in this paper, an adaptive neuro fuzzy inference system (anfis) based control is proposed for the tracking of a micro-electro mechanical systems (mems) gyroscope sensor. the anfis is used to train parameters of the controller for tracking a desired trajectory. numerical simulations for a mems gyroscope are looked into to check the effectiveness of the anfis control scheme. it proves that the sy...

a mobile manipulator robot is known as a complex system due to some properties such as coupling between the manipulator and mobile chassis, holonomic and nonholonomic constraints, multivariable and nonlinear dynamics. the control of robot faces the external disturbance, parametric uncertainty and unmodeled dynamics. therefore, the use of an adaptive fuzzy system is suggested for its capability ...

In this paper, an Adaptive Neuro Fuzzy Inference System (ANFIS) based control is proposed for the tracking of a Micro-Electro Mechanical Systems (MEMS) gyroscope sensor. The ANFIS is used to train parameters of the controller for tracking a desired trajectory. Numerical simulations for a MEMS gyroscope are looked into to check the effectiveness of the ANFIS control scheme. It proves that the sy...

this paper presents a delay compensator fuzzy control for trajectory tracking of omni-directional mobile robots. fuzzy logic control (flc) of the robots is a suitable strategy for dealing with model uncertainties, nonlinearities and disturbances.  on the other hand, in many robotic applications such as mobile robots, delay phenomenon is able to substantially deteriorate the behavior of system's...

this paper introduces a technique for controlling a class of uncertain chaotic systems using an adaptive fuzzy proportional-integrator-derivative (pid) controller with h∞ tracking performance. the purpose of this work is to achieve optimal tracking performance of the controller using backtracking search algorithm (bsa). bsa, which is a novel heuristic algorithm, has an easy structure with singl...

this paper presents an indirect adaptive system based on neuro-fuzzy approximators for the speed control of induction motors. the uncertainty including parametric variations, the external load disturbance and unmodeled dynamics is estimated and compensated by designing neuro-fuzzy systems. the contribution of this paper is presenting a stability analysis for neuro-fuzzy speed control of inducti...

This paper presents a fuzzy tracking control design based on H∞ performance for nonlinear systems. The Takagi-Sugeno fuzzy model is employed to approximate a nonlinear system. Based on the H∞ tracking performance, the nonlinear system output is controlled to track a reference signal, and at the same time the tracking performance is attenuated to a prescribed level. Linear matrix inequalities (L...

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 ...