Functional Nonlinear Model Predictive Control Based on Adaptive Dynamic Programming

This paper presents a functional model predictive control (MPC) approach based on an adaptive dynamic programming (ADP) algorithm with the abilities of handling control constraints and disturbances for the optimal control of nonlinear discrete-time systems. In the proposed ADP-based nonlinear MPC (N...

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Veröffentlicht in:	IEEE transactions on cybernetics Jg. 49; H. 12; S. 4206 - 4218
Hauptverfasser:	Dong, Lu, Yan, Jun, Yuan, Xin, He, Haibo, Sun, Changyin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.12.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Adaptive algorithms Adaptive control Adaptive dynamic programming (ADP) Algorithms Artificial neural networks Computer simulation Discrete time systems Dynamic programming Economic models Feedback control Heuristic algorithms Horizon Mathematical model Neural networks neural networks (NNs) Nonlinear control nonlinear model predictive control (NMPC) Nonlinear systems Optimal control Predictive control System dynamics Terminal constraints
ISSN:	2168-2267, 2168-2275, 2168-2275
Online-Zugang:	Volltext
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