The objective of the Fuzzy Adaptive Control (FAC) is to tune the scaling factors of the direct fuzzy logic controller (FLC). In this novel approach output scaling factor of Fuzzy controller is tuned through adaptation mechanism. The idea is to have a control system that will be able to achieve improvement in tracking set point change and rejection of load disturbance. In this paper, the propose...

In this paper controlled DC-DC converter using several fuzzy logic control law algorithms are studied. These controllers are designed to eliminate the overshoot and reduce the settling time response. In order to improve this property several control algorithms were investigated. The first one was the state controller with decomposed fuzzy PI controller and the second one was fuzzy PD state spac...

This paper describes a fuzzy logic based slip controller for an induction motor, with efficiency optimization for steady state operation. The speed control is accomplished through a Mandani type fuzzy controller, with 11 rules, taking speed error (built with 5 Membership Functions M.F.) and speed error variation (3 M.F.) as inputs, to produce the slip increment (5 M.F.). The average motor input...

The objective of the model reference adaptive fuzzy control (MRAFC) is to change the rules definition in the direct fuzzy logic controller (FLC) and rule base table according to the comparison between the reference model output signal and system output. The MRAFC is composed by the fuzzy inverse model and a knowledge base modifier. Because of its improved algorithm, the MRAFC has fast learning ...

This paper presents the detailed account on the control design for input tracking of a buck converter driven dc motor. Proportional-Integral (PI), Proportional-Integral-type Fuzzy Logic controller (PI-type FLC) and Linear Quadratic Regulator (LQR) are the techniques proposed in this investigation to control the speed of a dc motor. The dynamic system composed from buck-converter/dc motor is con...

This paper compares the performance of different control techniques applied to a high-performance brushless DC (BLDC) motor. The first controller is classical proportional integral (PI) controller. In contrast, second one based on adaptive neuro-fuzzy inference systems (proportional integral-adaptive system (PI-ANFIS) and particle swarm optimization-proportional (PSO-PI-ANFIS)). objective regul...

Alternating current electric drives are widely used in many commercial applications. Increasing energy efficiency and improving the quality of regulation major goals. The speed control structure induction machine with indirect vector rotor flux orientation permanent magnet synchronous taken into account. structures were modeled simulated Simulink. Different simulation regimes made for different...

This paper presents a comparative study between two maximum power point tracking (MPPT) algorithms, the incremental conductance algorithm (InC) and fuzzy logic controller (FLC). The algorithms were applied to low photovoltaic conversion system, they both use different PI controllers grid synchronization techniques. Moreover, InC FLC methods have Clarke Park Transformation. To some extent, appro...