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Event-Triggered Robust Optimal Control for Robotic Manipulators with Input Constraints via adaptive dynamic programming

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IFAC-PapersOnLine 2023年第2期56卷 841-846页

作者： Chen Chen Zhinan Peng Chaobin Zou Kecheng Shi Rui Huang Hong Cheng School of Automation Engineering University of Electronic Science and Technology of China Chengdu 611731 China Institute of Electronic and Information Engineering of University of Electronic Science and Technology of China Dongguan 523808 China

This paper proposes an event-triggered robust tracking control method for robotic manipulators with asymmetrical input constraints based on adaptive dynamic programming (ADP). First, the original robust tracking control problem is transformed into an optimal control problem for a nominal system with the help of a novel cost function design. Next, an event-triggered optimal control approach is proposed to solve this optimization problem and obtain the optimal solution to the Hamilton-Jacobi-Bellman (HJB) equation. The classical ADP framework is then used to approximate the optimal cost function and controller. Unlike existing weight adaptive laws, an additional term is introduced for removing the requirement of initial stabilization. Based on the Lyapunov theory, the stability of the original robotic system and the convergence of weight estimation are both guaranteed. Finally, simulation results are presented to demonstrate the effectiveness of the proposed event-triggered optimal control method.

关键词： Robust tracking control event-triggered mechanism robotic systems adaptive dynamic programming neural networks

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adaptive dynamic programming Approach for Micro-grid Optimal Energy Transmission Scheduling 39

Adaptive Dynamic Programming Approach for Micro-grid Optimal...

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39th Chinese Control Conference (CCC)

作者： Li, Jinglin Chen, Shuai Jiang, Chengpeng Liu, Fen Xiao, Wendong Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China Beijing Engn Res Ctr Ind Spectrum Imaging Beijing 100083 Peoples R China State Grid Blockchain Technol Beijing Co Ltd Beijing 100083 Peoples R China

ISBN: (纸本)9789881563903

Micro-grid energy scheduling optimization is a complex nonlinear optimization problem. During the studies, the micro-grid is the low-voltage system whose resistance of the transmission line plays an important role in the system. Difference in traditional micro-grid control scheme, a new control scheme is proposed which the power flow of each transmission line is taken as decision variables, that is to say, the power flow of each line is controlled in order to get the optimal operating cost of micro-grid. Based on the above, in this paper we focus on the micro-grid optimal energy transmission scheduling. It is formulated as a nonlinear quadratic programming problem with quadratic constraints, due to infinite micro-grid operating cycle, it is also an infinite steps optimization problem. Traditional optimal scheduling algorithm is difficult to deal with. Therefore, we propose an adaptive dynamic programing (ADP) algorithm which is effective to solve the infinite steps optimization problem. ADP could avoid meeting the curse of dimensionality caused by the micro-grid optimization, and also has the neural networks which are updated by themselves during applications. By theoretical proof, we obtain an optimal control accuracy and operation efficiency. Finally, numerical simulation results show that the adaptive dynamic programming algorithm has less operating cost and better control scheme compared with the simulated annealing algorithm.

关键词： micro-grid optimal energy transmission scheduling adaptive dynamic programming

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adaptive dynamic programming Method for Optimal Battery Management of Battery Electric Vehicle 9

Adaptive Dynamic Programming Method for Optimal Battery Mana...

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9th IEEE Data Driven Control and Learning Systems Conference (DDCLS)

作者： Xue, Jiguang Yan, Chunsheng Wang, Dan Wang, Jun Wu, Jun Liao, Zehua State Grid Liaoning Elect Power Co Ltd Elect Power Res Inst Shenyang 110006 Peoples R China LiaoNing Elect Power Dev Stock Co LTD Shenyang 110006 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

ISBN: (纸本)9781728159225

One of the main influencing factors of battery electric vehicle (BEV) application is the high-cost of the battery. We consider to apply the battery of BEV to smart residential environments when the BEV is idle, so that we can lower the utility cost. Therefore, an adaptive dynamic programming (ADP) method is designed to solve the optimal battery management, which avoids the dimension disaster of the complex nonlinear BEV system. First, the operation modes of the battery are analyzed, and the problem statement is carried out. Then, the corresponding self-learning optimization algorithm is developed based on ADP. Finally, numerical results by experiment simulations are used to verify the ADP algorithm.

