This note investigates the optimal linear quadratic control problem in the discrete-time framework, for stochastic systems affected by disturbances generated by a nonlinear stochastic exosystem. The application of the maximum principle to nonlinear optimal control problems does not admit, in general, implementable solutions. Therefore, it is worthwhile to look for finite-dimensional approximation schemes. The approach followed in this note is based on the nu-degree Carleman approximation of a stochastic nonlinear system applied to the exosystem and provides a real-time algorithm to design an implementable control law. Simulations support theoretical results and show the improvements when the approximation index nu is increased.

The Carleman approximation approach to solve a stochastic nonlinear control problem

Mavelli G;Palumbo P
2010

Abstract

This note investigates the optimal linear quadratic control problem in the discrete-time framework, for stochastic systems affected by disturbances generated by a nonlinear stochastic exosystem. The application of the maximum principle to nonlinear optimal control problems does not admit, in general, implementable solutions. Therefore, it is worthwhile to look for finite-dimensional approximation schemes. The approach followed in this note is based on the nu-degree Carleman approximation of a stochastic nonlinear system applied to the exosystem and provides a real-time algorithm to design an implementable control law. Simulations support theoretical results and show the improvements when the approximation index nu is increased.
2010
Istituto di Analisi dei Sistemi ed Informatica ''Antonio Ruberti'' - IASI
Kalman filtering
stochastic optimal control
stochastic systems
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/170267
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