In this paper, the authors propose two indirect adaptive fuzzy control schemes for a class of uncertain continuous-time single-input single-output (SISO) nonlinear dynamic systems with known and unknown control direction. Within these schemes, fuzzy systems are used to approximate unknown nonlinear functions and the Nussbaum gain technique is used to deal with the unknown control direction. Thi...

This paper presents the nano-positioning control of a piezoelectric platform. A Bouc-Wen model is established to describe the nonlinear hysteretic effect of piezoelectric systems. Three kinds of compensators, traditional PI controller, PI-like fuzzy logic controller (FLC) and adaptive PI-FLC controller, are designed for the piezoelectric systems. The adaptive PI controller is tuned on-line by m...

An adaptive control based on fuzzy logic has been implemented for Gas Tungsten Arc Welding (GTAW). This adaptive controller eliminates the problems frequently experienced with traditional Automatic Voltage Control (AVC) systems, which do not adequately perform for all operational conditions because of the non-linear relationship between the arc voltage, current and arc length. This paper examin...

This paper shows how adaptive systems can learn to add an optimal amount of noise to some nonlinear feedback systems. Noise can improve the signal-to-noise ratio of many nonlinear dynamical systems. This “stochastic resonance” (SR) effect occurs in a wide range of physical and biological systems. The SR effect may also occur in engineering systems in signal processing, communications, and contr...

A new adaptive anomaly detection framework, based on the use of unsupervised evolving connectionist systems, is proposed to address the issue of concept drift. It is designed to adapt to normal behavior changes while still recognizing anomalies. The evolving connectionist systems learn a subject’s behavior in an online, adaptive fashion without a priori knowledge of the underlying data distribu...

During the last two decades, there has been significant progress in the area of adaptive control design of nonlinear systems (Krstic et al., 1995; Sastry & Isidori, 1989; Slotine & Li 1991; Spooner et al., 2002). Most of the developed adaptive control schemes assume that an accurate model of the system is available and the unknown parameters appear linearly with respect to known nonlinear funct...

Adaptive fuzzy-based tracking control designs will be proposed in this paper for both holonomic mechanical systems as well as a large class of nonholonomic mechanical systems with plant uncertainties and external disturbances. A unified and systematic procedure is employed to derive the controllers for both holonomic and nonholonomic mechanical control systems, respectively. First, a fuzzy logi...

This paper is concerned with the problem of adaptive fuzzy output tracking for a class of perturbed strict-feedback nonlinear systems with time delays and unknown virtual control coefficients. Fuzzy logic systems in Mamdani type are used to approximate the unknown nonlinear functions, then the adaptive fuzzy tracking controller is designed by using the backstepping technique and Lyapunov–Krasov...

The concept of fuzzy approximate disturbance decoupling is introduced for a class of MIMO nonlinear systems with unknown nonlinearities. Based on the backstepping technique, a direct adaptive fuzzy almost disturbance decoupling control scheme is proposed. The proposed fuzzy controllers guarantee internal uniform ultimate boundedness of the closed-loop adaptive systems and render a bounded appro...

In this paper, an adaptive fuzzy robust output feedback control approach is proposed for a class of single input single output (SISO) strict-feedback nonlinear systems without measurements of states. The nonlinear systems addressed in this paper are assumed to possess unstructured uncertainties, unmodeled dynamics and dynamic disturbances, where the unstructured uncertainties are not linearly p...