This paper presents a discrete-time robust control for electrically driven robot manipulators in the task space. A novel discrete-time model-free control law is proposed by employing an adaptive fuzzy estimator for the compensation of the uncertainty including model uncertainty, external disturbances and discretization error. Parameters of the fuzzy estimator are adapted to minimize the estimat...

In this work a motion control scheme, which belongs to the class of the control schemes known as a sliding mode control with disturbance estimation is proposed. Adaptive fuzzy disturbance estimator works as an identifier of variable part of a system dynamics. Adaptation algorithm is derived by using the Lyapunov stability theory and provides global asymptotic stability of the state errors. For ...

There are some experiences that researcher come across quite number of time for very large networks in the initial samples such that they cannot finish the sampling procedure. Two solutions have been proposed and used by marine biologists which we discuss in this article: i) Adaptive cluster sampling based on order statistics with a stopping rule, ii) Restricted adaptive cluster sampling. Until...

In this paper, a new sensorless model reference adaptive method is used for direct control of active and reactive power of the doubly fed induction generator (DFIG). In order to estimate the rotor speed, a high frequency signal injection scheme is implemented. In this study, to improve the accuracy of speed estimation, two methods are suggested. First, the coefficients of proportional-integral ...

The innovative intelligent fuzzy weighted input estimation method which efficiently and robustly estimates the unknown time-varying input force in on-line is presented in this paper. The algorithm includes the Kalman Filter (KF) and the recursive least square estimator (RLSE), which is weighted by the fuzzy weighting factor proposed based on the fuzzy logic inference system. To directly synthes...

There are some experiences that researcher come across quite number of time for very large networks in the initial samples such that they cannot finish the sampling procedure. Two solutions have been proposed and used by marine biologists which we discuss in this article: i) Adaptive cluster sampling based on order statistics with a stopping rule, ii) Restricted adaptive cluster sampling. Until...

This paper discusses a model reference adaptive sliding-mode control of the sensorless vector controlled induction motor drive in a wide speed range. The adaptive speed controller uses on-line trained fuzzy neural network, which enables very fast tracking of the changing speed reference signal. This adaptive sliding-mode neuro-fuzzy controller (ASNFC) is used as a speed controller in the direct...

this paper presents fuzzy and conventional performance of model reference adaptive control(mrac) to control a dc drive. the aims of this work are achieving better match of motor speed with reference speed, decrease of noises under load changes and disturbances, and increase of system stability. the operation of nonadaptive control and the model reference of fuzzy and conventional adaptive contr...