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...

In this paper, we present an improved Direct Adaptive Fuzzy (IDAF) controller applied to general control DC motor speed system. In particular, an IDAF algorithm is designed to control an uncertain DC motor speed to track a given reference signal. In fact, the quality of the control system depends significantly on the amount of fuzzy rules-fuzzy sets and the updating coefficient of the adaptive ...

A direct adaptive tracking control architecture is proposed and evaluated for a class of continuous-time nonlinear dynamic systems for which an explicit linear parameterization of the uncertainty in the dynamics is either unknown or impossible. The architecture employs a network of gaussian radial basis functions to adaptively compensate for the plant nonlinearities. Under mild assumptions abou...

In this paper, a Proportional-Derivative and Integral (PD-I) type Fuzzy-Neural Network Controller (FNNC) based on Sugeno fuzzy model is proposed for brushless DC drives to achieve satisfied performance under steady state and transient conditions. The proposed FNNC uses the speed error, change of error and the error integral as inputs. While the PD-FNNC is activated in transient states, the PI-F...

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...

A model reference adaptive control method is proposed for uncertain nonlinear characteristics of spacecraft attitude control system. This method combines fuzzy control methodology and nonlinear feedback linearization methodology, which made the closed-loop system stable and the state of fuzzy system track the state of reference model according to the parallel distributed compensation theory and...