This paper addresses the design procedure of a fuzzy logic-based adaptive approach for DFIGs to enhance automatic generation control (AGC) capabilities and provide better dynamic responses in multi-area power systems. In doing so, a proportional-integral (PI) controller is employed in DFIG structure to control the governor speed of wind turbine. At the first stage, the adjustable parameters of ...

Two phenomena can produce chattering: switching of input control signal and the large amplitude of this switching (switching gain). To remove the switching of input control signal, dynamic sliding mode control (DSMC) is used. In DSMC switching is removed due to the integrator which is placed before the plant. However, in DSMC the augmented system (system plus the integrator) is one dimension bi...

In this paper, an adaptive fuzzy control scheme is proposed for a class of perturbed strict-feedback nonlinear systems with unknown discrete and distributed time-varying delays, and the proposed design method does not require a priori knowledge of the signs of the control gains.Based on the backstepping technique, the adaptive fuzzy controller is constructed. The main contributions of the paper...

The paper proposed a new fuzzy-neural recurrent multi-model for systems identification and states estimation of complex nonlinear mechanical plants with backlash. The parameters and states of the local recurrent neural network models are used for a local direct and indirect adaptive control systems design. The designed local control laws are coordinated by a fuzzy rule based control system. Sim...

In this paper, the discrete-time nonlinear systems identification and control based on an adaptive filter are introduced. This adaptive filter is mplemented using the adaptive network called Multi Input Fuzzy Rules Emulated Network (MIFREN). Inspired by the neuro-fuzzy network, the tructure of MIFREN resembles the human knowledge in the form of fuzzy IF-THEN rules. The initial value of MIFREN’s...

unknown noise and artifacts present in medical signals with  non-linear fuzzy filter will be estimate and then removed. an adaptive neuro-fuzzy interference system which has a nonlinear  structure presented  for the noise function prediction by before samples. this paper is about a neuro-fuzzy method to estimate unknown noise of electrocardiogram (ecg) signal. adaptive neural combined with fuzz...

in this paper, an optimal adaptive fuzzy integral sliding mode control is presented to control the robot manipulator position tracking in the presence of uncertainties and permanent magnet dc motor. in the proposed control, sliding surface of the sliding mode control is defined according to the information of position tracking error, derivatives, and error integral. in order to estimate bounds ...

According to the character of the volume-lag of the controlled process of three-tank-system, Smith predictor was adopted to compensate three-tank-system fuzzy adaptive control system. Fuzzy adaptive Smith predictive control system is composed with Smith predictor and fuzzy adaptive controller. The PID parameters were setting on line. This algorithm uses fuzzy adaptive PID control to improve the...

A “learning system” possesses the capability to improve its performance over time by interaction with its environment. A learning control system is designed so that its “learning controller” has the ability to improve the performance of the closed-loop system by generating command inputs to the plant and utilizing feedback information from the plant. In this brief paper, we introduce a learning...

Aiming at the characteristics which variable air volume air conditioning system is multi-variable, nonlinear and uncertain system, normal fuzzy neural network is hard to meet the requirements which dynamic control of multi-variable. In this paper, we put forward a recursive neural network predictive control strategy based on T-S fuzzy model. Through T-S fuzzy recursive neural network predictor ...