关键词： Battery electric vehicle optimal control adaptive dynamic programming battery management

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Optimal tracking control of hydraulic support initial support force based on adaptive dynamic programming

Optimal tracking control of hydraulic support initial suppor...

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第43届中国控制会议

作者： Qingliang Zeng Bingyi Jia Jun Zhao Lirong Wan College of Mechanical and Electronic Engineering Shandong University of Science and Technology College of Transportation Shandong University of Science and Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Due to the complex coal mining environment and dynamic pressure characteristics in hydraulic supply systems, setting and controlling the initial support force of hydraulic supports leads to the significant challenges. This paper proposes an optimal tracking control method for the initial support force of hydraulic supports base on adaptive dynamic programming(ADP). First,a mathematical model for the fluid supply system is developed, and an augmented system is constructed to transform the tracking problem into a regulation control problem. Accordingly, the optimal control cost function is estimated by applying a neural network(NN), where a discount factor is introduced to ensure boundedness. Finally, an online adaptive learning method based on adaptive parameter estimation technique is designed to online update the unknown NN weights, thus the Hamilton-JacobiBellman(HJB) equation can be online resolved. Simulation results demonstrate high control accuracy, with the tracking error converging to zero, enabling adaptive adjustment of the initial support force in complex coal mine working environments.

关键词： Initial support force Fluid supply system adaptive dynamic programming Optimal tracking control

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Robust Sliding Mode adaptive dynamic programming Control for Partially Unknown Second-order Nonlinear Systems

Robust Sliding Mode Adaptive Dynamic Programming Control for...

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第43届中国控制会议

作者： Tao Huang Hongqian Lu Yefeng Yang Xianlin Huang Center for Control Theory and Guidance Technology Harbin Institute of Technology Department of Aeronautical and Aviation Engineering the Hong Kong Polytechnic University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

This paper introduces a novel robust cost function for the ADP algorithm to suppress the impact of the disturbance for partially unknown second-order nonlinear systems. The sliding mode control is employed to design the cost function, which thereby enhances the performance of the closed-loop system. Furthermore, an offline disturbance compensator is proposed to further improve the robustness of the system. Subsequently, the trajectory of the entire closed-loop system is proved to be uniformly ultimate bounded(UUB) in a Lyapunov sense. Sufficient simulations are conducted to verify the effectiveness and superiority of the proposed method.

关键词： Sliding mode control adaptive dynamic programming Robust cost function Disturbance compensator

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An Event-Triggered adaptive dynamic programming Method for Large-Scale HVAC Systems*

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IFAC-PapersOnLine 2023年第2期56卷 5281-5286页

作者： Shan Xue Zhiwen Chen Derong Liu Chao Shangt Hongtian Chen School of Computer Science and Engineering South China University of Technology Guangzhou 510006 China School of Automation Central South University Changsha 410083 China Peng Cheng Laboratory Shenzhen 518000 China School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen 518005 China Department of Automation BNRist Tsinghua University Beijing 100084 China Department of Automation Shanghai Jiao Tong University Shanghai 200240 China

In this paper, an event-triggered adaptive dynamic programming (ADP) algorithm is developed for the temperature control of large-scale heating, ventilation, and air conditioning (HVAC) systems. First, the dynamic model of the system is established by using the conservation of mass and energy, which involves the dynamics of the fan and the cooling coil. Second, the multi-zone temperature control problem is treated as a non-zero-sum game, which requires solving the coupled Hamilton-Jacobian (HJ) equations. Then, the ADP algorithm is employed to solve the HJ equation. Importantly, in order to reduce the network transmission burden of large-scale HVAC systems, the ADP algorithm developed in this paper is based on event-triggering mechanism. Theoretical analysis proves that the tracking error and the neural network weight estimation error are uniformly ultimately bounded. Simulation results verify the effectiveness of the algorithm.

关键词： adaptive dynamic programming optimal control event-triggering mechanism neural networks heating, ventilation, and air conditioning

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Robust Cooperative Control for Nonlinear Multi-agent Systems with Input-Disturbances via adaptive dynamic programming 33

Robust Cooperative Control for Nonlinear Multi-agent Systems...

