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

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.

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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.

Item type: Article
ID code: 36509
Keywords: probability density function , lyapunov stability theory , B-splines neural networks, dynamic stochastic systems, Electrical engineering. Electronics Nuclear engineering, Modelling and Simulation, Applied Mathematics, Control and Systems Engineering, Computer Science Applications
Subjects: Technology > Electrical engineering. Electronics Nuclear engineering
Department: Faculty of Engineering > Electronic and Electrical Engineering
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Depositing user: Pure Administrator
Date Deposited: 20 Dec 2011 11:30
Last modified: 04 Sep 2014 21:51
URI: http://strathprints.strath.ac.uk/id/eprint/36509

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