Presents a one grade adaptive controller with one reference model which is built according to δ MRACS adaptive control theory and used to control an actual high order hydraulic system, and the whole hardware system u...Presents a one grade adaptive controller with one reference model which is built according to δ MRACS adaptive control theory and used to control an actual high order hydraulic system, and the whole hardware system used, which includes a AT89C51 single chip microcomputer, 74Ls373 flip latch, 6116 store, eight bit ADC0809, and so on, and the satisfactory results obtained in study on hydraulic control system.展开更多
In this paper, we conduct research on the unmanned aerial vehicle adaptive control system based on fuzzy control and chaosmechanics. Four rotor aircraft is a kind of nonlinear systems with underactuated, strong coupli...In this paper, we conduct research on the unmanned aerial vehicle adaptive control system based on fuzzy control and chaosmechanics. Four rotor aircraft is a kind of nonlinear systems with underactuated, strong coupling characteristic. Although in existing research,through the design of the control algorithm effectively inhibits both for fl ight control effect, but not fundamentally eliminate the effect of aircraft.Dynamic model of unmanned helicopter fl ight control system design is very approximate, need to gradually improve the modeling accuracy, soas to get the exact autonomous fl ight control, so you need to practice constantly required to modeling in the fl ight information, so the unmannedhelicopter fl ight control system to have the ability to retrieve information modeling. This paper proposes the new idea on the issues that will bemeaningful.展开更多
Based on the analysis of the mechanism of wire tension control by using torque motors in the multi-wire saw machining process, some mathematical models of a tension control system are studied, and an adaptive algo- ri...Based on the analysis of the mechanism of wire tension control by using torque motors in the multi-wire saw machining process, some mathematical models of a tension control system are studied, and an adaptive algo- rithm is designed for controlling the wire tension. In this algorithm of tension control, the rotation speeds and waving angle of motors are measured and fed back to the controller, and the NLMS（ normalized least mean squares） algorithm is used to calculate the adaptive correction value and control the wire tension accurately. The computer simulation results in Matlab software validate the high accuracy for controlling the system of the wire tension with the NLMS algorithm in the multi-wire saw machining process.展开更多
This article presents an adaptive optimal control method for a semi-active suspension system.The model of the suspension system is built,in which the components of uncertain parameters and exogenous disturbance are de...This article presents an adaptive optimal control method for a semi-active suspension system.The model of the suspension system is built,in which the components of uncertain parameters and exogenous disturbance are described.The adaptive optimal control law consists of the sum of the optimal control component and the adaptive control component.First,the optimal control law is designed for the model of the suspension system after ignoring the components of uncertain parameters and exogenous disturbance caused by the road surface.The optimal control law expresses the desired dynamic characteristics of the suspension system.Next,the adaptive component is designed with the purpose of compensating for the effects caused by uncertain parameters and exogenous disturbance caused by the road surface;the adaptive component has adaptive parameter rules to estimate uncertain parameters and exogenous disturbance.When exogenous disturbances are eliminated,the system responds with an optimal controller designed.By separating theoretically the dynamic of a semi-active suspension system,this solution allows the design of two separate controllers easily and has reduced the computational burden and the use of too many tools,thus allowing for more convenient hardware implementation.The simulation results also show the effectiveness of damping oscillations of the proposed solution in this article.展开更多
The paper proposes a method for solving the problem of synthesis of an adaptive control system for unstable and deterministic chaotic processes in the class of‘dovetail’catastrophes for objects with m-inputs and n-o...The paper proposes a method for solving the problem of synthesis of an adaptive control system for unstable and deterministic chaotic processes in the class of‘dovetail’catastrophes for objects with m-inputs and n-outputs.The synthesis problem is solved by the gradient-velocity method of Lyapunov vector functions.From the conditions of the aperiodic robust stability of the etalon model with the desired dynamics of the main control loop and the generalised configurable object,the control goal is achieved.One of the most promising ways of solving the problem of managing unstable and deterministic chaotic processes is the synthesis of a control system in the class of‘swallowtail’catastrophes and the use of adaptation methods.Selecting and studying a reference model,and employing the gradient-velocity method for a generalised configurable control object ensure robust stability,utilise current information effectively,and achieve desired system quality and management goals.展开更多
Aeropropulsion System Test Facility (ASTF) is required to accurately control the pressure and temperature of the airflow to test the performance of the aero-engine. However, the control accuracy of ASTF is significant...Aeropropulsion System Test Facility (ASTF) is required to accurately control the pressure and temperature of the airflow to test the performance of the aero-engine. However, the control accuracy of ASTF is significantly affected by the flow disturbance caused by aero-engine acceleration and deceleration. This would reduce the credibility of ASTF’s test results for the aero-engine. Therefore, first, this paper proposes a feedforward compensation-based L1 adaptive control method for ASTF to address this problem. The baseline controller is first designed based on ideal uncoupled closed-loop dynamics to achieve dynamic decoupling. Then, L1 adaptive control is adopted to deal with various uncertainties and ensure good control performance. To further enhance the anti-disturbance performance, a feedforward strategy based on disturbance prediction is designed in the L1 adaptive control framework to compensate for the unmatched flow disturbance, which cannot be measured directly. In addition, this strategy takes into account the effects of actuator dynamics. With this method, the feedforward term can be determined from the nominal model parameters despite uncertainties. Finally, to demonstrate the effectiveness of the proposed method, various comparative experiments are performed on a hardware-in-the-loop system of ASTF. The experimental results show that the proposed method possesses excellent tracking performance, anti-disturbance performance and robustness.展开更多
