The conventional dynamic programming methodology for the solution of optimal control, despite having many desirable features, is severely restricted by its computational requirements. However, in recent times, an alternate formulation, known as the adaptive-critic synthesis, has given it a new perspective. In this paper, we have attempted to use the philosophy of adaptive-critic design to the optimal control of distributed parameter systems. An important contribution of this study is the derivation of the necessary conditions of optimality for distributed parameter systems, described in discrete domain, following the principle of approximate dynamic programming. Then the derived necessary conditions of optimality are used to synthesize infinite time optimal neuro-controllers in the framework of adaptive-critic design. A motivating example that follows clearly shows the potential of the adaptive critic procedure.
S. N. Balakrishnan and R. Padhi, "Infinite Time Optimal Neuro Control for Distributed Parameter Systems," Proceedings of the 2000 American Control Conference, 2000, Institute of Electrical and Electronics Engineers (IEEE), Jan 2000.
The definitive version is available at https://doi.org/10.1109/ACC.2000.876927
2000 American Control Conference, 2000
Mechanical and Aerospace Engineering
Keywords and Phrases
Adaptive-Critic Design; Adaptive-Critic Synthesis; Approximate Dynamic Programming; Approximation Theory; Computational Complexity; Control System Synthesis; Discrete Domain; Discrete Systems; Distributed Parameter Systems; Dynamic Programming; Dynamic Programming Methodology; Infinite Time Optimal Neuro Control; Infinite Time Optimal Neuro-Controller Synthesis; Neurocontrollers; Optimal Control
Article - Conference proceedings
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