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33rd Chinese Control and Decision Conference (CCDC)

作者： Qu, Qiuxia Wang, Juan QiongXia Sun, Liangliang Cui, Yang Shenyang Jianzhu Univ Sch Informat & Control Engn Shenyang 110168 Peoples R China Univ Sci & Technol Liaoning Sch Elect & Informat Engn Anshan 114051 Peoples R China

ISBN: (纸本)9781665440899

Considering the leader-following consensus problem for the nonlinear multi-agent systems with bounded input-disturbances under fixed topology, a novel distributed robust protocol is designed to guarantee all followers synchronize to the leader by investigating the gain of the Nash Equilibrium. The robustness restrictions are given through Lyapunov theory. To get the Nash solution, critic neural networks are trained based on adaptive dynamic programming algorithm in an online and forward-in-time manner to solve the coupled Hamilton-Jacobi equations. An additional term is added to the neural network weight tuning law to avoid the requirement for the initial admissible control law.

关键词： adaptive dynamic programming Input-disturbance Leader-following consensus problem Multi-agent systems Nash equilibrium Neural network

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Bias-policy iteration based adaptive dynamic programming for unknown continuous-time linear systems

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AUTOMATICA 2022年 136卷 110058-110058页

作者： Jiang, Huaiyuan Zhou, Bin Harbin Inst Technol Ctr Control Theory & Guidance Technol POB 416 Harbin 150001 Peoples R China

In this paper, a bias-policy iteration method for solving the data-driven optimal control problem of unknown continuous-time linear systems is proposed. Firstly, a model-based bias-policy iteration method is given and its convergence is rigorously proved. Then the data-driven implementation for the proposed method is then introduced without using the information of the system matrices. The relationship between the proposed method and the existing policy iteration method and value iteration method is also analyzed. Compared with the existing policy iteration method, the most significant advantage of the proposed method is that, by adding a bias parameter, the condition of the initial admissible controllers can be further relaxed. Simulation examples verify the effectiveness of the proposed bias-policy iteration method. (C) 2021 Elsevier Ltd. All rights reserved.

关键词： adaptive dynamic programming Policy iteration Unknown systems Optimal control Data-driven control

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Fault detection and isolation of actuator failures in jet engines using adaptive dynamic programming

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APPLIED MATHEMATICS AND COMPUTATION 2022年 414卷 126664-126664页

作者： Kang, Haobo Ma, Hongjun Chinese Acad Sci Shenyang Inst Automat Shenyang 110004 Liaoning Peoples R China Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Liaoning Peoples R China

This paper presents a adaptive dynamic programming-based fault detection and isolation (FDI) scheme to detect and isolate faults in an aircraft jet engine. To this end, the weights in Actor-Critic neural networks are first tuned to learn the input-output map of the jet engine considering its multiple working modes. The convergences of the trainings in Critic-Actor neural networks are strictly proved without knowing the drift dynamics and the input dynamics in the presence of unknown nonlinearities and approximation errors. Using the residuals that are generated by measuring the difference of each network output and the measured engine output, various criteria are established for accomplishing the fault diagnosis task, that addresses the problem of fault detection and isolation of the system components. A number of simulation studies are carried out for combustion chamber of a single-spool jet engine to demonstrate and illustrate the advantages, capabilities, and performance of our proposed fault diagnosis scheme. (c) 2021 Elsevier Inc. All rights reserved.

关键词： Fault detection and isolation Data-based adaptive dynamic programming Jet engine

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Morphing UAV Formation Control Based on adaptive dynamic programming

Morphing UAV Formation Control Based on Adaptive Dynamic Pro...

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第43届中国控制会议

作者： Ruifeng Li Liqian Dou Hui Yu Zheyu Zhang Hao Cheng School of Electrical Engineering and Automation Tianjin University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In this study,an adaptive dynamic programming-based collaborative tracking control algorithm is developed for the formation of morphing unmanned aerial vehicles(UAVs).The multi-morphing UAVs system is divided into the position and attitude *** the position subsystem,a novel cost function fused with the impact of UAV morphing is introduced and the position controllers for morphing UAVs are developed using adaptive dynamic programming(ADP).To quantify the impact of morphing,a high-order finite-time observer is introduced which estimates the acceleration from aerodynamic force acting on the *** the attitude subsystem,an integral back-stepping controller is *** stability of morphing UAV formation is theoretically proven with the Lyapunov *** involving comparisons with PID algorithm and sliding mode control(SMC) method have been conducted to validate its effectiveness and robustness.

关键词： Morphing Unmanned Aerial Vehicle Formation Control adaptive dynamic programming Optimal Control

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