The paper proposed to apply a hierarchical fuzzy-neural multi-model and Takagi–Sugeno (T–S) rules with recurrent neural procedural consequent part for systems identification, states estimation and adaptive control of complex nonlinear plants. The parameters and states of the local recurrent neural network models are used for a local direct and indirect adaptive trajectory tracking control syste...

Abstract This paper addresses the problem of adaptive fuzzy tracking control for MIMO uncertain nonlinear time-delay systems. The control scheme combines adaptive fuzzy control with  H control. Adaptive time-delay fuzzy logic systems are constructed and used to approximate the uncertain unknown timedelay functions. The  H compensator is designed to eliminate fuzzy approximation errors and ext...

In this paper, a direct adaptive output feedback control scheme using fuzzy systems is presented for a class of uncertain SISO nonlinear systems with unknown control direction. Within this scheme, a high-gain observer is employed to estimate the unavailable system states, a fuzzy system is employed to generate directly the control input signal with only output feedback, and the Nussbaum-type fu...

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 ...

An adaptive fuzzy control system with supervisory controller is proposed to improve dynamic performance of three-phase active power filter APF . The proposed adaptive fuzzy controller for APF does not build an accuratemathematical model but approximates the nonlinear characteristics of APF using fuzzy approximation. The adaptive law based on the Lyapunov analysis can adaptively adjust the fuzzy...

in this paper, a recurrent fuzzy-neural network (rfnn) controller with neural network identifier in direct control model is designed to control the speed and exhaust temperature of the gas turbine in a combined cycle power plant. since the turbine operation in combined cycle unit is considered, speed and exhaust temperature of the gas turbine should be simultaneously controlled by fuel command ...

controller design remains an elusive and challenging problem foruncertain nonlinear dynamics. interval type-2 fuzzy logic systems (it2fls) incomparison with type-1 fuzzy logic systems claim to effectively handle systemuncertainties especially in the presence of disturbances and noises, but lack aformal mechanism to guarantee performance. in contrast, adaptive sliding modecontrol (asmc) provides...

Stimulated by the growing demand for improving the reliability and performance of systems, fault-tolerant control has been receiving significant attention since its goal is to detect the occurrence of faults and achieve satisfactory system performance in the presence of faults. To develop an intelligent fault-tolerant control system, we begin by constructing a design model of the system using a...

The paper presents a general methodology of adaptive control based on fuzzy model to deal with unknown plants. The problem of parameter estimation is solved using a direct approach, i.e. the controller parameters are adapted without explicitly estimating plant parameters. Thus, very simple adaptive and control laws are obtained using Lyapunov stability criterion. The generality of the approach ...