EKF-based Enhanced Performance Controller Design for Non-linear Stochastic Systems

Date

2017-08-21

Advisors

Journal Title

Journal ISSN

ISSN

Volume Title

Publisher

IEEE

Type

Article

Peer reviewed

Yes

Abstract

In this paper, a novel control algorithm is presented to enhance the performance of the tracking property for a class of non-linear and dynamic stochastic systems subjected to non- Gaussian noises. Although the existing standard PI controller can be used to obtain the basic tracking of the systems, the desired tracking performance of the stochastic systems is difficult to achieve due to the random noises. To improve the tracking performance, an enhanced performance loop is constructed using the EKF-based state estimates without changing the existing closed loop with PI controller. Meanwhile, the gain of the enhanced performance loop can be obtained based upon the entropy optimization of the tracking error. In addition, the stability of the closed loop system is analysed in the mean square sense. The simulation results are given to illustrate the effectiveness of the proposed control algorithm.

Description

Keywords

Stochastic systems, Entropy, Algorithm design and analysis, Kalman filters, Control systems, Probability density function

Citation

Zhou, Y. et al (2017) EKF-based Enhanced Performance Controller Design for Non-linear Stochastic Systems. IEEE Transactions on Automatic Control, PP (99),

Rights

Research Institute