Designing a Practical μ-Synthesis Controller Using the PSO Algorithm

Abstract

In present days nonlinear systems are very common in all industrial fields so it is a very essential need that the system must give robust stability and robust performance. The objective of this paper is to obtain a low-order μ synthesis controller that will help us to become system performance robust. As an issue of weighting function (WF) optimization is solved in the suggested method i.e. μ synthesis, it ensures convergence to a global or local minimum. Population-based algorithms like Particle swarm optimization (PSO), Genetic algorithm (GA), Teaching learning based optimization (TLBO) algorithm, and JAYA have been increasingly employed to solve various optimization problems. In this paper, PSO is used to get an optimized solution of the coefficient of the weighting function. The method proposed is applied to a continuous stirred tank reactor (CSTR).