In this paper,the problem of non-singular fixed-time control with prescribed performance is studied for multi-agent systems characterized by uncertain states,nonlinearities,and nonstrict feedback.To mitigate the nonli...In this paper,the problem of non-singular fixed-time control with prescribed performance is studied for multi-agent systems characterized by uncertain states,nonlinearities,and nonstrict feedback.To mitigate the nonlinearity,a fuzzy logic algorithm is applied to approximate the intrinsic dynamics of the system.Furthermore,a fuzzy logic system state observer based on leader state information is designed to address the partial unob-servability of followers.Subsequently,the power integral method is incorporated into the backstepping approach to avoid singularities in the fixed-time controller.A command filter method is introduced into the standard backstepping approach to reduce the computational complexity of controller design.Then,a non-singular fixed-time adaptive control strategy with prescribed performance is proposed by constraining the tracking error within a prescribed range.Rigorous theoretical analysis ensures the convergence of consensus error in the multi-agent system to the prescribed performance region within a fixed time.Finally,the practicality of the algorithm is validated through numerical simulations.展开更多
This paper is dedicated to fixed-time passivity and synchronization for multi-weighted spatiotemporal directed networks.First,to achieve fixed-time passivity,a type of decentralized power-law controller is developed,i...This paper is dedicated to fixed-time passivity and synchronization for multi-weighted spatiotemporal directed networks.First,to achieve fixed-time passivity,a type of decentralized power-law controller is developed,in which only one parameter needs to be adjusted in the power-law terms;this greatly decreases the inconvenience of parameter adjustment.Second,several fixed-time passivity criteria with LMI forms are derived by using a Gauss divergence theorem to deal with the spatial diffusion of nodes and by applying the Hölder’s inequality to dispose rigorously the power-law term greater than one in the designed control scheme;this improves the previous theoretical analysis.Additionally,the fixed-time synchronization of spatiotemporal directed networks with multi-weights is addressed as a direct result of fixed-time strict passivity.Finally,a numerical example is presented in order to show the validity of the theoretical analysis.展开更多
This paper presents an adaptive multi-agent coordination(AMAC)strategy suitable for complex scenarios,which only requires information exchange between neighbouring robots.Unlike traditional multi-agent coordination me...This paper presents an adaptive multi-agent coordination(AMAC)strategy suitable for complex scenarios,which only requires information exchange between neighbouring robots.Unlike traditional multi-agent coordination methods that are solved by neural dynamics,the proposed strategy displays greater flexibility,adaptability and scalability.Furthermore,the proposed AMAC strategy is reconstructed as a time-varying complex-valued matrix equation.By introducing a dynamic error function,a fixed-time convergent zeroing neural network(FTCZNN)model is designed for the online solution of the AMAC strategy,with its convergence time upper bound derived theoretically.Finally,the effectiveness and applicability of the coordination control method are demonstrated by numerical simulations and physical experiments.Numerical results indicate that this method can reduce the formation error to the order of 10^(-6)within 1.8 s.展开更多
In this paper,a class of discontinuous Cohen-Grossberg neural networks with timevarying delays is considered.Firstly,under the extended Filippov differential inclusions framework,the problem of periodic solutions of t...In this paper,a class of discontinuous Cohen-Grossberg neural networks with timevarying delays is considered.Firstly,under the extended Filippov differential inclusions framework,the problem of periodic solutions of the considered neural networks with more relaxed conditions imposed on the amplification functions is analyzed by using set-valued mapping and Kakutani's fixed point theorem,which has rarely been used to study such problem.Secondly,the fixed-time synchronization of the error system of the considered neural networks is also investigated by designing a novel control strategy,which can improve not only the previous ones with sign function greatly,but also can reduce the chattering phenomenon.Finally,two numerical examples are presented to further illustrate the validity of the obtained results.展开更多
This paper is dedicated to solving the problem of adaptive fuzzy fault-tolerant tracking control for a class of time-varying high-order uncertain nonlinear systems.The motivation comes from how to construct a compact ...This paper is dedicated to solving the problem of adaptive fuzzy fault-tolerant tracking control for a class of time-varying high-order uncertain nonlinear systems.The motivation comes from how to construct a compact set large enough in which the approximation of any unknown continuous function by a fuzzy logic system(FLS)is effective while compensating sensor/actuator faults and external disturbances.The difficulty is to verify the boundedness of closed-loop signals on the constructed compact set and to reduce the number of the variables of the fuzzy membership functions as many as possible.By a new lemma,linear/nonlinear terms are introduced in adaptive laws to dominate unknown residual terms.With adding a power integrator method,a unified fault-tolerant controller is designed to drive the tracking error to converge to a small compact set of the origin within a fixed time,regardless of whether the system suffers from faults and disturbances.Superior to the existing results,in the presence of time-varying factors the scheme of this paper clarifies the logical relationship between the compactness of the approximation and the boundedness of the state variables.Finally,the application of control strategy is demonstrated by numerical/practical examples.