Linearized controller design for the output probability density functions of non-Gaussian stochastic systems

Tools

Kabore, P. and Baki, H. and Yue, H. and Wang, H. (2005) Linearized controller design for the output probability density functions of non-Gaussian stochastic systems. International Journal of Automation and Computing, 2 (1). pp. 67-74. (http://scholar.ilib.cn/A-gjzdhyjszz-e200501011.htm...)

Full text not available in this repository.Request a copy

Abstract

This paper presents a linearized approach for the controller design of the shape of output probability density functions for general stochastic systems. A square root approximation to an output probability density function is realized by a set of B-spline functions. This generally produces a nonlinear state space model for the weights of the B-spline approximation. A linearized model is therefore obtained and embedded into a performance function that measures the tracking error of the output probability density function with respect to a given distribution. By using this performance function as a Lyapunov function for the closed loop system, a feedback control input has been obtained which guarantees closed loop stability and realizes perfect tracking. The algorithm described in this paper has been tested on a simulated example and desired results have been achieved.

ORCID iDs

Kabore, P., Baki, H., Yue, H. ORCID logoORCID: https://orcid.org/0000-0003-2072-6223 and Wang, H.;
CORE (COnnecting REpositories)