this paper presents a novel indirect adaptive power system stabilizer (pss) via a developed synergetic control methodology and fuzzy systems. fuzzy system is utilized in an adaptive scheme to estimate the system using a nonlinear model. the synergetic control guarantees robustness of the controller and makes the controller easy to implement because of using a chatter free continuous control law...

In this paper, we present a combined direct and indirect adaptive control scheme for adjusting an adaptive fuzzy controller, and an adaptive fuzzy identification model parameters. First, using adaptive fuzzy building blocks, with a common set of parameters, we design and study an adaptive controller and an adaptive identification model that have been proposed for a general class of the uncertai...

In this paper, we study the design and analysis of adaptive control systems over wireless networks using event-triggering control theory. The proposed event-triggered adaptive control methodology schedules the data exchange dependent upon errors exceeding userdefined thresholds to reduce wireless network utilization and guarantees system stability and command following performance in the presen...

During the last decade a considerable progress has been made in the design of stabilizing controllers for nonlinear systems with known and unknown constant parameters. New design tools such as adaptive feedback linearization, adaptive backstepping, control Lyapunov functions (CLFs) and robust control Lyapunov functions (RCLFs), nonlinear damping and switching adaptive control have been introduc...

In recent years a growing interest was observed in the problem of synchronizing chaotic systems [Afraimovich et al., 1987; Pecora & Carroll, 1990; Cuomo et al., 1993; Blekhman et al., 1995; Nijmeijer & Mareels, 1997; Pogromsky & Nijmeijer, 1999]. It was motivated not only by scientific interest in the problem, but also by practical applications in different fields [Blekhman, 1988; Lindsey, 1972...

A novel adaptive control strategy is proposed herein to increase the efficiency of adaptive control by combining Takagi–Sugeno (T–S) fuzzy modeling and the Ge–Yao–Chen (GYC) partial region stability theory. This approach provides two major contributions: (1) increased synchronization efficiency, especially for parameters tracing and (2) a simpler controller design. Two simulated cases are prese...

This article investigates estimators of a weighted average of stratum-specific univariate parameters and compares them in terms of a design-based estimate of mean-squared error (MSE). The research is motivated by a stratified survey sample of Florida Medicaid beneficiaries, in which the parameters are population stratum means and the weights are known and determined by the population sampling f...

In this paper, an adaptive fuzzy backstepping control approach is developed for a class of nonlinear systems with unknown time delays and unmeasured states. By using fuzzy logic systems to approximate the unknown nonlinear functions, a fuzzy adaptive state observer is designed for estimating the unmeasured states. By combining the adaptive backstepping technique with adaptive fuzzy control desi...

Neural network adaptive filters are mainly used for the interference cancellation techniques. The gradient based design methods are well developed for the design of neural network adaptive filter but they converge to local minima. This paper describes the global optimization interference cancelling techniques for adaptive filtering of interferences in the corrupted signal. The system is designe...

Design of an adaptive controller for complex dynamic systems is a big challenge faced by the researchers. In this paper, we introduce a novel concept of dynamic pole motion (DPM) for the design of an error-based adaptive controller (EBAC). The purpose of this novel design approach is to make the system response reasonably fast with no overshoot, where the system may be timevarying and nonlinear...