In recent years, soft computing methods have generated a large research interest. The synthesis of the fuzzy logic and the evolutionary algorithms is one of these methods. A particular evolutionary algorithm (EA) is differential evolution (DE). As for any EA, DE algorithm also requires parameters tuning to achieve desirable performance. In this paper tuning the perturbation factor vector of DE ...

It is presented in this paper a method for designing a nonlinear model predictive controller. The controller is based on a hybrid Wiener-Hammerstein fuzzy-neural predictive model and а simplified gradient optimization algorithm. The proposed approach is used to control the product temperature in a Lyophlization plant. The controller efficiency is tested and proved by simulation experiments in M...

In recent years, soft computing methods have generated a large research interest. The synthesis of the fuzzy logic and the evolutionary algorithms is one of these methods. A particular evolutionary algorithm (EA) is differential evolution (DE). As for any EA, DE algorithm also requires parameters tuning to achieve desirable performance. In this paper tuning the perturbation factor vector of DE ...

this paper proposes a novel hybrid algorithm namely apso-bfo which combines merits of bacterial foraging optimization (bfo) algorithm and adaptive particle swarm optimization (apso) algorithm to determine the optimal pid parameters for control of nonlinear systems. to balance between exploration and exploitation, the proposed hybrid algorithm accomplishes global search over the whole search spa...

In this paper a fuzzy logic (FL) based load frequency controller (LFC) called discrete FuzzyP+FuzzyI+FuzzyD (FP+FI+FD) is proposed to ensure the stability of a multi-source power system in restructured environment. The whale optimization algorithm (WOA) is used for optimum designing the proposed control strategy to reduce fuzzy system effort and achieve the best performance of LFC task. Further...

This paper introduces an improved electromagnetism-like algorithm (IEM) for recurrent fuzzy neural controller design. The hybrid IEM algorithm combines the advantages of the electromagnetism-like (EM) algorithm and the genetic algorithm (GA). The proposed IEM is composed of initialization, local search, total force calculation, movement, and evaluation. For recurrent fuzzy neural controller des...

In this paper, an optimal controller for the longitudinal channel of an autonomous helicopter model is designed by blending together two artificial intelligence techniques, genetic algorithms and fuzzy control. An evaluation index that captures the complex, constrained, multiple objective character of the problem was built based on several design requirements expressed in terms of the time resp...

In this paper, a consistent pattern with the optimal coordinated design of PSS and SSSC controller to improve the damping of low frequency oscillations is shown. In this design, sensing and signal transmission time delays are considered as effectiveness parameters. The design problem has been considered an optimization problem and biogeography-based optimization (BBO) algorithm is used for sear...

The concept of intelligently controlling the search process of gravitational search algorithm (GSA) is introduced to develop a novel data mining technique. The proposed method is called fuzzy GSA miner (FGSA-miner). At first a fuzzy controller is designed for adaptively controlling the gravitational coefficient and the number of effective objects, as two important parameters which play major ro...