Designing an interval type-2 fuzzy disturbance observer for a class of nonlinear systems based on modified particle swarm optimization

Abstract

This paper presents a new interval type-2 fuzzy disturbance observer design for a class of nonlinear systems using modified particle swarm optimization. The design procedure has two main parts, including the selection of the initial structure of the type-2 fuzzy disturbance observer, and the optimization of the observer parameters using a modified particle swarm optimization algorithm. The modified particle swarm optimization algorithm has a better performance in terms of the accuracy and convergence rate compared with the standard particle swarm optimization and many other evolutionary algorithms. In this algorithm, the upper and lower bounds of the search space are defined for the parameters of each particle based on their values, and weaker particles are substituted with new particles. To accentuate the outstanding performance of the modified particle swarm optimization for the considered task, its performance is compared with five famous meta-heuristic optimization algorithms. In addition, utilizing interval type-2 fuzzy systems in the proposed observer provides more robustness compared with type-1 fuzzy systems. The effectiveness of the proposed fuzzy disturbance observer is shown through computer simulation and experimental results for the ball and beam system, while the system is subjected to sinusoid and square disturbances, and a comparison is drawn to indicate the superiority of the proposed fuzzy disturbance observer over the other observers.