Analysis and Design of Softly Switched Model Predictive Control
| Authors: | Wang Jingsong, University of Birmingham, United Kingdom
Grochowski Michal, Gdansk University of Technology, Poland
Brdys Mietek, University of Birmingham, United Kingdom |
|---|
| Topic: | 5.4 Large Scale Complex Systems |
|---|
| Session: | Large Scale Complex Systems I- Theory |
|---|
| Keywords: | predictive control, discrete-time systems, constraints, stability analysis, supervisory control, sequential switching |
|---|
Abstract
This paper presents a new approach to soft switching between two model predictive controllers. The motivation for this work comes from the control of large scale hierarchical systems where different operating scenario asking for different control objective makes a single model predictive controller (MPC) unsuitable. The proposed soft switching approach shows much better switching performance both in system output and control input than the traditional hard switching. The stability of the designed soft switching process is analysed and sufficient conditions for stability are derived. Numerical examples with simulation results show that the proposed approach can be useful in practical applications.
