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IEEE/CAA Journal of Automatica Sinica 2021年第6期8卷 1119-1132页

作者： Jiaxin Zhang Kewen Li Yongming Li College of Science Liaoning University of TechnologyJinzhou 121001China Institute of Automation Qufu Normal UniversityQufu 273165China

In this paper,an adaptive neural-network(NN)output feedback optimal control problem is studied for a class of strict-feedback nonlinear systems with unknown internal dynamics,input saturation and state *** networks are used to approximate unknown internal dynamics and an adaptive NN state observer is developed to estimate immeasurable *** the framework of the backstepping design,by employing the actor-critic architecture and constructing the tan-type Barrier Lyapunov function(BLF),the virtual and actual optimal controllers are *** order to accomplish optimal control effectively,a simplified reinforcement learning(RL)algorithm is designed by deriving the updating laws from the negative gradient of a simple positive function,instead of employing existing optimal control *** addition,to ensure that all the signals in the closed-loop system are bounded and the output can follow the reference signal within a bounded error,all state variables are confined within their compact sets all ***,a simulation example is given to illustrate the effectiveness of the proposed control strategy.

关键词： Backstepping design immeasurable states neuralnetworks(NNs) optimal control state constraints

Safe Q-Learning for Data-Driven Nonlinear Optimal Control With Asymmetric state constraints

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IEEE/CAA Journal of Automatica Sinica 2024年第12期11卷 2408-2422页

作者： Mingming Zhao Ding Wang Shijie Song Junfei Qiao the School of Information Science and Technology the Beijing Key Laboratory of Computational Intelligence and Intelligent Systemthe Beijing Laboratory of Smart Environmental Protectionand the Beijing Institute of Artificial IntelligenceBeijing University of Technology.Beijing 100124China IEEE the School of Mechanical and Electrical Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

This article develops a novel data-driven safe Q-learning method to design the safe optimal controller which can guarantee constrained states of nonlinear systems always stay in the safe region while providing an optimal ***,we design an augmented utility function consisting of an adjustable positive definite control obstacle function and a quadratic form of the next state to ensure the safety and ***,by exploiting a pre-designed admissible policy for initialization,an off-policy stabilizing value iteration Q-learning(SVIQL)algorithm is presented to seek the safe optimal policy by using offline data within the safe region rather than the mathematical ***,the monotonicity,safety,and optimality of the SVIQL algorithm are theoretically *** obtain the initial admissible policy for SVIQL,an offline VIQL algorithm with zero initialization is constructed and a new admissibility criterion is established for immature iterative ***,the critic and action networks with precise approximation ability are established to promote the operation of VIQL and SVIQL ***,three simulation experiments are conducted to demonstrate the virtue and superiority of the developed safe Q-learning method.

关键词： Adaptive critic control adaptive dynamic programming(ADP) control barrier functions(CBF) stabilizing value iteration Q-learning(SVIQL) state constraints

VARIATIONAL DISCRETIZATION OF PARABOLIC CONTROL PROBLEMS IN THE PRESENCE OF POINTWISE state constraints

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Journal of Computational Mathematics 2011年第1期29卷 1-15页

作者： Klaus Deckelnick Michael Hinze Institut fiir Analysis und Numerik Otto-von Guericke-Universitiit Magdeburg Universitiitsplatz 2 39106 Magdeburg Germany Schwerpunkt Optimierung und Approximation Universitiit Hamburg Bundesstraape 55 20146 Hamburg Germany

space dimensions. These bounds follow from uniform estimates for the discretization error of the state under natural regularity requirements.

关键词： Parabolic optimal control problem state constraints Error estimates.

Adaptive fuzzy asymptotic control design for MIMO nonlinear systems with state constraints

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Journal of Control and Decision 2023年第4期10卷 610-623页

作者： Yongchao Liu Bowen Zeng Qidan Zhu Lipeng Wang Institute of Complexity Science School of AutomationQingdao UniversityQingdaoPeople’s Republic of China Shandong Key Laboratory of Industrial Control Technology QingdaoPeople’s Republic of China College of Intelligent Systems Science and Engineering Harbin Engineering UniversityHarbinPeople’s Republic of China

This paper addresses the asymptotic control problem of uncertain multi-input and multi-output(MIMO)nonlinear *** considered MIMO systems contain unknown virtual control coefficients(UVCCs)and state *** Lyapunov function by associating with the lower bounds of UVCCs is presented to counteract the adverse effect deriving from *** state constraints are ensured by utilising the barrier Lyapunov ***,the asymptotic tracking controller is recursively constructed by combining the backstepping technique with fuzzy logic *** remarkable character of the designed controller is that the asymptotic tracking performance can be achieved by introducing some smooth functions into adaptive backstepping *** contrast to the existing results,the conditions on the UVCCs are ***,the new control design is illustrated by a practical example.

关键词： Asymptotic tracking control state constraints bound estimation method nonlinear systems

Event-triggered adaptive finite-time control for nonlinear systems under asymmetric time-varying state constraints

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Frontiers of Information Technology & Electronic Engineering 2021年第12期22卷 1610-1624页

作者： Yan WEI Jun LUO Huaicheng YAN Yueying WANG School of Aeronautics and Astronautics Shanghai Jiao Tong UniversityShanghai 200240China School of Mechatronic Engineering and Automation Shanghai UniversityShanghai 200444China School of Information Science and Engineering East China University of Science and TechnologyShanghai 200237China

This paper investigates the issue of event-triggered adaptive finite-time state-constrained control for multi-input multi-output uncertain nonlinear *** prevent asymmetric time-varying state constraints from being violated,a tan-type nonlinear mapping is established to transform the considered system into an equivalent“non-constrained”*** employing a smooth switch function in the virtual control signals,the singularity in the traditional finite-time dynamic surface control can be *** logic systems are used to compensate for the unknown functions.A suitable event-triggering rule is introduced to determine when to transmit the control *** Lyapunov analysis,the closed-loop system is proved to be semi-globally practical finite-time stable,and the state constraints are never *** are provided to evaluate the effectiveness of the proposed approach.

