This paper presents the development of a fuzzy logic library using the dynamic simulation software SIMULINK under MATLAB environment. The developed library includes the main blocks: MIN (minimum operation), MAX (maximum operation), MFG (membership function generator), FUZ (fuzzifier to convert a crisp input into a fuzzy labels), F-RULES (fuzzy rules matrix), F-INF (Min-Max fuzzy inference), DEF...

This article presents an intelligent fuzzy logic controller (FLC) for controlling single-body heaving wave energy converter (WEC) or what is widely known as “Point Absorber”. The controller aims at maximizing the energy captured from the sea waves. The power take-off (PTO) limitations are addressed implicitly in the fuzzy inference system (FIS) framework. In order to enhance the WEC power captu...

This paper presents a new approach that minimizes copper & iron losses and optimizes the efficiency of a variable speed Induction motor drive. This method is based on a simple induction motor field oriented control model includes iron losses uses only conventional IM parameters. In literature, Fuzzy logic and Genetic Algorithms have been used for efficiency optimization of induction motor drive...

This paper presents a new approach that minimizes copper & iron losses and optimizes the efficiency of a variable speed Induction motor drive. This method is based on a simple induction motor field oriented control model includes iron losses uses only conventional IM parameters. In literature, Fuzzy logic and Genetic Algorithms have been used for efficiency optimization of induction motor drive...

New trends and the effect of key factors influence the quality of the holes produced by ECM processes. Researchers developed a fuzzy logic controller by adding intelligence to the ECM process. Maintaining optimum ECM process conditions ensures higher machining efficiency and performance. This paper presents the development of a fuzzy logic controller to add intelligence to the ECM process. An e...

Steer-by-wire performance is largely determined by the control system is applied. In this paper the present modeling and simulation of vehicle steering control system using Particle Swarm Optimization to tune the parameters that are needed on Fuzzy Logic and PID control, the cascade Fuzzy Logic and PID control used for controlling lateral motion and yaw motion errors on the vehicle model be rep...

Sentiment classification aims to detect information such as opinions, explicit , implicit feelings expressed in text. The most existing approaches are able to detect either explicit expressions or implicit expressions of sentiments in the text separately. In this proposed framework it will detect both Implicit and Explicit expressions available in the meeting transcripts. It will classify the P...

We extend Knuth's 16 Boolean binary logic operators to fuzzy logic and neutrosophic logic binary operators. Then we generalize them to n-ary fuzzy logic and neutrosophic logic operators using the smarandache codification of the Venn diagram and a defined vector neutrosophic law. In such way, new operators in neutrosophic logic/set/probability are built. Introduction. For the beginning let’s con...

In this paper, a 2 DOF planar robot was controlled by Mamdani type-PD-Fuzzy Logic Controller (FLC) tuned with particle swarm algorithm (PSO). In a tuning process of PD-FLC, several trajectories were applied to the robot system. The parameters of fuzzy controller were updated based on squared mean error cost function. The PD-FLC tuned by PSO was tested with a different trajectory. The error of t...

This paper presents a novel improved fuzzy particle swarm optimization (IFPSO) algorithm to the intelligent identification and control of a dynamic system. The proposed algorithm estimates optimally the parameters of system and controller by minimizing the mean of squared errors. The particle swarm optimization is enhanced intelligently by using a fuzzy inertia weight to rationally balance the ...