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This paper presents an approach to the design of analog circuits based on operational amplifiers using genetic algorithms. The input parameter is the transfer function of the required system. The fitness function of the genetic algorithm is implemented by means of a fuzzy inference system. This article includes the synthesis of the methodology used in the design and also some results with a specific...
Different methods and schemes have been proposed in literature for tuning continuous and discrete PI (ProportionalIntegral) controllers. This paper proposes a scheme in which, this controller structure is explored in a different way, by looking its behavior as a lag compensator and tuning it by genetic algorithms. A difference with conventional approaches is the manner to evaluate every individual...
To solve the problem which is hard to avoid the local optimal solution or slower population diversity when using genetic algorithm to generate the fuzzy rules in a fuzzy system, this paper proposes an automatic rule generation using fuzzy genetic algorithm. This algorithm utilizes the rules population diversity and evolutionary speed to automatically adjust the crossover rate and mutation rate based...
One significant challenge in building fuzzy systems for complex problems is the "curse of dimensionality". For the sake of a reduced size of the knowledge base, some rules with incomplete premise structures covering larger areas of the input domain are often desirable. This paper presents a genetic algorithm based approach to searching for suitable antecedents of rules under which specific...
The hybrid approach neuro-fuzzy with subtractive clustering and genetic algorithm (ANFIS-GA) technique is developed to model, to simulate and to optimize fibre to yarn spinning process in textile industry. Starting with cotton, desired yarn is produced on ring frame. The quality and cost of resulting yarn plays a significant role in determining its end application. The challenging task of any spinner...
This paper introduces genetic algorithm (GA) based method to construct a satisfactory fuzzy system directly from some gathered input-output data of the discussed problem. In this method, each individual in the population is constructed to determine the number of fuzzy rules and the premise and the consequent part of the fuzzy system. With the special mutation operation and the adequate fitness function,...
The purpose of this paper is to implement a new method for designation of fuzzy logic controller for STATCOM to improve the voltage profile. Because of the importance of power quality in industrial bus bars when the loads are numerous, the classic methods of control (because of inherent time delay) can not been used. Therefore the fuzzy controller has been developed to for compensation because of...
The purpose of this paper is to study a new method to design the fuzzy controller to control STATCOM for promotion voltage profile. Because of the importance of power quality in industrial bus bars when the loads are numerous, the classic methods of control (because of inherent time delay) can not been used. Therefore the fuzzy controller has been developed to for compensation because of the fast...
We propose a method to interpolate traffic data of roads using genetic fuzzy systems (GFSs). In Japan, car navigation equipment provides drivers with real-time traffic information about principal roads. The information enables giving route guidance. In a previous study, the problem of the method lies in the following two facts because a human designs membership functions of fuzzy c-means (FCM) experientially...
In this two-part paper presents an evolutionary fuzzy design method based energy management strategy for parallel hybrid electric vehicles. The proposed method consists of two steps. In the first phase, a fuzzy logic controller was employed to quantify the energy management system behavior. In the second stage, a genetic algorithm was used for fine-tuning the parameters of the fuzzy controller based...
This research work presents a new approach for fuzzy system building taking into account the accuracy and interpretability of the system. One difficulty in the handling of high-dimensional problems by fuzzy rule-based systems is the exponential increase in the number of rules and in the number of conditions in the antecedent part of the rule. Thus, as first step of the proposed approach we apply a...
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