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 order to achieve accurate interception of high-speed maneuvering targets,this paper presents a relative Line-of-Sight(LOS)velocity based finite-time three-dimensional guidance law design framework,and discusses the...In order to achieve accurate interception of high-speed maneuvering targets,this paper presents a relative Line-of-Sight(LOS)velocity based finite-time three-dimensional guidance law design framework,and discusses the application of fixed-time convergence disturbance observer in this framework.Firstly,a simple Lyapunov function is provided to show that the coupled terms in the relative kinematics can be ignored in the proposed guidance law design framework.Secondly,the realizations of several classical guidance laws are analyzed with the proposed framework,including TPN guidance law,finite-time Input-to-State Stability(ISS)guidance law,and sliding mode guidance law.Thirdly,fixed-time convergence disturbance observers are introduced to design the composite finite-time 3D guidance law,and Lyapunov method is employed to show the stability of the guidance system.Numerical simulations with different scenarios show that the proposed generalized guidance law performs high interception accuracy.展开更多
This paper proposes a multivariable fixed-time leaderfollower formation control method for a group of nonholonomic mobile robots, which has the ability to estimate multiple uncertainties. Firstly, based on the state s...This paper proposes a multivariable fixed-time leaderfollower formation control method for a group of nonholonomic mobile robots, which has the ability to estimate multiple uncertainties. Firstly, based on the state space model of the leader-follower formation, a multivariable fixed-time formation kinematics controller is designed. Secondly, to overcome uncertainties existing in the nonholonomic mobile robot system, such as load change,friction, external disturbance, a multivariable fixed-time torque controller based on the fixed-time disturbance observer at the dynamic level is designed. The designed torque controller is cascaded with the formation controller and finally realizes accurate estimation of the uncertain part of the system, the follower tracking of reference velocity and the desired formation of the leader and the follower in a fixed-time. The fixed-time upper bound is completely determined by the controller parameters, which is independent of the initial state of the system. The multivariable fixed-time control theory and the Lyapunov method are adopted to ensure the system stability.Finally, the effectiveness of the proposed algorithm is verified by the experimental simulation.展开更多
This paper proposes a new global fixed-time sliding mode control strategy for the trajectory tracking control of uncertain robotic manipulators.First,a fixed-time disturbance observer(FTDO) is designed to deal with th...This paper proposes a new global fixed-time sliding mode control strategy for the trajectory tracking control of uncertain robotic manipulators.First,a fixed-time disturbance observer(FTDO) is designed to deal with the adverse effects of model uncertainties and external disturbances in the manipulator systems.Then an adaptive scheme is used and the adaptive FTDO(AFTDO) is developed,so that the priori knowledge of the lumped disturbance is not required.Further,a new non-singular fast terminal sliding mode(NFTSM) surface is designed by using an arctan function,which helps to overcome the singularity problem and enhance the robustness of the system.Based on the estimation of the lumped disturbance by the AFTDO,a fixed-time non-singular fast terminal sliding mode controller(FTNFTSMC)is developed to guarantee the trajectory tracking errors converge to zero within a fixed time.The settling time is independent of the initial state of the system.In addition,the stability of the AFTDO and FTNFTSMC is strictly proved by using Lyapunov method.Finally,the fixed-time NFESM(FTNFTSM) algorithm is validated on a 2-link manipulator and comparisons with other existing sliding mode controllers(SMCs) are performed.The comparative results confirm that the FTNFTSMC has superior control performance.展开更多
To achieve the fast convergence and tracking precision of a robotic upper-limb exoskeleton,this paper proposes an observer-based integrated fixed-time control scheme with a backstepping method.Firstly,a typical 5 DoF(...To achieve the fast convergence and tracking precision of a robotic upper-limb exoskeleton,this paper proposes an observer-based integrated fixed-time control scheme with a backstepping method.Firstly,a typical 5 DoF(degrees of freedom)dynamics is constructed by Lagrange equations and processed for control purposes.Secondly,second-order sliding mode controllers(SOSMC)are developed and novel sliding mode surfaces are introduced to ensure the fixed-time convergence of the human-robot system.Both the reaching time and settling time are proved to be bounded with certain values independent of initial system conditions.For the purpose of rejecting the matched and unmatched disturbances,nonlinear fixed-time observers are employed to estimate the exact value of disturbances and compensate the controllers online.Ultimately,the synthesis of controllers and disturbance observers is adopted to achieve the excellent tracking performance and simulations are given to verify the effectiveness of the proposed control strategy.展开更多
