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Feedback control of minimum‐time optimal control problems using neural networks
Author(s) -
Goh C. J.,
Edwards N. J.,
Zomaya A. Y.
Publication year - 1993
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/oca.4660140102
Subject(s) - control theory (sociology) , robustness (evolution) , feed forward , artificial neural network , optimal control , computer science , open loop controller , controller (irrigation) , feedforward neural network , actuator , control engineering , control (management) , engineering , mathematics , closed loop , artificial intelligence , mathematical optimization , agronomy , biochemistry , chemistry , biology , gene
This paper presents an optimal feedback controller capable of driving a non‐linear control system from an arbitrary initial state to a fixed final state in minimum time. The controller is based on a feedforward multilayer neural network trained repeatedly using open‐loop optimal control data which densely span the field of extremals of the non‐linear system. The effectiveness of the controller is clearly demonstrated by a simulation on a two‐link robot manipulator. The effect of sensor/actuator noise and parameter variation is also included to confirm the robustness of the controller.