to enhance target maneuver estimation.This method ensures accurate and real-time prediction of target acceleration while maintaining predefined convergence performance,even under complex interception conditions.By integrating the FTOC guidance law and IFAPO,the approach optimizes cooperative missile positioning,improves interception success rates,and minimizes fuel consumption,addressing practical constraints in military applications.Simulation results and comparative analyses confirm the effectiveness of the integrated approach,demonstrating its capability to achieve cooperative interception of highly maneuvering targets with enhanced efficiency and reduced economic costs,aligning with realistic combat scenarios.