In this paper,we investigate formation tracking control of autonomous underwater vehicles(AUVs)with model parameter uncertainties and external disturbances.The external disturbances due to the wind,waves,and ocean cur...In this paper,we investigate formation tracking control of autonomous underwater vehicles(AUVs)with model parameter uncertainties and external disturbances.The external disturbances due to the wind,waves,and ocean currents are combined with the model parameter uncertainties as a compound disturbance.Then a disturbance observer(DO)is introduced to estimate the compound disturbance,which can be achieved within a finite time independent of the initial estimation error.Based on a DO,a novel fixed-time sliding control scheme is developed,by which the follower vehicle can track the leader vehicle with all the states globally stabilized within a given settling time.The effectiveness and performance of the method are demonstrated by numerical simulations.展开更多
In this paper,the fixed-time time-varying formation of heterogeneous multi-agent systems(MASs) based on tracking error observer under denial-of-service(DoS) attacks is investigated.Firstly,the dynamic pinning strategy...In this paper,the fixed-time time-varying formation of heterogeneous multi-agent systems(MASs) based on tracking error observer under denial-of-service(DoS) attacks is investigated.Firstly,the dynamic pinning strategy is used to reconstruct the communication channel for the system that suffers from DoS attacks to prevent the discontinuous transmission information of the communication network from affecting MASs formation.Then,considering that the leader state is not available to each follower under DoS attacks,a fixed-time distributed observer without velocity information is constructed to estimate the tracking error between followers and the leader.Finally,adaptive radial basis function neural network(RBFNN) is used to approximate the unknown ensemble disturbances in the system,and the fixed-time time-varying formation scheme is designed with the constructed observer.The effectiveness of the proposed control algorithm is demonstrated by the numerical simulation.展开更多
High-speed Electromagnetic Suspension(EMS)train is continuously impacted by the irregularity of the track,which worsens the levitation performance of the train.In this paper,a composite control scheme for the EMS is p...High-speed Electromagnetic Suspension(EMS)train is continuously impacted by the irregularity of the track,which worsens the levitation performance of the train.In this paper,a composite control scheme for the EMS is proposed to suppress track irregularities by integrating a Refined Disturbance Observer(RDO)and a Prescribed Performance Fixed-Time Controller(PPFTC).The RDO is designed to estimate precisely the track irregularities and lumped disturbances with uncertainties and exogenous disturbances in the suspension system,and reduce input chattering by applying to the disturbance compensation channel.PPFTC is designed to converge the suspension air gap error to equilibrium point with prescribed performance by completing error conversion,and solve the fast dynamic issue of EMS.And the boundary of overshoot and steady-state is limited in the ranged prescribed.A theoretical analysis is conducted on the stability of the proposed control method.Finally,the effectiveness and reasonability of the proposed composite anti-disturbance control scheme is verified by simulation results.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
This paper presents an investigation on the target-guided coordinated control(TACC)of unmanned surface vehicles(USVs).In the scenario of tracking non-cooperative targets,the status information of the target can only b...This paper presents an investigation on the target-guided coordinated control(TACC)of unmanned surface vehicles(USVs).In the scenario of tracking non-cooperative targets,the status information of the target can only be obtained by some USVs.In order to achieve semi-encirclement tracking of noncooperative targets under maritime security conditions,a fixed-time tracking control method based on dynamic surface control(DSC)is proposed in this paper.Firstly,a novel TACC architecture with decoupled kinematic control law and decoupled kinetic control law was designed to reduce the complexity of control system design.Secondly,the proposed DSC-based target-guided kinematic control law including tracking points pre-allocation strategy and sigmoid artificial potential functions(SigAPFs)can avoid collisions during tracking process and optimize kinematic control output.Finally,a fixed-time TACC system was proposed to achieve fast convergence of kinematic and kinetics errors.The effectiveness of the proposed TACC approach in improving target tracking safety and reducing control output chattering was verified by simulation comparison results.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
基金supported by the National Natural Science Foundation of China(62203356).
