this article presents a fuzzy robust mixed - sensitivity gain - scheduled h controller based on the loop -shaping methodology for a class of mimo uncertain nonlinear time - varying systems. in order to design this controller, the nonlinear parameter - dependent plant is first modeled as a set of linear subsystems by takagi and sugeno’s (t - s) fuzzy approach. both loop - shaping methodology and...

Industries have many rotational operations that are used for design, transport, lift, drilling, rolling, robotics, and other applications. These rotating applications require a proper controller accurate control of the operation. Separately excited DC motors (SEDCMs) versatile various industrial because their specific speed characteristics. So, smooth operation an SEDC motor, controllers should...

In this study, an adaptive fuzzy sliding-mode control (AFSMC) system is adopted to control the position of an induction servo motor. The AFSMC system comprises the fuzzy control design and the robust control design. In the fuzzy control design a fuzzy controller is designed to mimic an ideal control law. In the robust control design a robust controller is designed to compensate the approximatio...

In this paper, we develop a new control method that brings together the advantages of fuzzy logic and sliding mode control. First, we introduce a non-chattering robust sliding mode control. Then, in order to improve the performance of the controller a fuzzy logic algorithm is integrated with the sliding mode controller. This algorithm decides the slope of the sliding surface of the sliding mode...

This paper represents a novel online self-learning disturbance observer (SLDO) by benefiting from the combination of a type-2 neuro-fuzzy structure (T2NFS), feedback-error learning scheme and sliding mode control (SMC) theory. The SLDO is developed within a framework of feedback-error learning scheme in which a conventional estimation law and a T2NFS work in parallel. In this scheme, the latter...

in this paper we consider the problem of delay-dependent robusth1 control for uncertain fuzzy systems with time-varying delay. the takagi–sugeno (t–s) fuzzy model is used to describe such systems. time-delay isassumed to have lower and upper bounds. based on the lyapunov-krasovskiifunctional method, a sufficient condition for the existence of a robust $h_{infty}$controller is obtained. the fuzz...

In this paper, the problem of robust control of nonlinear fractional-order systems in the presence of uncertainties and external disturbance is investigated. Fuzzy logic systems are used for estimating the unknown nonlinear functions. Based on the fractional Lyapunov direct method and some proposed Lemmas, an adaptive fuzzy controller is designed. The proposed method can guarantee all the signa...

In this paper is presented the study of fuzzy logic power stabilizer for stability of a single machine infinite bus (SMIB). The performance of the system with fuzzy logic based power system stabilizer is compared with the system having conventional power system stabilizer and system without power system stabilizer. The results show that the system with fuzzy logic controller is capable of stabi...

A robust fuzzy control is developed for robot manipulators to guarantee both global stability and Performance. Robot dynamics under consideration may include large nonlinear uncertainties, such as nonlinear load variations and unmodelled dynamics. Fuzzy sets are chosen based on performance requirements and stability regions of the control system. For each fuzzy set, a sub-control is designed, b...

This article presents a fuzzy robust Mixed - Sensitivity Gain - Scheduled H controller based on the Loop -Shaping methodology for a class of MIMO uncertain nonlinear Time - Varying systems. In order to design this controller, the nonlinear parameter - dependent plant is first modeled as a set of linear subsystems by Takagi and Sugeno’s (T - S) fuzzy approach. Both Loop - Shaping methodology and...