Models' Bank Selection of Nonlinear Systems by Integrating Gap Metric, Margin Stability, and MOPSO Algorithm

摘要

This paper deals with the control of nonlinear systems where the multimodel approach has been used to build global controller. In multimodel approaches, two problems could be generally encountered: (1) how to find the required number of models and (2) what are their locations in an operating space. The developed method integrates gap metric, margin stability and multi-objective particle swarm optimization algorithm (MOPSO) to get a reduced model bank that provides necessary information for controller design. For this, the gap metric and the margin stability are respectively used as a distance measuring tool and as a guideline for selecting the model bank. The controller design is handled as a multi-objective optimization problem. In this context, the MOPSO algorithm is used for tuning optimal PID controllers that give the shortest rise time with a lower overshoot percentage and good margin stability.