In this paper,a pair of dynamic high-gain observer and output feedback controller is proposed for nonlinear systems with multiple unknown time delays.By constructing Lyapunov-Krasovskii functionals,it shows that globa...In this paper,a pair of dynamic high-gain observer and output feedback controller is proposed for nonlinear systems with multiple unknown time delays.By constructing Lyapunov-Krasovskii functionals,it shows that global state asymptotic regulation can be ensured by introducing a single dynamic gain;furthermore,global asymptotic stabilization can be achieved by choosing a sufficiently large static scaling gain when the upper bounds of all system parameters are known.Especially,the output coefficient is allowed to be non-differentiable with unknown upper bound.This paper proposes a generalized Lyapunov matrix inequality based dynamic-gain scaling method,which significantly simplifies the design computational complexity by comparing with the classic backstepping method.展开更多
In this paper, a fault-tolerant-based online critic learning algorithm is developed to solve the optimal tracking control issue for nonaffine nonlinear systems with actuator faults.First, a novel augmented plant is co...In this paper, a fault-tolerant-based online critic learning algorithm is developed to solve the optimal tracking control issue for nonaffine nonlinear systems with actuator faults.First, a novel augmented plant is constructed by fusing the system state and the reference trajectory, which aims to transform the optimal fault-tolerant tracking control design with actuator faults into the optimal regulation problem of the conventional nonlinear error system. Subsequently, in order to ensure the normal execution of the online learning algorithm, a stability criterion condition is created to obtain an initial admissible tracking policy. Then, the constructed model neural network(NN) is pretrained to recognize the system dynamics and calculate trajectory control. The critic and action NNs are constructed to output the approximate cost function and approximate tracking control,respectively. The Hamilton-Jacobi-Bellman equation of the error system is solved online through the action-critic framework. In theoretical analysis, it is proved that all concerned signals are uniformly ultimately bounded according to the Lyapunov principle.The tracking control law can approach the optimal tracking control within a finite approximation error. Finally, two experimental examples are conducted to indicate the effectiveness and superiority of the developed fault-tolerant tracking control scheme.展开更多
The increasing penetration of second-life battery energy storage systems(SLBESS)in power grids presents substantial challenges to system operation and control due to the heterogeneous characteristics and uncertain deg...The increasing penetration of second-life battery energy storage systems(SLBESS)in power grids presents substantial challenges to system operation and control due to the heterogeneous characteristics and uncertain degradation patterns of repurposed batteries.This paper presents a novel model-free adaptive voltage controlembedded dung beetle-inspired heuristic optimization algorithmfor optimal SLBESS capacity configuration and power dispatch.To simultaneously address the computational complexity and ensure system stability,this paper develops a comprehensive bilevel optimization framework.At the upper level,a dung beetle optimization algorithmdetermines the optimal SLBESS capacity configuration byminimizing total lifecycle costswhile incorporating the charging/discharging power trajectories derived from the model-free adaptive voltage control strategy.At the lower level,a health-priority power dispatch optimization model intelligently allocates power demands among heterogeneous battery groups based on their real-time operational states,state-of-health variations,and degradation constraints.The proposed model-free approach circumvents the need for complex battery charging/discharging power controlmodels and extensive historical data requirements whilemaintaining system stability through adaptive controlmechanisms.A novel cycle life degradation model is developed to quantify the relationship between remaining useful life,depth of discharge,and operational patterns.The integrated framework enables simultaneous strategic planning and operational control,ensuring both economic efficiency and extended battery lifespan.The effectiveness of the proposed method is validated through comprehensive case studies on hybrid energy storage systems,demonstrating superior computational efficiency,robust performance across different network configurations,and significant improvements in battery utilization compared to conventional approaches.展开更多
In this paper, the containment control problem in nonlinear multi-agent systems(NMASs) under denial-of-service(DoS) attacks is addressed. Firstly, a prediction model is obtained using the broad learning technique to t...In this paper, the containment control problem in nonlinear multi-agent systems(NMASs) under denial-of-service(DoS) attacks is addressed. Firstly, a prediction model is obtained using the broad learning technique to train historical data generated by the system offline without DoS attacks. Secondly, the dynamic linearization method is used to obtain the equivalent linearization model of NMASs. Then, a novel model-free adaptive predictive control(MFAPC) framework based on historical and online data generated by the system is proposed, which combines the trained prediction model with the model-free adaptive control method. The development of the MFAPC method motivates a much simpler robust predictive control solution that is convenient to use in the case of DoS attacks. Meanwhile, the MFAPC algorithm provides a unified predictive framework for solving consensus tracking and containment control problems. The boundedness of the containment error can be proven by using the contraction mapping principle and the mathematical induction method. Finally, the proposed MFAPC is assessed through comparative experiments.展开更多
A tracking stability control problem for the vertical electric stabilization system of moving tank based on adaptive robust servo control is addressed.This paper mainly focuses on two types of possibly fast timevaryin...A tracking stability control problem for the vertical electric stabilization system of moving tank based on adaptive robust servo control is addressed.This paper mainly focuses on two types of possibly fast timevarying but bounded uncertainty within the vertical electric stabilization system:model parameter uncertainty and uncertain nonlinearity.First,the vertical electric stabilization system is constructed as an uncertain nonlinear dynamic system that can reflect the practical mechanics transfer process of the system.Second,the dynamical equation in the form of state space is established by designing the angular tracking error.Third,the comprehensive parameter of system uncertainty is designed to estimate the most conservative effects of uncertainty.Finally,an adaptive robust servo control which can effectively handle the combined effects of complex nonlinearity and uncertainty is proposed.The feasibility of the proposed control strategy under the practical physical condition is validated through the tests on the experimental platform.This paper pioneers the introduction of the internal nonlinearity and uncertainty of the vertical electric stabilization system into the settlement of the tracking stability control problem,and validates the advanced servo control strategy through experiment for the first time.展开更多