文摘In this paper,the problem of non-singular fixed-time control with prescribed performance is studied for multi-agent systems characterized by uncertain states,nonlinearities,and nonstrict feedback.To mitigate the nonlinearity,a fuzzy logic algorithm is applied to approximate the intrinsic dynamics of the system.Furthermore,a fuzzy logic system state observer based on leader state information is designed to address the partial unob-servability of followers.Subsequently,the power integral method is incorporated into the backstepping approach to avoid singularities in the fixed-time controller.A command filter method is introduced into the standard backstepping approach to reduce the computational complexity of controller design.Then,a non-singular fixed-time adaptive control strategy with prescribed performance is proposed by constraining the tracking error within a prescribed range.Rigorous theoretical analysis ensures the convergence of consensus error in the multi-agent system to the prescribed performance region within a fixed time.Finally,the practicality of the algorithm is validated through numerical simulations.
基金supported by the National Natural Science Foundation of China(62373317)the Tianshan Talent Training Program(2022TSYCCX0013)+3 种基金the Key Project of Natural Science Foundation of Xinjiang(2021D01D10)the Basic Research Foundation for Universities of Xinjiang(XJEDU2023P023)the Xinjiang Key Laboratory of Applied Mathematics(XJDX1401)the Intelligent Control and Optimization Research Platform in Xinjiang University.
文摘This paper is dedicated to fixed-time passivity and synchronization for multi-weighted spatiotemporal directed networks.First,to achieve fixed-time passivity,a type of decentralized power-law controller is developed,in which only one parameter needs to be adjusted in the power-law terms;this greatly decreases the inconvenience of parameter adjustment.Second,several fixed-time passivity criteria with LMI forms are derived by using a Gauss divergence theorem to deal with the spatial diffusion of nodes and by applying the Hölder’s inequality to dispose rigorously the power-law term greater than one in the designed control scheme;this improves the previous theoretical analysis.Additionally,the fixed-time synchronization of spatiotemporal directed networks with multi-weights is addressed as a direct result of fixed-time strict passivity.Finally,a numerical example is presented in order to show the validity of the theoretical analysis.
基金supported by the National Natural Science Foundation of China under Grants 61962023,61562029 and 62466019.
文摘This paper presents an adaptive multi-agent coordination(AMAC)strategy suitable for complex scenarios,which only requires information exchange between neighbouring robots.Unlike traditional multi-agent coordination methods that are solved by neural dynamics,the proposed strategy displays greater flexibility,adaptability and scalability.Furthermore,the proposed AMAC strategy is reconstructed as a time-varying complex-valued matrix equation.By introducing a dynamic error function,a fixed-time convergent zeroing neural network(FTCZNN)model is designed for the online solution of the AMAC strategy,with its convergence time upper bound derived theoretically.Finally,the effectiveness and applicability of the coordination control method are demonstrated by numerical simulations and physical experiments.Numerical results indicate that this method can reduce the formation error to the order of 10^(-6)within 1.8 s.
基金Supported by the National Natural Science Foundation of China(62576008)University Annual Scientific Research Plan of Anhui Province(2022AH030023)。
文摘In this paper,a class of discontinuous Cohen-Grossberg neural networks with timevarying delays is considered.Firstly,under the extended Filippov differential inclusions framework,the problem of periodic solutions of the considered neural networks with more relaxed conditions imposed on the amplification functions is analyzed by using set-valued mapping and Kakutani's fixed point theorem,which has rarely been used to study such problem.Secondly,the fixed-time synchronization of the error system of the considered neural networks is also investigated by designing a novel control strategy,which can improve not only the previous ones with sign function greatly,but also can reduce the chattering phenomenon.Finally,two numerical examples are presented to further illustrate the validity of the obtained results.
