Adaptive Dynamic Programming-based Adaptive Optimal Tracking Control of a Class of Strict-feedback Nonlinear System

This paper proposes a novel scheme to investigate the adaptive optimal tracking control problem of a class of strict-feedback nonlinear system via adaptive dynamic programming (ADP). First of all, by employing backstepping technique, a tracking error system is established. Then, the solution to adap...

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Bibliographic Details
Published in:International journal of control, automation, and systems Vol. 21; no. 4; pp. 1349 - 1360
Main Author: Zhao, Jin-Gang
Format: Journal Article
Language:English
Published: Bucheon / Seoul Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers 01.04.2023
Springer Nature B.V
제어·로봇·시스템학회
Subjects:
Adaptive control
Adaptive systems
Algorithms
Closed loops
Control
Control systems
Dynamic programming
Engineering
Feedback control
Mechatronics
Neural networks
Nonlinear systems
Optimal control
Reference signals
Regular Paper
Robotics
Tracking control
Tracking errors
제어계측공학
tracking control
nonlinear systems
strict-feedback
nonholonomic mobile robot
Adaptive dynamic programming
ISSN:1598-6446, 2005-4092
Online Access:Get full text
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Summary:This paper proposes a novel scheme to investigate the adaptive optimal tracking control problem of a class of strict-feedback nonlinear system via adaptive dynamic programming (ADP). First of all, by employing backstepping technique, a tracking error system is established. Then, the solution to adaptive optimal tracking control problem of strict-feedback nonlinear system is shown to be obtainable by solving the optimal regulation problem of established tracking error system. The solution of optimal regulation problem can be found by solving the corresponding Hamilton-Jacobi-Bellman (HJB) equation. In order to solve the HJB equation, a neural network (NN)-based online ADP algorithm is provided. To relax traditional Persistence of Excitation (PE) conditions, the historical and instantaneous state data are used to deign the NN weights tuning law simultaneously. In the provided ADP algorithm, the optimal control input is calculated in a forward-in-time manner without requiring any value or policy iterations. Based on the Lyapunov theory, we demonstrate that uniform ultimate boundedness (UUB) of all the signals in the closed-loop system are guaranteed. Application to the adaptive optimal tracking control of a nonholonomic mobile robot system demonstrates the efficacy of the provided ADP scheme. The designed ADP scheme achieves good tracking performance under different reference signals.
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http://link.springer.com/article/10.1007/s12555-022-0223-4
ISSN:1598-6446
2005-4092
DOI:10.1007/s12555-022-0223-4