This paper investigates the adaptive fuzzy finite-time output-feedback fault-tolerant control (FTC) problemfor a class of nonlinear underactuated wheeled mobile robots (UWMRs) system with intermittent actuatorfaults. ...This paper investigates the adaptive fuzzy finite-time output-feedback fault-tolerant control (FTC) problemfor a class of nonlinear underactuated wheeled mobile robots (UWMRs) system with intermittent actuatorfaults. The UWMR system includes unknown nonlinear dynamics and immeasurable states. Fuzzy logic systems(FLSs) are utilized to work out immeasurable functions. Furthermore, with the support of the backsteppingcontrol technique and adaptive fuzzy state observer, a fuzzy adaptive finite-time output-feedback FTC scheme isdeveloped under the intermittent actuator faults. It is testifying the scheme can ensure the controlled nonlinearUWMRs is stable and the estimation errors are convergent. Finally, the comparison results and simulationvalidate the effectiveness of the proposed fuzzy adaptive finite-time FTC approach.展开更多
Since backlash nonlinearity is inevitably existing in actuators for bidirectional stabilization system of allelectric tank,it behaves more drastically in high maneuvering environments.In this work,the accurate trackin...Since backlash nonlinearity is inevitably existing in actuators for bidirectional stabilization system of allelectric tank,it behaves more drastically in high maneuvering environments.In this work,the accurate tracking control for bidirectional stabilization system of moving all-electric tank with actuator backlash and unmodeled disturbance is solved.By utilizing the smooth adaptive backlash inverse model,a nonlinear robust adaptive feedback control scheme is presented.The unknown parameters and unmodelled disturbance are addressed separately through the derived parametric adaptive function and the continuous nonlinear robust term.Because the unknown backlash parameters are updated via adaptive function and the backlash effect can be suppressed successfully by inverse operation,which ensures the system stability.Meanwhile,the system disturbance in the high maneuverable environment can be estimated with the constructed adaptive law online improving the engineering practicality.Finally,Lyapunov-based analysis proves that the developed controller can ensure the tracking error asymptotically converges to zero even with unmodeled disturbance and unknown actuator backlash.Contrast co-simulations and experiments illustrate the advantages of the proposed approach.展开更多
This paper mainly focuses on the development of a learning-based controller for a class of uncertain mechanical systems modeled by the Euler-Lagrange formulation.The considered system can depict the behavior of a larg...This paper mainly focuses on the development of a learning-based controller for a class of uncertain mechanical systems modeled by the Euler-Lagrange formulation.The considered system can depict the behavior of a large class of engineering systems,such as vehicular systems,robot manipulators and satellites.All these systems are often characterized by highly nonlinear characteristics,heavy modeling uncertainties and unknown perturbations,therefore,accurate-model-based nonlinear control approaches become unavailable.Motivated by the challenge,a reinforcement learning(RL)adaptive control methodology based on the actor-critic framework is investigated to compensate the uncertain mechanical dynamics.The approximation inaccuracies caused by RL and the exogenous unknown disturbances are circumvented via a continuous robust integral of the sign of the error(RISE)control approach.Different from a classical RISE control law,a tanh(·)function is utilized instead of a sign(·)function to acquire a more smooth control signal.The developed controller requires very little prior knowledge of the dynamic model,is robust to unknown dynamics and exogenous disturbances,and can achieve asymptotic output tracking.Eventually,co-simulations through ADAMS and MATLAB/Simulink on a three degrees-of-freedom(3-DOF)manipulator and experiments on a real-time electromechanical servo system are performed to verify the performance of the proposed approach.展开更多
This paper deeply introduces a brand-new research method for the synchronous characteristics of DC microgrid bus voltage and an improved synchronous control strategy.This method mainly targets the problem of bus volta...This paper deeply introduces a brand-new research method for the synchronous characteristics of DC microgrid bus voltage and an improved synchronous control strategy.This method mainly targets the problem of bus voltage oscillation caused by the bifurcation behavior of DC microgrid converters.Firstly,the article elaborately establishes a mathematical model of a single distributed power source with hierarchical control.On this basis,a smallworld network model that can better adapt to the topology structure of DC microgrids is further constructed.Then,a voltage synchronization analysis method based on the main stability function is proposed,and the synchronous characteristics of DC bus voltage are deeply studied by analyzing the size of the minimum non-zero eigenvalue.In view of the situation that the line coupling strength between distributed power sources is insufficient to achieve bus voltage synchronization,this paper innovatively proposes a new improved adaptive controller to effectively control voltage synchronization.And the convergence of the designed controller is strictly proved by using Lyapunov’s stability theorem.Finally,the effectiveness and feasibility of the designed controller in this paper are fully verified through detailed simulation experiments.After comparative analysis with the traditional adaptive controller,it is found that the newly designed controller can make the bus voltages of each distributed power source achieve synchronization more quickly,and is significantly superior to the traditional adaptive controller in terms of anti-interference performance.展开更多
In this study,we consider a single-link flexible manipulator in the presence of an unknown Bouc-Wen type of hysteresis and intermittent actuator faults.First,an inverse hysteresis dynamics model is introduced,and then...In this study,we consider a single-link flexible manipulator in the presence of an unknown Bouc-Wen type of hysteresis and intermittent actuator faults.First,an inverse hysteresis dynamics model is introduced,and then the control input is divided into an expected input and an error compensator.Second,a novel adaptive neural network-based control scheme is proposed to cancel the unknown input hysteresis.Subsequently,by modifying the adaptive laws and local control laws,a fault-tolerant control strategy is applied to address uncertain intermittent actuator faults in a flexible manipulator system.Through the direct Lyapunov theory,the proposed scheme allows the state errors to asymptotically converge to a specified interval.Finally,the effectiveness of the proposed scheme is verified through numerical simulations and experiments.展开更多
