A Comparative Study of Fuzzy–PSO and Chaos–PSO
نویسندگان
چکیده
Two popular particle swarm optimization (PSO) formulations; fuzzy–PSO (FPSO) and chaos–PSO (CPSO) have previously been studied in the literature. The charisma factor in FPSO gives the ability to track the particles which are closest to the optimum. CPSO has been aimed to search the area by using the chaotic maps. These two different algorithms are shown to demonstrate sufficient performance independently. Unfortunately, comparisons of their performances are currently unavailable. In this study, both FPSO and CPSO algorithms are examined. The underlying mechanisms and motivations for these methods are discussed. The performances for FPSO and CPSO are compared. The results are presented using benchmark functions.
منابع مشابه
Designing an adaptive fuzzy control for robot manipulators using PSO
This paper presents designing an optimal adaptive controller for tracking control of robot manipulators based on particle swarm optimization (PSO) algorithm. PSO algorithm has been employed to optimize parameters of the controller and hence to minimize the integral square of errors (ISE) as a performance criteria. In this paper, an improved PSO using logic is proposed to increase the convergenc...
متن کاملAdaptive particularly tunable fuzzy particle swarm optimization algorithm
Particle Swarm Optimization (PSO) is a metaheuristic optimization algorithm that owes much of its allure to its simplicity and its high effectiveness in solving sophisticated optimization problems. However, since the performance of the standard PSO is prone to being trapped in local extrema, abundant variants of PSO have been proposed by far. For instance, Fuzzy Adaptive PSO (FAPSO) algorithms ...
متن کاملParticle swarm approaches using Lozi map chaotic sequences to fuzzy modelling of an experimental thermal-vacuum system
Particle Swarm Optimization (PSO) approach intertwined with Lozi map chaotic sequences to obtain Takagi–Sugeno (TS) fuzzy model for representing dynamical behaviours are proposed in this paper. The proposed method is an alternative for nonlinear identification approaches especially when dealing with complex systems that cannot always be modelled using first principles to determine their dynamic...
متن کاملComparative Study of Particle Swarm Optimization based Unsupervised Clustering Techniques
In order to overcome the shortcomings of traditional clustering algorithms such as local optima and sensitivity to initialization, a new Optimization technique, Particle Swarm Optimization is used in association with Unsupervised Clustering techniques in this paper. This new algorithm uses the capacity of global search in PSO algorithm and solves the problems associated with traditional cluster...
متن کاملA PSO-based Optimization of a fuzzy-based MPPT controller for a photovoltaic pumping system used for irrigation of greenhouses
The main asset of this paper is among the uses of fuzzy logic in the engineering sector and especially in the renewable energies as a large alternate of fossil energies, in this paper a PSO-based optimization is used to find the optimal scaling parameters, of a fuzzy logic-based MPPT controller, that maximize the efficiency of a photovoltaic pumping system. The tuning of input and output parame...
متن کامل