关键词： Event-triggered control Nonlinear mapping Adaptive fuzzy control Finite-time state constraints

Asymmetric time-varying integral barrier Lyapunov function based adaptive optimal control for nonlinear systems with dynamic state constraints

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Frontiers of Information Technology & Electronic Engineering 2024年第6期25卷 887-902页

作者： Yan WEI Mingshuang HAO Xinyi YU Linlin OU College of Information Engineering Zhejiang University of TechnologyHangzhou 310023China

This paper investigates the issue of adaptive optimal tracking control for nonlinear systems with dynamic state *** asymmetric time-varying integral barrier Lyapunov function(ATIBLF)based integral reinforcement learning(IRL)control algorithm with an actor–critic structure is first *** ATIBLF items are appropriately arranged in every step of the optimized backstepping control design to ensure that the dynamic full-state constraints are never ***,optimal virtual/actual control in every backstepping subsystem is decomposed with ATIBLF items and also with an adaptive optimized ***,neural networks are used to approximate the gradient value *** to the Lyapunov stability theorem,the boundedness of all signals of the closed-loop system is proved,and the proposed control scheme ensures that the system states are within predefined compact ***,the effectiveness of the proposed control approach is validated by simulations.

关键词： state constraints Asymmetric time-varying integral barrier Lyapunov function(ATIBLF) Adaptive optimal control Nonlinear systems

Adaptive Neural Network Control for Nonholonomic Systems with Time-varying state constraints and Inverse Dynamics

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Adaptive Neural Network Control for Nonholonomic Systems wit...

Zonotopic Kalman filtering based fault diagnosis algorithm for linear system with state constraints

第43届中国控制会议

作者： Qing Dai Yuqiang Wu School of Engineering Qufu Normal University

This article investigates a method of adaptive neural networks stabilization for a class of nonholonomic systems with time-varying state constraints and integral input-to-state stable inverse dynamics. By using the integral input-to-state stable Lyapunov function and combining it with the small gain theorem to handle inverse dynamics of nonholonomic systems. The tan-type barrier Lyapunov function is constructed to handle state constraints of x0-subsystem. A coordinate transformation is designed and a novel nonlinear state-dependent function is constructed to transform the original constrained subsystem into an unconstrained system to handle state constraints of x-subsystem. Then,we put forward the adaptive neural networks to compensate for the uncertainties of nonholonomic systems. The designed adaptive neural networks control strategy guarantees all signals in the closed-loop system bounded without violating time-varying state constraints. Finally,simulation results verify the effectiveness of the method.

关键词： Nonholonomic systems state constraints Input-to-state stable Barrier Lyapunov function

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Zonotopic Kalman filtering based fault diagnosis algorithm f...

Extended-state-Observer-Based Tracking Control for Motor-drive Systems with state constraints and Unknown Disturbances

第40届中国控制会议

作者： Yacong Zhan Ziyun Wang Yan Wang Zhicheng Ji Engineering Research Center of Internet of Things Technology and Applications （Ministry of Education） Jiangnan University

A novel fault diagnosis method based on zonotopic Kalman filter for linear system with state constraints is *** augmented system is constructed by extending the state constraints to the system output vector and the fault to the state vector,***,a zonotopic Kalman filter is designed to obtain the interval *** a fault occurs,the fault estimate can be directly found,vice *** effectiveness and accuracy of this algorithm are demonstrated through the sensor fault diagnosis case of the electrothermal coupled model of Li-ion battery.

关键词： state constraints Zonotopic Kalman filter Fault diagnose Electrothermal model Linear system

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Extended-State-Observer-Based Tracking Control for Motor-dri...

FINITE ELEMENT ANALYSIS OF OPTIMAL CONTROL PROBLEM GOVERNED BY STOKES EQUATIONS WITH L^2-NORM state-constraints

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作者： Yun Cheng Xuemei Ren Lufeng Zhang Pengbiao Wang School of Automation Beijing Institute of Technology

In order to address the state constraints of the motor-drive systems（MDS） with the unknown disturbances, a funnel control strategy based on extended state observer（ESO） is proposed. The unknown disturbances（modeling error, nonlinear frictions and unknown disturbance torque） and unknown speed in the MDS were estimated by a time varying gain ESO, which has better transient behavior of the estimations. The original system was transformed into a constrain-free system by two funnel variables, and then the evolution of the position tracking error in a funnel region and speed in a constant boundary were achieve by a dynamic surface control. Furthermore, the feasibility conditions of virtual control laws in barrier Lyapunov function（BLF）were removed. The convergence of the closed-loop control system was illustrated by the Lyapunov theory. Simulation results verify the effectiveness of the proposed funnel control method.

关键词： Motor-drive systems state constraints funnel control extended state observer tracking control

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Journal of Computational Mathematics 2011年第5期29卷 589-604页

作者： Haifeng Niu Danping Yang School of Mathematics and Information Science Henan Polytechnic University Jiaozuo 454000 China School of Mathematics Shandong University Jinan 250100 China Department of Mathematics East China Normal University Shanghai 200241 China

An optimal control problem governed by the Stokes equations with L^2-norra state constraints is studied. Finite element approximation is constructed. The optimality conditions of both the exact and discretized problems are discussed, and the a priori error estimates of the optimal order accuracy in L^2-norm and H^1-norm are given. Some numerical experiments are presented to verify the theoretical results.

关键词： Optimal control state constraints Stokes equations a priori error analysis.