The development of the adaptive cycle engine is a crucial direction of advanced fighter power sources in the near future.However,this new technology brings more uncertainty to the design of the control system.To addre...The development of the adaptive cycle engine is a crucial direction of advanced fighter power sources in the near future.However,this new technology brings more uncertainty to the design of the control system.To address the versatile thrust demand under complex dynamic characteristics of the adaptive cycle engine,this paper proposes a direct thrust estimation and control method based on the Model-Free Adaptive Control(MFAC)algorithm.First,an improved Sliding Mode Control-MFAC(SMC-MFAC)algorithm has been developed by introducing a sliding mode variable structure into the standard Full Format Dynamic Linearization-MFAC(FFDL-MFAC)and designing self-adaptive weight coefficients.Then a trivariate double-loop direct thrust control structure with a controller-based thrust estimator and an outer command compensation loop has been established.Through thrust feedback and command correction,accurate control under multi-mode and operation conditions is achieved.The main contribution of this paper is the improved algorithm that combines the tracking capability of the MFAC and the robustness of the SMC,thus enhancing the dynamic performance.Considering the requirements of the online thrust feedback,the designed MFAC-based thrust estimator significantly speeds up the calculation.Additionally,the proposed command correction module can achieve the adaptive thrust control without affecting the operation of the inner loop.Simulations and Hardware-in-Loop(HIL)experiments have been performed on an adaptive cycle engine component-level model to investigate the estimation and control effect under different modes and health conditions.The results demonstrate that both the thrust estimation precision and operation speed are significantly improved compared with Extended Kalman Filter(EKF).Furthermore,the system can accelerate the response of the controlled plant,reduce the overshoot,and realize the thrust recovery within the safety range when the engine encounters the degradation.展开更多
To overcome the challenges associated with predicting gas extraction performance and mitigating the gradual decline in extraction volume,which adversely impacts gas utilization efficiency in mines,a gas extraction pur...To overcome the challenges associated with predicting gas extraction performance and mitigating the gradual decline in extraction volume,which adversely impacts gas utilization efficiency in mines,a gas extraction pure volume prediction model was developed using Support Vector Regression(SVR)and Random Forest(RF),with hyperparameters fine-tuned via the Genetic Algorithm(GA).Building upon this,an adaptive control model for gas extraction negative pressure was formulated to maximize the extracted gas volume within the pipeline network,followed by field validation experiments.Experimental results indicate that the GA-SVR model surpasses comparable models in terms of mean absolute error,root mean square error,and mean absolute percentage error.In the extraction process of bedding boreholes,the influence of negative pressure on gas extraction concentration diminishes over time,yet it remains a critical factor in determining the extracted pure volume.In contrast,throughout the entire extraction period of cross-layer boreholes,both extracted pure volume and concentration exhibit pronounced sensitivity to fluctuations in extraction negative pressure.Field experiments demonstrated that the adaptive controlmodel enhanced the average extracted gas volume by 5.08% in the experimental borehole group compared to the control group during the later extraction stage,with a more pronounced increase of 7.15% in the first 15 days.The research findings offer essential technical support for the efficient utilization and long-term sustainable development of mine gas resources.The research findings offer essential technical support for gas disaster mitigation and the sustained,efficient utilization of mine gas.展开更多
Tracking control of tendon-driven manipulators has become a prevalent research area.However,the existence of flexible elastic tendons generates substantial residual vibrations,resulting in difficulties for trajectory ...Tracking control of tendon-driven manipulators has become a prevalent research area.However,the existence of flexible elastic tendons generates substantial residual vibrations,resulting in difficulties for trajectory tracking control of the manipulator.This paper proposes the radial basis function neural network adaptive hierarchical sliding mode control(RBFNNA-HSMC)method,which combines the dynamic model of the elastic tendon-driven manipulator(ETDM)with radial basis neural network adaptive control and hierarchical sliding mode control technology.The aim is to achieve trajectory tracking control of ETDM even under conditions of model inaccuracy and disturbance.The Lyapunov stability theory demonstrates the stability of the proposed RBFNNA-HSM controller.In order to assess the effectiveness and adaptability of the proposed control method,simulations and experiments were performed on a two-DOF ETDM.The RBFNNA-HSM method shows superior tracking accuracy compared to traditional modelbased HSM control.The experiment shows that the maximum tracking error for ETDM double-joint trajectory tracking is below 2.593×10-3rad and 1.624×10-3rad,respectively.展开更多
Aiming at the problems of large fluctuation of output active power and poor control performance in the process of frequency support of an energy-storage-type static-var-generator(ESVG),the adaptive adjustment control ...Aiming at the problems of large fluctuation of output active power and poor control performance in the process of frequency support of an energy-storage-type static-var-generator(ESVG),the adaptive adjustment control method for its active-loop parameters is used to realize thewind-farmfrequency support,which has become the current research hotspot.Taking the ESVG with a supercapacitor on the DC side as the research object,the influence trend of the change of virtual rotation inertia and virtual damping coefficient on its virtual angular velocity and power angle is analyzed.Then,the constraint relationship between the equivalent virtual inertia time constant of the supercapacitor and the virtual rotation inertia of the ESVG is clarified.Then,combined with the second-order response characteristics of the ESVG power control loop,the selection principles of the frequency modulation coefficient,the virtual rotation inertia,and the virtual damping coefficient are determined.An ESVG adjustment control method,considering the adaptive adjustment of the active loop parameters of the supercapacitor equivalent inertia,is proposed.While ensuring the frequency support capability of the ESVG,the fluctuation degree of its output active power and the virtual angular velocity are suppressed,and the proposed adjustment method also improves the stability of the ESVG control system and the frequency support capability for the wind farm.Finally,the simulation verifies the correctness of the theoretical analysis and the effectiveness of the proposed strategy.展开更多
文摘Presents a one grade adaptive controller with one reference model which is built according to δ MRACS adaptive control theory and used to control an actual high order hydraulic system, and the whole hardware system used, which includes a AT89C51 single chip microcomputer, 74Ls373 flip latch, 6116 store, eight bit ADC0809, and so on, and the satisfactory results obtained in study on hydraulic control system.