基金supported by National Natural Science Foundation of China[grant number 62173208]Taishan Scholar Project of Shandong Province of China[grant number tsqn202103061]。
文摘This paper is dedicated to solving the problem of adaptive fuzzy fault-tolerant tracking control for a class of time-varying high-order uncertain nonlinear systems.The motivation comes from how to construct a compact set large enough in which the approximation of any unknown continuous function by a fuzzy logic system(FLS)is effective while compensating sensor/actuator faults and external disturbances.The difficulty is to verify the boundedness of closed-loop signals on the constructed compact set and to reduce the number of the variables of the fuzzy membership functions as many as possible.By a new lemma,linear/nonlinear terms are introduced in adaptive laws to dominate unknown residual terms.With adding a power integrator method,a unified fault-tolerant controller is designed to drive the tracking error to converge to a small compact set of the origin within a fixed time,regardless of whether the system suffers from faults and disturbances.Superior to the existing results,in the presence of time-varying factors the scheme of this paper clarifies the logical relationship between the compactness of the approximation and the boundedness of the state variables.Finally,the application of control strategy is demonstrated by numerical/practical examples.
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.
文摘In order to achieve accurate interception of high-speed maneuvering targets,this paper presents a relative Line-of-Sight(LOS)velocity based finite-time three-dimensional guidance law design framework,and discusses the application of fixed-time convergence disturbance observer in this framework.Firstly,a simple Lyapunov function is provided to show that the coupled terms in the relative kinematics can be ignored in the proposed guidance law design framework.Secondly,the realizations of several classical guidance laws are analyzed with the proposed framework,including TPN guidance law,finite-time Input-to-State Stability(ISS)guidance law,and sliding mode guidance law.Thirdly,fixed-time convergence disturbance observers are introduced to design the composite finite-time 3D guidance law,and Lyapunov method is employed to show the stability of the guidance system.Numerical simulations with different scenarios show that the proposed generalized guidance law performs high interception accuracy.
基金supported by the National Natural Science Foundation of China(61872204)the Natural Science Foundation of Heilongjiang Province of China(F2015025)。
文摘This paper proposes a multivariable fixed-time leaderfollower formation control method for a group of nonholonomic mobile robots, which has the ability to estimate multiple uncertainties. Firstly, based on the state space model of the leader-follower formation, a multivariable fixed-time formation kinematics controller is designed. Secondly, to overcome uncertainties existing in the nonholonomic mobile robot system, such as load change,friction, external disturbance, a multivariable fixed-time torque controller based on the fixed-time disturbance observer at the dynamic level is designed. The designed torque controller is cascaded with the formation controller and finally realizes accurate estimation of the uncertain part of the system, the follower tracking of reference velocity and the desired formation of the leader and the follower in a fixed-time. The fixed-time upper bound is completely determined by the controller parameters, which is independent of the initial state of the system. The multivariable fixed-time control theory and the Lyapunov method are adopted to ensure the system stability.Finally, the effectiveness of the proposed algorithm is verified by the experimental simulation.
基金partially supported by the National Natural Science Foundation of China (62322315,61873237)Zhejiang Provincial Natural Science Foundation of China for Distinguished Young Scholars(LR22F030003)+2 种基金the National Key Rearch and Development Funding(2018YFB1403702)the Key Rearch and Development Programs of Zhejiang Province (2023C01224)Major Project of Science and Technology Innovation in Ningbo City (2019B1003)。
文摘This paper proposes a new global fixed-time sliding mode control strategy for the trajectory tracking control of uncertain robotic manipulators.First,a fixed-time disturbance observer(FTDO) is designed to deal with the adverse effects of model uncertainties and external disturbances in the manipulator systems.Then an adaptive scheme is used and the adaptive FTDO(AFTDO) is developed,so that the priori knowledge of the lumped disturbance is not required.Further,a new non-singular fast terminal sliding mode(NFTSM) surface is designed by using an arctan function,which helps to overcome the singularity problem and enhance the robustness of the system.Based on the estimation of the lumped disturbance by the AFTDO,a fixed-time non-singular fast terminal sliding mode controller(FTNFTSMC)is developed to guarantee the trajectory tracking errors converge to zero within a fixed time.The settling time is independent of the initial state of the system.In addition,the stability of the AFTDO and FTNFTSMC is strictly proved by using Lyapunov method.Finally,the fixed-time NFESM(FTNFTSM) algorithm is validated on a 2-link manipulator and comparisons with other existing sliding mode controllers(SMCs) are performed.The comparative results confirm that the FTNFTSMC has superior control performance.
