In today‟s world, fuzzy logic and particle swarm optimization are used to answer various engineering problems. In this paper, the proportional integral derivative (PID) controller tuning by fuzzy rule method (FRMs) and a particle swarm optimization (PSO) algorithm are proposed to improve controller by adjusting transfer function parameters. The proposed fuzzy rule function and PSO algorithm sea...

This paper deals with the design of a novel fuzzy proportional–integral–derivative (PID) controller for automatic generation control (AGC) of a two unequal area interconnected thermal system. For the first time teaching–learning based optimization (TLBO) algorithm is applied in this area to obtain the parameters of the proposed fuzzy-PID controller. The design problem is formulated as an optimi...

In this paper, a new improved Differential Search Algorithm optimization approach is proposed and successfully applied to the design and tuning of a PID-type Fuzzy Logic Controller. The scaling factors tuning problem of the Fuzzy Logic Controller structure is formulated and systematically resolved, using the improved constrained Differential Search Algorithm-based method. A comparison, with the...

Trial and error method can be used to find a suitable design of a fuzzy controller. However, there are many options including fuzzy rules, Membership Functions (MFs) and scaling factors to achieve a desired performance. An optimization algorithm facilitates this process and finds an optimal design to provide a desired performance. This paper presents a novel application of the Bacterial Foragin...

This paper gives the structure optimization of fuzzy control systems based on genetic algorithm in the MATLAB environment. The genetic algorithm is a powerful tool for structure optimization of the fuzzy controllers, therefore, in this paper, integration and synthesis of fuzzy logic and genetic algorithm has been proposed. The genetic algorithms are applied for fuzzy rules set, scaling factors ...

In this work Artificial Intelligence (AI) techniques like Fuzzy logic, Genetic Algorithms and Particle Swarm Optimization have been used to improve the performance of the Automatic Generation Control (AGC) system. Instead of applying Genetic Algorithms and Particle swarm optimization independently for optimizing the parameters of the conventional AGC with PI controller, an intelligent tuned Fuz...

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 presents two optimal approaches of two-stage fuzzy controller for traffic signals at isolated intersections. Firstly, in the light that traffic status variables in two-stage controller leads to the inefficiency of traffic status weakening under low traffic flow, a two-stage combination fuzzy controller is designed from the perspective of structural optimization; this controller intro...

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...