Optimum design of fuzzy controller using hybrid ant lion optimizer and Jaya algorithm

Azizi, Mahdi; Ghasemi, Seyyed Arash Mousavi; Ejlali, Reza Goli; Talatahari, Siamak

doi:10.1007/s10462-019-09713-8

Cited by 68 publications

(19 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Wang et al combined wavelet Renyi entropy with three-segment encoded Jaya algorithm to solve Alcoholism Identification [27]. Azizi et al used hybrid ant lion optimizer and Jaya algorithm to solve fuzzy controller optimum design [28]. In 2018, Rao et al employed elitist-Jaya algorithm to solve heat exchangers multi-objective optimization problem [29] and proposed a multi-team perturbation guiding Jaya algorithm for wind farm layout optimization problem [30].…”

Section: Jaya Variants Improvementsmentioning

confidence: 99%

Self-adaptively Commensal Learning-based Jaya Algorithm with Multi-populations and its Application

Xie

Zhang

Ouyang³

et al. 2021

Preprint

View full text Add to dashboard Cite

Jaya algorithm is an advanced optimization algorithm, which has been applied to many real-world optimization problems. Jaya algorithm has better performance in some optimization field. However, Jaya algorithm exploration capability is not better. In order to enhance exploration capability of the Jaya algorithm, a self-adaptively commensal learning-based Jaya algorithm with multi-populations (Jaya-SCLMP) is presented in this paper. In Jaya-SCLMP, a commensal learning strategy is used to increase the probability of finding the global optimum, in which the person history best and worst information is used to explore new solution area. Moreover, a multi-populations strategy based on Gaussian distribution scheme and learning dictionary is utilized to enhance the exploration capability, meanwhile every sub-population employed three Gaussian distributions at each generation, roulette wheel selection is employed to choose a scheme based on learning dictionary. The performance of Jaya-SCLMP is evaluated based on 28 CEC 2013 unconstrained benchmark problems. In addition, three reliability problems, i.e. complex (bridge) system, series system and series-parallel system are selected. Compared with several Jaya variants and several state-of-the-art other algorithms, the experimental results reveal that Jaya-SCLMP is effective.

show abstract

Section: Jaya Variants Improvementsmentioning

confidence: 99%

Self-adaptively Commensal Learning-based Jaya Algorithm with Multi-populations and its Application

Xie

Zhang

Ouyang³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…In order to optimize the design of fuzzy controller Azizi et al [142] hybridize ALO with Jaya algorithm. They applied their algorithm in seismically excited nonlinear buildings.…”

Section: B Hybrid Variants Of Alomentioning

confidence: 99%

Ant Lion Optimization: Variants, Hybrids, and Applications

2020

View full text Add to dashboard Cite

Ant Lion Optimizer (ALO) is a recent novel algorithm developed in the literature that simulates the foraging behavior of a Ant lions. Recently, it has been applied to a huge number of optimization problems. It has many advantages: easy, scalable, flexible, and have a great balance between exploration and exploitation. In this comprehensive study, many publications using ALO have been collected and summarized. Firstly, we introduce an introduction about ALO. Secondly, we categorized the recent versions of ALO into 3 Categories mainly Modified, Hybrid and Multi-Objective. we also introduce the applications in which ALO has been applied such as power, Machine Learning, Image processing problems, Civil Engineering, Medical, etc. The review paper is ended by giving a conclusion of the main ALO foundations and providing some suggestions & possible future directions that can be investigated.

show abstract

“…Recently, promising meta-heuristic optimization methods are being studied to solve many complex problems such as turning PID controllers using three-stage optimization memetic exploration (3SOME), 21 tuning the membership functions of a fuzzy logic system using bee colony optimization (BCO), 22 optimum design of fuzzy controller using hybrid ant lion optimizer and Jaya algorithm, 23 a survey on the intelligent controller tuning problem, 24 and so on. Among them, the topic of neural networks-based heuristic optimization plays a trending technology.…”

Section: Introductionmentioning

confidence: 99%

Hysteresis compensation and adaptive control based evolutionary neural networks for piezoelectric actuator

2021

View full text Add to dashboard Cite

This manuscript introduces a new adaptive inverse neural (AIN) control method applied to precisely track the piezoelectric (PZT) actuator displacement.First, a 3-layer neural network optimized by the enhanced differential evolution technique which modifies a mutation scheme and provides suggestions for selecting mutant coefficient F, crossover coefficient CR, and population size NP, is used to identify the inverse nonlinearity hysteresis structure of the PZT actuator. Second, a feed-forward control based on the identified model is proposed to compensate for the PZT hysteresis effect. Third, the Lyapunov stability principle is used to design and implement an adaptive law-based neural sliding mode model plus the feed-forward compensator to ensure that the whole PZT plant is operated in asymptotical stability. The experiment results demonstrate the proposed AIN controller proves superiority in comparison with other advanced control methods. K E Y W O R D S adaptive inverse neural controller, back-propagation, enhanced differential evolution, hybrid adaptive inverse neural control, Lyapunov stability concept

show abstract

Optimum design of fuzzy controller using hybrid ant lion optimizer and Jaya algorithm

Cited by 68 publications

References 38 publications

Self-adaptively Commensal Learning-based Jaya Algorithm with Multi-populations and its Application

Self-adaptively Commensal Learning-based Jaya Algorithm with Multi-populations and its Application

Ant Lion Optimization: Variants, Hybrids, and Applications

Hysteresis compensation and adaptive control based evolutionary neural networks for piezoelectric actuator

Contact Info

Product

Resources

About