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Decentralized guaranteed cost control of interconnected systems with uncertainties: A learning-based optimal control strategy
Jan 03, 2017Author：
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Title: Decentralized guaranteed cost control of interconnected systems with uncertainties: A learning-based optimal control strategy
Authors: Wang, D; Liu, DR; Mu, CX; Ma, HW
Author Full Names: Wang, Ding; Liu, Derong; Mu, Chaoxu; Ma, Hongwen
Source: NEUROCOMPUTING, 214 297-306; 10.1016/j.neucom.2016.06.020 NOV 19 2016
Language: English
Abstract: A novel learning-based optimal control approach is constructed to attain the decentralized guaranteed cost controller design for a class of continuous-time complex nonlinear systems with dynamical uncertainties and interconnections. This is performed by combining robust decentralized control formulation with adaptive critic learning technique. By expressing the interconnected subsystems as a whole system and introducing a new cost function for the overall plant, the decentralized guaranteed cost control problem is formulated as an optimal control problem for the nominal overall system. Then, a policy iteration based learning control algorithm is employed to solve the modified Hamilton-Jacobi-Bellman equation with respect to the nominal plant iteratively. A critic neural network is constructed to approximate the optimal state feedback control law and then the uniform ultimate boundedness stability issue is analyzed. Meanwhile, a simulation experiment is conducted to verify the good performance of the control approach. (C) 2016 Elsevier B.V. All rights reserved.
ISSN: 0925-2312
eISSN: 1872-8286
IDS Number: EA6LS
Unique ID: WOS:000386741300028
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