This paper presents a novel adaptive neuro-fuzzy inference system based on interval Gaussian type-2 fuzzy sets in the antecedent part and Gaussian type-1 fuzzy sets as coefficients of linear combination of input variables in the consequent part. The capability of the proposed ANFIS2 for function approximation and dynamical system identification is remarkable. The structure of ANFIS2 is very sim...

An adaptive neuro fuzzy inference system based on interval Gaussian type-2 fuzzy sets in the antecedent part and Gaussian type-1 fuzzy sets as coefficients of linear combination of input variables in the consequent part is presented in this paper. The capability of the proposed method (we named ANFIS2) for function approximation and dynamical system identification is remarkable. The structure o...

This paper considers the problem of adaptive output feedback tracking control for a class of nonstrict-feedback nonlinear systems with unknown time-varying delays and unknown backlash-like hysteresis. Fuzzy logic systems are used to estimate the unknown nonlinear functions. Based on the Lyapunov–Krasovskii method, the control scheme is constructed by using the backstepping and adaptive techniqu...

Abstract. Combining both kinds of fuzzy logic forms including fuzzy T-S model and adaptive fuzzy logic systems, this paper presents an observer-based ∞ H control scheme for a class of uncertain nonlinear timedelay systems. Firstly, the fuzzy T-S model is used to approximate the nonlinear systems, and an observer is designed to observe the system states, and the fuzzy control law of the fuzzy mo...

The dynamics of the Autonomous Underwater Vehicles (AUVs) are highly nonlinear and time varying and the hydrodynamic coefficients of vehicles are difficult to estimate accurately because of the variations of these coefficients with different navigation conditions and external disturbances. This study presents the on-line system identification of AUV dynamics to obtain the coupled nonlinear dyna...

For a class of uncertain nonlinear systems, this paper presents a method based on biological adaptation strategies of hybrid adaptive fuzzy control method. The method in the controller design, the ecological niche theory function as a consequent of the fuzzy rule fuzzy system, is established based on the biological adaptation of the adaptive controller. The controller design embodies the biolog...

this paper presents designing an optimal adaptive controller for tracking control of robot manipulators based on particle swarm optimization (pso) algorithm. pso algorithm has been employed to optimize parameters of the controller and hence to minimize the integral square of errors (ise) as a performance criteria. in this paper, an improved pso using logic is proposed to increase the convergenc...

Doubly-fed induction generator (DFIG) based wind turbines with traditional maximum power point tracking (MPPT) control provide no inertia response under system frequency events. Recently, the DFIG wind turbines have been equipped with virtual inertia controller (VIC) for supporting power system frequency stability. However, the conventional VICs with fixed gain have negative effects on inter-ar...

We proposed a fuzzy control scheme to implement the cycle-to-cycle control for restoring swing phase of gait using functional electrical stimulation (FES). We designed two fuzzy controllers for the biceps femoris short head (BFS) and the vastus muscles to control flexion and extension of the knee joint during the swing phase. Control capabilities of the designed fuzzy controllers were tested an...