基金supported by National Natural Science Foundation of China (Nos. 61703134, 61703135, 61773151, 61503118 and 61871173)Natural Science Foundation of Hebei Province (Nos. F2015202150, F2016202327 and F2018202279)+3 种基金Natural Science Foundation of Tianjin (No. 17JCQNJC04400)the Foundation of Hebei Educational Committee (Nos. QN2015068 and ZD2016071)the Colleges and Universities in Hebei Province Science and Technology Research Youth Fund (No. ZC2016020)the Graduate Innovation Funding Project of Hebei Province (No. CXZZBS2017038)
文摘To achieve the fast convergence and tracking precision of a robotic upper-limb exoskeleton,this paper proposes an observer-based integrated fixed-time control scheme with a backstepping method.Firstly,a typical 5 DoF(degrees of freedom)dynamics is constructed by Lagrange equations and processed for control purposes.Secondly,second-order sliding mode controllers(SOSMC)are developed and novel sliding mode surfaces are introduced to ensure the fixed-time convergence of the human-robot system.Both the reaching time and settling time are proved to be bounded with certain values independent of initial system conditions.For the purpose of rejecting the matched and unmatched disturbances,nonlinear fixed-time observers are employed to estimate the exact value of disturbances and compensate the controllers online.Ultimately,the synthesis of controllers and disturbance observers is adopted to achieve the excellent tracking performance and simulations are given to verify the effectiveness of the proposed control strategy.
基金supported in part by the National Natural Science Foundation of China(61573077,U1808205)the National Key Research and Development Program of China(2017YFA0700300)
文摘In this paper,we investigate formation tracking control of autonomous underwater vehicles(AUVs)with model parameter uncertainties and external disturbances.The external disturbances due to the wind,waves,and ocean currents are combined with the model parameter uncertainties as a compound disturbance.Then a disturbance observer(DO)is introduced to estimate the compound disturbance,which can be achieved within a finite time independent of the initial estimation error.Based on a DO,a novel fixed-time sliding control scheme is developed,by which the follower vehicle can track the leader vehicle with all the states globally stabilized within a given settling time.The effectiveness and performance of the method are demonstrated by numerical simulations.
文摘In this paper,the fixed-time time-varying formation of heterogeneous multi-agent systems(MASs) based on tracking error observer under denial-of-service(DoS) attacks is investigated.Firstly,the dynamic pinning strategy is used to reconstruct the communication channel for the system that suffers from DoS attacks to prevent the discontinuous transmission information of the communication network from affecting MASs formation.Then,considering that the leader state is not available to each follower under DoS attacks,a fixed-time distributed observer without velocity information is constructed to estimate the tracking error between followers and the leader.Finally,adaptive radial basis function neural network(RBFNN) is used to approximate the unknown ensemble disturbances in the system,and the fixed-time time-varying formation scheme is designed with the constructed observer.The effectiveness of the proposed control algorithm is demonstrated by the numerical simulation.
基金supported by the National Natural Science Foundation of China(Grant 62273029).
文摘High-speed Electromagnetic Suspension(EMS)train is continuously impacted by the irregularity of the track,which worsens the levitation performance of the train.In this paper,a composite control scheme for the EMS is proposed to suppress track irregularities by integrating a Refined Disturbance Observer(RDO)and a Prescribed Performance Fixed-Time Controller(PPFTC).The RDO is designed to estimate precisely the track irregularities and lumped disturbances with uncertainties and exogenous disturbances in the suspension system,and reduce input chattering by applying to the disturbance compensation channel.PPFTC is designed to converge the suspension air gap error to equilibrium point with prescribed performance by completing error conversion,and solve the fast dynamic issue of EMS.And the boundary of overshoot and steady-state is limited in the ranged prescribed.A theoretical analysis is conducted on the stability of the proposed control method.Finally,the effectiveness and reasonability of the proposed composite anti-disturbance control scheme is verified by simulation results.
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This paper presents an investigation on the target-guided coordinated control(TACC)of unmanned surface vehicles(USVs).In the scenario of tracking non-cooperative targets,the status information of the target can only be obtained by some USVs.In order to achieve semi-encirclement tracking of noncooperative targets under maritime security conditions,a fixed-time tracking control method based on dynamic surface control(DSC)is proposed in this paper.Firstly,a novel TACC architecture with decoupled kinematic control law and decoupled kinetic control law was designed to reduce the complexity of control system design.Secondly,the proposed DSC-based target-guided kinematic control law including tracking points pre-allocation strategy and sigmoid artificial potential functions(SigAPFs)can avoid collisions during tracking process and optimize kinematic control output.Finally,a fixed-time TACC system was proposed to achieve fast convergence of kinematic and kinetics errors.The effectiveness of the proposed TACC approach in improving target tracking safety and reducing control output chattering was verified by simulation comparison results.
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.
