In the field of Automation, Fuzzy Control Fuzzy control has significant merits which are utilized in intelligent controllers, especially for vibration control systems. This paper is concerned with the application aspects of the developed MR damper for landing gear system, to attenuate the sustained vibrations during the landing phase. Also a comparative study is made on the responses obtained f...

This paper proposes a methodology of designing a Maximum Power Point Tracking (MPPT) controller for photovoltaic systems (PV) using a Fuzzy Gain Scheduling of Proportional-Integral-Derivative (PID) type controller (FGS-PID) with adaptation of scaling factors (SF) for the input signals of FGS. The proposed adaptive FGS-PID method is based on a two-level control system architecture, which combine...

1PG student, Dept. of EEE, Andhra University (A), Visakhapatnam, India 2Professor, Dept. of EEE, Andhra University (A), Visakhapatnam, India ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract In this paper we summarized the design and implementation of fuzzy logic controller to solve automatic powe...

This paper deals with the application of artificial neural network (ANN) and fuzzy based Adaptive Neuro Fuzzy Inference System(ANFIS) approach to Load Frequency Control (LFC) of multi unequal area hydro-thermal interconnected power system. The proposed ANFIS controller combines the advantages of fuzzy controller as well as quick response and adaptability nature of ANN. Area-1 and area-2 consist...

In this study, a black box modeling of the coupledtank system is obtained by using fuzzy sets. The derived model is tested via adaptive neuro fuzzy inference system (ANFIS). In order to achieve a better control performance, the parameters of three different controller types, classical proportional integral controller (PID), fuzzy PID and function tuner method, are tuned by one of the evolutiona...

A hybrid model is designed by combining the genetic algorithm (GA), radial basis function neural network (RBF-NN) and Sugeno fuzzy logic to determine the optimal parameters of a proportional-integralderivative (PID) controller. Our approach used the rule base of the Sugeno fuzzy system and fuzzy PID controller of the automatic voltage regulator (AVR) to improve the system sensitive response. Th...

In this paper we propose a parallel structure of I-P-D (Integral minus Proportional minus Derivative) type fuzzy controller based on the conventional PID control theory, used to control the speed of DC motor. The conventional PID controller exhibit poor performance when applied to DC motor, it fails to perform satisfactory under parameter variation or load changes. The parallel I-P-D type fuzzy...

The goal of studying the vehicle suspension systems is to reduce the vehicle vibrations which are due to the irregularities of road levels and the fluctuations in the vehicle velocity. These vibrations are transferred to the body and occupants of vehicles through the suspension system. In general, the main function of an active suspension system is to support the vehicle body by reducing the in...

A concept called the decomposition of multivariable control rules is presented. Fuzzy control is the application of the compositional rule of inference and it is shown how the inference of the rule base with complex rules can be reduced to the inference of a number of rule bases with simple rules. A fuzzy logic based controller is applied to a simple magnetic suspension system. The controller h...

This paper presents an internal fuzzy neural model for PID controller tuning. The designed model is used as a predictor in an optimization task for PID controller. It is used a simplified gradient algorithm during the training of the fuzzy neural architecture and for tuning of PID controller’s parameters. The designed tuning algorithm is used for level control of a two cascaded water tanks. The...