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Neural dynamic optimization for control systems.II. Theory

Chang-Yun Seong, Bernard Widrow

Year
2001
Citations
36

Abstract

The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical methods such as DP. This paper mainly describes the theory of NDO, while the two other companion papers of this topic explain the background for the development of NDO and demonstrate the method with several applications including control of autonomous vehicles and of a robot arm, respectively.

Keywords

Computer scienceComputationOptimal controlDynamic programmingArtificial neural networkNonlinear systemFeature (linguistics)Control (management)RobotMIMO

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