Finite-Horizon Optimal State Feedback Control of Nonlinear Stochastic Systems Based on a Minimum Principle
| Autor: | Dietrich Brunn, Toshiyuki Ohtsuka, Uwe D. Hanebeck, Marc Peter Deisenroth, F. Weissel |
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| Rok vydání: | 2006 |
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| Zdroj: | MFI 2006 MFI 2006 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems |
| Popis: | In this paper, an approach to the finite-horizon optimal state-feedback control problem of nonlinear, stochastic, discrete-time systems is presented. Starting from the dynamic programming equation, the value function will be approximated by means of Taylor series expansion up to second-order derivatives. Moreover, the problem will be reformulated, such that a minimum principle can be applied to the stochastic problem. Employing this minimum principle, the optimal control problem can be rewritten as a two-point boundary-value problem to be solved at each time step of a shrinking horizon. To avoid numerical problems, the two-point boundary-value problem will be solved by means of a continuation method. Thus, the curse of dimensionality of dynamic programming is avoided, and good candidates for the optimal state-feedback controls are obtained. The proposed approach will be evaluated by means of a scalar example system. © 2006 IEEE. |
| Databáze: | OpenAIRE |
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