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.

Meeting Name

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

Document Type

Article - Conference proceedings

Document Version

Final Version

File Type





© 2000 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

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