Robust static output feedback control using a Particle Swarm Optimization-DE-linear matrix inequality algorithm hybrid algorithm

TL;DR

This paper introduces a hybrid Particle Swarm Optimization-DE algorithm combined with linear matrix inequalities to improve robust static output feedback control for uncertain systems, demonstrating enhanced convergence and accuracy.

Contribution

A novel hybrid algorithm integrating PSO, DE, and LMI methods for solving bi-linear matrix inequality problems in robust control design.

Findings

Improved convergence rate over existing methods

Enhanced accuracy in controller optimization

Effective handling of bi-linear matrix inequality constraints

Abstract

Under the multi-objective framework, this paper presents a hybrid algorithm to solve robust static output feedback control problem for continuous poly-topic uncertain system. To obtain static output feedback gain, a new hybrid algorithm is proposed by combination of a hybrid algorithm of the Particle Swarm Optimization and Differential Evolution (DE), and the linear matrix inequality method. The proposed algorithm is used to solve a optimization problem with a bi-linear matrix inequality constraints. The Particle Swarm Optimization-DE hybrid algorithm was used to obtain a population of controllers, and linear matrix inequality approach was used to optimize a performance criterion of the system. Taking a hybrid H 2/H infinite control problem as example, the detailed algorithm is presented to solve robust static output feedback control problem. The simulation results show that the proposed hybrid algorithm improves the convergence rate and accuracy of iterative methods and the original DE-linear matrix inequality algorithm.