Title :
A Random Spatial lbest PSO-Based Hybrid Strategy for Designing Adaptive Fuzzy Controllers for a Class of Nonlinear Systems
Author :
Sharma, Kaushik Das ; Chatterjee, Amitava ; Rakshit, Anjan
Author_Institution :
Dept. of Electr. Eng., West Bengal Univ. of Technol., Kalyani, India
fDate :
6/1/2012 12:00:00 AM
Abstract :
In this paper, a new variant of particle swarm optimization (PSO), called random spatial lbest PSO model, is proposed and implemented for designing a newly devised stable adaptive hybrid fuzzy controller. The newly developed concurrent hybrid strategy for designing fuzzy controllers utilizes the conventional Lyapunov theory and the proposed PSO-based stochastic approach. The objective is to design a self-adaptive fuzzy controller online, optimizing both its structures and free parameters such that the designed controller can guarantee the desired stability and simultaneously provide satisfactory transients performance. The global version and two different lbest variants of PSO schemes and the proposed random spatial lbest model of PSO are employed for three popular, challenging, and nonlinear processes, and the proposed controller emerges as the superior algorithm in terms of tracking performance overall. These results aptly demonstrate the usefulness of the proposed approach.
Keywords :
Lyapunov methods; adaptive control; control system synthesis; fuzzy control; nonlinear control systems; particle swarm optimisation; stability; stochastic processes; PSO-based stochastic approach; adaptive hybrid fuzzy controller design; concurrent hybrid strategy; conventional Lyapunov theory; nonlinear process; nonlinear systems; particle swarm optimization; random spatial lbest PSO-based hybrid strategy; selfadaptive fuzzy controller; stability; Adaptation models; Adaptive systems; Mathematical model; Particle swarm optimization; Process control; Stability analysis; Vectors; Global particle swarm optimization based approach (gPSOBA); Lyapunov theory; hybrid fuzzy controller; lbest particle swarm optimization (PSO); self-adaptive fuzzy controller;
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on
DOI :
10.1109/TIM.2012.2187359