NDLI: Optimal guaranteed cost control of uncertain non-linear systems using adaptive dynamic programming with concurrent learning

Content Provider	IET Digital Library
Author	Huang, Yuzhu
Abstract	In this study, the authors study the optimal guaranteed cost control problem for a class of non-linear uncertain systems based on adaptive dynamic programming (ADP) with concurrent learning. A neural network-based approximate optimal guaranteed cost control design is developed not only to ensure the system stability for all admissible uncertainties but also to achieve a minimal guaranteed cost. First, the optimal guaranteed cost control problem is transformed into an optimal control problem of the nominal system by properly modifying the cost function to account for all possible uncertainties. Then based on ADP, an adaptive optimal learning algorithm is proposed for the nominal system by using a single critic network with concurrent learning to approximate the solution of Hamilton–Jacobi–Bellman equation. To relax the demands of the persistence of excitation condition, the recorded past data are used simultaneously with the current data for the adaptation of the critic network weights. Besides, an additional adjusting term is employed to stabilise the system and relax the requirement for an initial stabilising control. Moreover, uniform ultimate boundedness of the closed-loop system is guaranteed by using the Lyapunov approach. Finally, three simulation examples are provided to demonstrate the effectiveness of the proposed approach.
Starting Page	1025
Ending Page	1035
Page Count	11
ISSN	17518644
Volume Number	12
e-ISSN	17518652
Issue Number	Issue 8, May (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cta/12/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cta.2017.1131
Journal	IET Control Theory & Applications
Publisher Date	2018-02-07
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Adaptive Control Adaptive Dynamic Programming Adaptive Optimal Learning Algorithm Admissible Uncertainties ADP Closed Loop System Closed-loop System Concurrent Learning Control System Analysis Control System Synthesis Cost Optimal Control Dynamic Programming Excitation Condition Hamilton-Jacobi-Bellman Equation Initial Stabilising Control Learning System Lyapunov Approach Lyapunov Method Minimal Guaranteed Cost Neural Network-based Approximate Optimal Guaranteed Cost Control Design Neurocontrol Neurocontrollers Nominal System Nonlinear Control System Optimal Control Optimisation Technique Self Adjusting Control System Single Critic Network Stability in Control Theory Synthesis Method System Stability Uncertain Nonlinear System Uncertain System Uniform Ultimate Boundedness
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Human-Computer Interaction Electrical and Electronic Engineering Computer Science Applications

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