Probabilistic Decoupling Control for Stochastic Non-Linear Systems Using EKF-Based Dynamic Set-Point Adjustment

Date

2018-11-01

Advisors

Journal Title

Journal ISSN

ISSN

Volume Title

Publisher

2018 UKACC 12th International Conference on Control (CONTROL)

Type

Conference

Peer reviewed

Yes

Abstract

In this paper, a novel decoupling control scheme is presented for a class of stochastic non-linear systems by estimation-based dynamic set-point adjustment. The loop control layer is designed using PID controller where the parameters are fixed once the design procedure is completed, which can be considered as an existing control loop. While the compensator is designed to achieve output decoupling in probability sense by a set-point adjustment approach based on the estimated states of the systems using extended Kalman filter. Based upon the mutual information of the system outputs, the parameters of the set-point adjustment compensator can be optimised. Using this presented control scheme, the analysis of stability is given where the tracking errors of the closed-loop systems are bounded in probability one. To illustrate the effectiveness of the presented control scheme, one numerical example is given and the results show that the systems are stable and the probabilistic decoupling is achieved simultaneously.

Description

Keywords

Citation

Zhang, Q. and Hu, L. (2018) Probabilistic Decoupling Control for Stochastic Non-Linear Systems Using EKF-Based Dynamic Set-Point Adjustment. 2018 UKACC 12th International Conference on Control (CONTROL), Sheffield, United Kingdom, 2018, pp. 330-335.

Rights

Research Institute

Institute of Artificial Intelligence (IAI)
Institute of Engineering Sciences (IES)