文摘In this paper, we conduct research on the unmanned aerial vehicle adaptive control system based on fuzzy control and chaosmechanics. Four rotor aircraft is a kind of nonlinear systems with underactuated, strong coupling characteristic. Although in existing research,through the design of the control algorithm effectively inhibits both for fl ight control effect, but not fundamentally eliminate the effect of aircraft.Dynamic model of unmanned helicopter fl ight control system design is very approximate, need to gradually improve the modeling accuracy, soas to get the exact autonomous fl ight control, so you need to practice constantly required to modeling in the fl ight information, so the unmannedhelicopter fl ight control system to have the ability to retrieve information modeling. This paper proposes the new idea on the issues that will bemeaningful.
基金supported by the National Natural Science Fundproject (50775207)Key Laboratory of E & M (Zhejiang University of Technology) Open Fund project (2009EP017)
文摘Based on the analysis of the mechanism of wire tension control by using torque motors in the multi-wire saw machining process, some mathematical models of a tension control system are studied, and an adaptive algo- rithm is designed for controlling the wire tension. In this algorithm of tension control, the rotation speeds and waving angle of motors are measured and fed back to the controller, and the NLMS（ normalized least mean squares） algorithm is used to calculate the adaptive correction value and control the wire tension accurately. The computer simulation results in Matlab software validate the high accuracy for controlling the system of the wire tension with the NLMS algorithm in the multi-wire saw machining process.
基金supported in part by the Thai Nguyen University of Technology,Vietnam.
文摘This article presents an adaptive optimal control method for a semi-active suspension system.The model of the suspension system is built,in which the components of uncertain parameters and exogenous disturbance are described.The adaptive optimal control law consists of the sum of the optimal control component and the adaptive control component.First,the optimal control law is designed for the model of the suspension system after ignoring the components of uncertain parameters and exogenous disturbance caused by the road surface.The optimal control law expresses the desired dynamic characteristics of the suspension system.Next,the adaptive component is designed with the purpose of compensating for the effects caused by uncertain parameters and exogenous disturbance caused by the road surface;the adaptive component has adaptive parameter rules to estimate uncertain parameters and exogenous disturbance.When exogenous disturbances are eliminated,the system responds with an optimal controller designed.By separating theoretically the dynamic of a semi-active suspension system,this solution allows the design of two separate controllers easily and has reduced the computational burden and the use of too many tools,thus allowing for more convenient hardware implementation.The simulation results also show the effectiveness of damping oscillations of the proposed solution in this article.
文摘The paper proposes a method for solving the problem of synthesis of an adaptive control system for unstable and deterministic chaotic processes in the class of‘dovetail’catastrophes for objects with m-inputs and n-outputs.The synthesis problem is solved by the gradient-velocity method of Lyapunov vector functions.From the conditions of the aperiodic robust stability of the etalon model with the desired dynamics of the main control loop and the generalised configurable object,the control goal is achieved.One of the most promising ways of solving the problem of managing unstable and deterministic chaotic processes is the synthesis of a control system in the class of‘swallowtail’catastrophes and the use of adaptation methods.Selecting and studying a reference model,and employing the gradient-velocity method for a generalised configurable control object ensure robust stability,utilise current information effectively,and achieve desired system quality and management goals.
基金supported by the“Shuimu Tsinghua Scholar”Project,China(No.2024SM223)the National Science and Technology Major Project,China(No.Y2022-V-0002-0028).
文摘Aeropropulsion System Test Facility (ASTF) is required to accurately control the pressure and temperature of the airflow to test the performance of the aero-engine. However, the control accuracy of ASTF is significantly affected by the flow disturbance caused by aero-engine acceleration and deceleration. This would reduce the credibility of ASTF’s test results for the aero-engine. Therefore, first, this paper proposes a feedforward compensation-based L1 adaptive control method for ASTF to address this problem. The baseline controller is first designed based on ideal uncoupled closed-loop dynamics to achieve dynamic decoupling. Then, L1 adaptive control is adopted to deal with various uncertainties and ensure good control performance. To further enhance the anti-disturbance performance, a feedforward strategy based on disturbance prediction is designed in the L1 adaptive control framework to compensate for the unmatched flow disturbance, which cannot be measured directly. In addition, this strategy takes into account the effects of actuator dynamics. With this method, the feedforward term can be determined from the nominal model parameters despite uncertainties. Finally, to demonstrate the effectiveness of the proposed method, various comparative experiments are performed on a hardware-in-the-loop system of ASTF. The experimental results show that the proposed method possesses excellent tracking performance, anti-disturbance performance and robustness.
基金supported by the Zhejiang Provincial Natural Science Foundation(LY24F030011,LY23F030005)the National Natural Science Foundation of China(62373131).
文摘In this paper,a pair of dynamic high-gain observer and output feedback controller is proposed for nonlinear systems with multiple unknown time delays.By constructing Lyapunov-Krasovskii functionals,it shows that global state asymptotic regulation can be ensured by introducing a single dynamic gain;furthermore,global asymptotic stabilization can be achieved by choosing a sufficiently large static scaling gain when the upper bounds of all system parameters are known.Especially,the output coefficient is allowed to be non-differentiable with unknown upper bound.This paper proposes a generalized Lyapunov matrix inequality based dynamic-gain scaling method,which significantly simplifies the design computational complexity by comparing with the classic backstepping method.
