Asynchronous Parallel Pattern Search for Nonlinear Optimization
SIAM Journal on Scientific Computing
Introduction to the Special Issue on Parallel Meta-Heuristics
Journal of Heuristics
Analysis of Generalized Pattern Searches
SIAM Journal on Optimization
Parameter Selection in Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
RANK ORDERING AND POSITIVE BASES IN PATTERN SEARCH ALGORITHMS
RANK ORDERING AND POSITIVE BASES IN PATTERN SEARCH ALGORITHMS
Parallel Metaheuristics: A New Class of Algorithms
Parallel Metaheuristics: A New Class of Algorithms
Mesh Adaptive Direct Search Algorithms for Constrained Optimization
SIAM Journal on Optimization
Using Sampling and Simplex Derivatives in Pattern Search Methods
SIAM Journal on Optimization
Particle swarm optimization with adaptive population size and its application
Applied Soft Computing
Introduction to Derivative-Free Optimization
Introduction to Derivative-Free Optimization
Hybrid particle swarm optimization algorithm with fine tuning operators
International Journal of Bio-Inspired Computation
A novel hybrid particle swarm optimisation method applied to economic dispatch
International Journal of Bio-Inspired Computation
Particle swarm optimisation algorithm with forgetting character
International Journal of Bio-Inspired Computation
Implicit Filtering
A unified view on hybrid metaheuristics
HM'06 Proceedings of the Third international conference on Hybrid Metaheuristics
Balanced data gathering strategy based on ant colony algorithm in WSNs
International Journal of Wireless and Mobile Computing
Social emotional optimisation algorithm with Levy distribution
International Journal of Wireless and Mobile Computing
Design of wide-beam antenna using dynamic multi-objective BBO/DE
International Journal of Computer Applications in Technology
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Particle swarm optimisation (PSO), a population-based nature inspired algorithm has mostly been used for solving continuous optimisation problems, discrete variants also exist. It finds application in most of the engineering design problems. This paper introduces two improved forms of PSO algorithm applied to PID controller and Smith predictor design for a class of time delay systems. In this paper, derivative free optimisation methods, namely simplex derivative pattern search and implicit filtering are used to hybridise PSO algorithm with improved convergence than original PSO. The effectiveness of the proposed algorithms namely SDPS-PSO, IMF-PSO are demonstrated using unit step set point response for a class of dead-time systems using PID controller and Smith predictor designed using the proposed hybrid PSO algorithms. The results are compared with earlier controller tunings proposed by Kookos, Syrcos, Chidambaram, Kanthaswamy and Luyben.