Picture of virus under microscope

Research under the microscope...

The Strathprints institutional repository is a digital archive of University of Strathclyde research outputs.

Strathprints serves world leading Open Access research by the University of Strathclyde, including research by the Strathclyde Institute of Pharmacy and Biomedical Sciences (SIPBS), where research centres such as the Industrial Biotechnology Innovation Centre (IBioIC), the Cancer Research UK Formulation Unit, SeaBioTech and the Centre for Biophotonics are based.

Explore SIPBS research

Minimum entropy control of non-Gaussian dynamic stochastic systems

Wang, H. and Yue, H. (2001) Minimum entropy control of non-Gaussian dynamic stochastic systems. In: 40th IEEE Conference on Decision and Control, 2001-12-04 - 2001-12-07.

Full text not available in this repository. (Request a copy from the Strathclyde author)

Abstract

This paper presents a new method to minimize the closed loop randomness for general dynamic stochastic systems using the entropy concept. The system is assumed to be subjected to any bounded random inputs. Using the recently developed linear B-spline model ([11, 10, 9, 8]) for the shape control of the system output probability density function, a control input is formulated which minimizes the output entropy of the closed loop system. Since the entropy is the measure of randomness for a given random variable, this controller can thus reduces the uncertainty of the closed loop system. A set of sufficient conditions have been established to guarantee the local minimum property of the obtained control input and the stability of the closed loop system. Discussions on the design of minimum entropy tracking error have also been made. An illustrative example is utilized to demonstrate the use of the control algorithm, and satisfactory results have been obtained.