基金supported in part by the National Natural Science Foundation of China(62222301,62373012,62473012,62021003)the National Science and Technology Major Project(2021ZD0112302,2021ZD0112301)the Beijing Natural Science Foundation(JQ19013)
文摘In this paper, a fault-tolerant-based online critic learning algorithm is developed to solve the optimal tracking control issue for nonaffine nonlinear systems with actuator faults.First, a novel augmented plant is constructed by fusing the system state and the reference trajectory, which aims to transform the optimal fault-tolerant tracking control design with actuator faults into the optimal regulation problem of the conventional nonlinear error system. Subsequently, in order to ensure the normal execution of the online learning algorithm, a stability criterion condition is created to obtain an initial admissible tracking policy. Then, the constructed model neural network(NN) is pretrained to recognize the system dynamics and calculate trajectory control. The critic and action NNs are constructed to output the approximate cost function and approximate tracking control,respectively. The Hamilton-Jacobi-Bellman equation of the error system is solved online through the action-critic framework. In theoretical analysis, it is proved that all concerned signals are uniformly ultimately bounded according to the Lyapunov principle.The tracking control law can approach the optimal tracking control within a finite approximation error. Finally, two experimental examples are conducted to indicate the effectiveness and superiority of the developed fault-tolerant tracking control scheme.
基金Financial support was provided by the State Grid Sichuan Electric Power Company Science and Technology Project“Key Research on Development Path Planning and Key Operation Technologies of New Rural Electrification Construction”under Grant No.52199623000G.
文摘The increasing penetration of second-life battery energy storage systems(SLBESS)in power grids presents substantial challenges to system operation and control due to the heterogeneous characteristics and uncertain degradation patterns of repurposed batteries.This paper presents a novel model-free adaptive voltage controlembedded dung beetle-inspired heuristic optimization algorithmfor optimal SLBESS capacity configuration and power dispatch.To simultaneously address the computational complexity and ensure system stability,this paper develops a comprehensive bilevel optimization framework.At the upper level,a dung beetle optimization algorithmdetermines the optimal SLBESS capacity configuration byminimizing total lifecycle costswhile incorporating the charging/discharging power trajectories derived from the model-free adaptive voltage control strategy.At the lower level,a health-priority power dispatch optimization model intelligently allocates power demands among heterogeneous battery groups based on their real-time operational states,state-of-health variations,and degradation constraints.The proposed model-free approach circumvents the need for complex battery charging/discharging power controlmodels and extensive historical data requirements whilemaintaining system stability through adaptive controlmechanisms.A novel cycle life degradation model is developed to quantify the relationship between remaining useful life,depth of discharge,and operational patterns.The integrated framework enables simultaneous strategic planning and operational control,ensuring both economic efficiency and extended battery lifespan.The effectiveness of the proposed method is validated through comprehensive case studies on hybrid energy storage systems,demonstrating superior computational efficiency,robust performance across different network configurations,and significant improvements in battery utilization compared to conventional approaches.
基金supported in part by the National Natural Science Foundation of China(62403396,62433018,62373113)the Guangdong Basic and Applied Basic Research Foundation(2023A1515011527,2023B1515120010)the Postdoctoral Fellowship Program of CPSF(GZB20240621)
文摘In this paper, the containment control problem in nonlinear multi-agent systems(NMASs) under denial-of-service(DoS) attacks is addressed. Firstly, a prediction model is obtained using the broad learning technique to train historical data generated by the system offline without DoS attacks. Secondly, the dynamic linearization method is used to obtain the equivalent linearization model of NMASs. Then, a novel model-free adaptive predictive control(MFAPC) framework based on historical and online data generated by the system is proposed, which combines the trained prediction model with the model-free adaptive control method. The development of the MFAPC method motivates a much simpler robust predictive control solution that is convenient to use in the case of DoS attacks. Meanwhile, the MFAPC algorithm provides a unified predictive framework for solving consensus tracking and containment control problems. The boundedness of the containment error can be proven by using the contraction mapping principle and the mathematical induction method. Finally, the proposed MFAPC is assessed through comparative experiments.
基金supported in part by the Nation Natural Science Foundation of China under Grant No.52175099China Postdoctoral Science Foundation under Grant No.2020M671494Jiangsu Planned Projects for Postdoctoral Research Funds under Grant No.2020Z179。
文摘A tracking stability control problem for the vertical electric stabilization system of moving tank based on adaptive robust servo control is addressed.This paper mainly focuses on two types of possibly fast timevarying but bounded uncertainty within the vertical electric stabilization system:model parameter uncertainty and uncertain nonlinearity.First,the vertical electric stabilization system is constructed as an uncertain nonlinear dynamic system that can reflect the practical mechanics transfer process of the system.Second,the dynamical equation in the form of state space is established by designing the angular tracking error.Third,the comprehensive parameter of system uncertainty is designed to estimate the most conservative effects of uncertainty.Finally,an adaptive robust servo control which can effectively handle the combined effects of complex nonlinearity and uncertainty is proposed.The feasibility of the proposed control strategy under the practical physical condition is validated through the tests on the experimental platform.This paper pioneers the introduction of the internal nonlinearity and uncertainty of the vertical electric stabilization system into the settlement of the tracking stability control problem,and validates the advanced servo control strategy through experiment for the first time.
基金the National Natural Science Foundation of China under Grant U22A2043.
