Robust Optimal Parallel Tracking Control Based on Adaptive Dynamic Programming

This article focuses on a novel robust optimal parallel tracking control method for continuous-time (CT) nonlinear systems subject to uncertainties. First, the designed virtual controller facilitates the transformation of the original nonlinear system into an affine system with an augmented state ve...

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Vydané v:IEEE transactions on cybernetics Ročník 54; číslo 7; s. 4308 - 4321
Hlavní autori: Wei, Qinglai, Jiao, Shanshan, Wang, Fei-Yue, Dong, Qi
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States IEEE 01.07.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Adaptive control
Adaptive dynamic programming (ADP)
Control methods
Control systems
Control theory
Dynamic programming
neural network (NN)
Neural networks
Nonlinear control
nonlinear robust optimal control
Nonlinear systems
Optimal control
parallel control
Performance analysis
Robust control
State vectors
Tracking control
Uncertain systems
Uncertainty
Virtual networks
ISSN:2168-2267, 2168-2275, 2168-2275
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Shrnutí:This article focuses on a novel robust optimal parallel tracking control method for continuous-time (CT) nonlinear systems subject to uncertainties. First, the designed virtual controller facilitates the transformation of the original nonlinear system into an affine system with an augmented state vector, which promotes the introduction of the optimal parallel tracking control problem. Then, this article generates fresh insight into counteracting the effects of uncertainty by developing a novel parallel control system that invokes the formulated virtual control law and an auxiliary variable obtained from the relationship between the solutions of the optimal control problems for the uncertain system and the nominal one. Next, critic neural networks (NNs) approximate the Hamilton-Jacobi-Bellman (HJB) equations' solution to implement the proposed robust optimal control method via adaptive dynamic programming (ADP). Finally, simulation experiments demonstrate the proposed method's remarkable effectiveness.
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ISSN:2168-2267
2168-2275
2168-2275
DOI:10.1109/TCYB.2023.3312543