Brief paper: A neural network solution for fixed-final time optimal control of nonlinear systems

Authors:
Tao Cheng;Frank L. Lewis;Murad Abu-Khalaf
Affiliations:
Automation and Robotics Research Institute, The University of Texas at Arlington, TX 76118, USA;Automation and Robotics Research Institute, The University of Texas at Arlington, TX 76118, USA;Automation and Robotics Research Institute, The University of Texas at Arlington, TX 76118, USA
Venue:
Automatica (Journal of IFAC)
Year:
2007

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Abstract

In this paper, fixed-final time optimal control laws using neural networks and HJB equations for general affine in the input nonlinear systems are proposed. The method utilizes Kronecker matrix methods along with neural network approximation over a compact set to solve a time-varying HJB equation. The result is a neural network feedback controller that has time-varying coefficients found by a priori offline tuning. Convergence results are shown. The results of this paper are demonstrated on an example.