文摘This paper investigates the adaptive fuzzy finite-time output-feedback fault-tolerant control (FTC) problemfor a class of nonlinear underactuated wheeled mobile robots (UWMRs) system with intermittent actuatorfaults. The UWMR system includes unknown nonlinear dynamics and immeasurable states. Fuzzy logic systems(FLSs) are utilized to work out immeasurable functions. Furthermore, with the support of the backsteppingcontrol technique and adaptive fuzzy state observer, a fuzzy adaptive finite-time output-feedback FTC scheme isdeveloped under the intermittent actuator faults. It is testifying the scheme can ensure the controlled nonlinearUWMRs is stable and the estimation errors are convergent. Finally, the comparison results and simulationvalidate the effectiveness of the proposed fuzzy adaptive finite-time FTC approach.
基金the National Natural Science Foundation of China(No.52275062)and(No.52075262).
文摘Since backlash nonlinearity is inevitably existing in actuators for bidirectional stabilization system of allelectric tank,it behaves more drastically in high maneuvering environments.In this work,the accurate tracking control for bidirectional stabilization system of moving all-electric tank with actuator backlash and unmodeled disturbance is solved.By utilizing the smooth adaptive backlash inverse model,a nonlinear robust adaptive feedback control scheme is presented.The unknown parameters and unmodelled disturbance are addressed separately through the derived parametric adaptive function and the continuous nonlinear robust term.Because the unknown backlash parameters are updated via adaptive function and the backlash effect can be suppressed successfully by inverse operation,which ensures the system stability.Meanwhile,the system disturbance in the high maneuverable environment can be estimated with the constructed adaptive law online improving the engineering practicality.Finally,Lyapunov-based analysis proves that the developed controller can ensure the tracking error asymptotically converges to zero even with unmodeled disturbance and unknown actuator backlash.Contrast co-simulations and experiments illustrate the advantages of the proposed approach.
基金supported in part by the National Key R&D Program of China under Grant 2021YFB2011300the National Natural Science Foundation of China under Grant 52075262。
文摘This paper mainly focuses on the development of a learning-based controller for a class of uncertain mechanical systems modeled by the Euler-Lagrange formulation.The considered system can depict the behavior of a large class of engineering systems,such as vehicular systems,robot manipulators and satellites.All these systems are often characterized by highly nonlinear characteristics,heavy modeling uncertainties and unknown perturbations,therefore,accurate-model-based nonlinear control approaches become unavailable.Motivated by the challenge,a reinforcement learning(RL)adaptive control methodology based on the actor-critic framework is investigated to compensate the uncertain mechanical dynamics.The approximation inaccuracies caused by RL and the exogenous unknown disturbances are circumvented via a continuous robust integral of the sign of the error(RISE)control approach.Different from a classical RISE control law,a tanh(·)function is utilized instead of a sign(·)function to acquire a more smooth control signal.The developed controller requires very little prior knowledge of the dynamic model,is robust to unknown dynamics and exogenous disturbances,and can achieve asymptotic output tracking.Eventually,co-simulations through ADAMS and MATLAB/Simulink on a three degrees-of-freedom(3-DOF)manipulator and experiments on a real-time electromechanical servo system are performed to verify the performance of the proposed approach.
基金supported by the National Natural Science Foundation of China(Nos.51767017 and 51867015)the Basic Research and Innovation Group Project of Gansu(No.18JR3RA13)the Major Science and Technology Project of Gansu(No.19ZD2GA003).
文摘This paper deeply introduces a brand-new research method for the synchronous characteristics of DC microgrid bus voltage and an improved synchronous control strategy.This method mainly targets the problem of bus voltage oscillation caused by the bifurcation behavior of DC microgrid converters.Firstly,the article elaborately establishes a mathematical model of a single distributed power source with hierarchical control.On this basis,a smallworld network model that can better adapt to the topology structure of DC microgrids is further constructed.Then,a voltage synchronization analysis method based on the main stability function is proposed,and the synchronous characteristics of DC bus voltage are deeply studied by analyzing the size of the minimum non-zero eigenvalue.In view of the situation that the line coupling strength between distributed power sources is insufficient to achieve bus voltage synchronization,this paper innovatively proposes a new improved adaptive controller to effectively control voltage synchronization.And the convergence of the designed controller is strictly proved by using Lyapunov’s stability theorem.Finally,the effectiveness and feasibility of the designed controller in this paper are fully verified through detailed simulation experiments.After comparative analysis with the traditional adaptive controller,it is found that the newly designed controller can make the bus voltages of each distributed power source achieve synchronization more quickly,and is significantly superior to the traditional adaptive controller in terms of anti-interference performance.
基金supported in part by the National Key Research and Development Program of China(2023YFB4706400)the National Natural Science Foundation of China(62273112,62073030,62203161)+6 种基金the Guangdong Basic and Applied Basic Research Foundation(2023B1515120018,2023B1515120019)the Open Project of Xiangjiang Laboratory(23XJ03012)the Natural Science Foundation of Hunan Province(2024JJ5087)the Natural Science Foundation of Jiangxi Province(20232BAB212024)the National Research Foundation of Korea funded by the Ministry of Science and ICT,South Korea(IRIS-2023-00207954)the Science and Technology Planning Project of Guangzhou,China(2023A03J0120)the Guangzhou University Research Project(RC2023037)
文摘In this study,we consider a single-link flexible manipulator in the presence of an unknown Bouc-Wen type of hysteresis and intermittent actuator faults.First,an inverse hysteresis dynamics model is introduced,and then the control input is divided into an expected input and an error compensator.Second,a novel adaptive neural network-based control scheme is proposed to cancel the unknown input hysteresis.Subsequently,by modifying the adaptive laws and local control laws,a fault-tolerant control strategy is applied to address uncertain intermittent actuator faults in a flexible manipulator system.Through the direct Lyapunov theory,the proposed scheme allows the state errors to asymptotically converge to a specified interval.Finally,the effectiveness of the proposed scheme is verified through numerical simulations and experiments.
基金supported by National Natural Science Foundation of China(No.52302472)。
文摘The development of the adaptive cycle engine is a crucial direction of advanced fighter power sources in the near future.However,this new technology brings more uncertainty to the design of the control system.To address the versatile thrust demand under complex dynamic characteristics of the adaptive cycle engine,this paper proposes a direct thrust estimation and control method based on the Model-Free Adaptive Control(MFAC)algorithm.First,an improved Sliding Mode Control-MFAC(SMC-MFAC)algorithm has been developed by introducing a sliding mode variable structure into the standard Full Format Dynamic Linearization-MFAC(FFDL-MFAC)and designing self-adaptive weight coefficients.Then a trivariate double-loop direct thrust control structure with a controller-based thrust estimator and an outer command compensation loop has been established.Through thrust feedback and command correction,accurate control under multi-mode and operation conditions is achieved.The main contribution of this paper is the improved algorithm that combines the tracking capability of the MFAC and the robustness of the SMC,thus enhancing the dynamic performance.Considering the requirements of the online thrust feedback,the designed MFAC-based thrust estimator significantly speeds up the calculation.Additionally,the proposed command correction module can achieve the adaptive thrust control without affecting the operation of the inner loop.Simulations and Hardware-in-Loop(HIL)experiments have been performed on an adaptive cycle engine component-level model to investigate the estimation and control effect under different modes and health conditions.The results demonstrate that both the thrust estimation precision and operation speed are significantly improved compared with Extended Kalman Filter(EKF).Furthermore,the system can accelerate the response of the controlled plant,reduce the overshoot,and realize the thrust recovery within the safety range when the engine encounters the degradation.
基金funded by the National Key Research and Development Program of China,grant number:2023YFF0615404.
文摘To overcome the challenges associated with predicting gas extraction performance and mitigating the gradual decline in extraction volume,which adversely impacts gas utilization efficiency in mines,a gas extraction pure volume prediction model was developed using Support Vector Regression(SVR)and Random Forest(RF),with hyperparameters fine-tuned via the Genetic Algorithm(GA).Building upon this,an adaptive control model for gas extraction negative pressure was formulated to maximize the extracted gas volume within the pipeline network,followed by field validation experiments.Experimental results indicate that the GA-SVR model surpasses comparable models in terms of mean absolute error,root mean square error,and mean absolute percentage error.In the extraction process of bedding boreholes,the influence of negative pressure on gas extraction concentration diminishes over time,yet it remains a critical factor in determining the extracted pure volume.In contrast,throughout the entire extraction period of cross-layer boreholes,both extracted pure volume and concentration exhibit pronounced sensitivity to fluctuations in extraction negative pressure.Field experiments demonstrated that the adaptive controlmodel enhanced the average extracted gas volume by 5.08% in the experimental borehole group compared to the control group during the later extraction stage,with a more pronounced increase of 7.15% in the first 15 days.The research findings offer essential technical support for the efficient utilization and long-term sustainable development of mine gas resources.The research findings offer essential technical support for gas disaster mitigation and the sustained,efficient utilization of mine gas.
基金Supported by Key R&D Project of Zhejiang(Grant No.2022C02052)。
文摘Tracking control of tendon-driven manipulators has become a prevalent research area.However,the existence of flexible elastic tendons generates substantial residual vibrations,resulting in difficulties for trajectory tracking control of the manipulator.This paper proposes the radial basis function neural network adaptive hierarchical sliding mode control(RBFNNA-HSMC)method,which combines the dynamic model of the elastic tendon-driven manipulator(ETDM)with radial basis neural network adaptive control and hierarchical sliding mode control technology.The aim is to achieve trajectory tracking control of ETDM even under conditions of model inaccuracy and disturbance.The Lyapunov stability theory demonstrates the stability of the proposed RBFNNA-HSM controller.In order to assess the effectiveness and adaptability of the proposed control method,simulations and experiments were performed on a two-DOF ETDM.The RBFNNA-HSM method shows superior tracking accuracy compared to traditional modelbased HSM control.The experiment shows that the maximum tracking error for ETDM double-joint trajectory tracking is below 2.593×10-3rad and 1.624×10-3rad,respectively.
基金funded by the Science and Technology Project of State Grid Corporation,grant number 5500-202329500A-3-2-ZN,funding data 2023.10–2025.12.
文摘Aiming at the problems of large fluctuation of output active power and poor control performance in the process of frequency support of an energy-storage-type static-var-generator(ESVG),the adaptive adjustment control method for its active-loop parameters is used to realize thewind-farmfrequency support,which has become the current research hotspot.Taking the ESVG with a supercapacitor on the DC side as the research object,the influence trend of the change of virtual rotation inertia and virtual damping coefficient on its virtual angular velocity and power angle is analyzed.Then,the constraint relationship between the equivalent virtual inertia time constant of the supercapacitor and the virtual rotation inertia of the ESVG is clarified.Then,combined with the second-order response characteristics of the ESVG power control loop,the selection principles of the frequency modulation coefficient,the virtual rotation inertia,and the virtual damping coefficient are determined.An ESVG adjustment control method,considering the adaptive adjustment of the active loop parameters of the supercapacitor equivalent inertia,is proposed.While ensuring the frequency support capability of the ESVG,the fluctuation degree of its output active power and the virtual angular velocity are suppressed,and the proposed adjustment method also improves the stability of the ESVG control system and the frequency support capability for the wind farm.Finally,the simulation verifies the correctness of the theoretical analysis and the effectiveness of the proposed strategy.
