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A unified recursive approach to i) identification for systems like ARMAX, nonlinear ARX, and others, and to ii) adaptive regulation of Hammerstein and Wiener systems is presented. By this method the problem under consideration is transformed to a root-seeking problem, to which the Robbins- Monro (RM) algorithm, the classical stochastic approximation (SA) algorithm, aiming at seeking for roots of an...
In this paper, a design method of adaptive output feedback controller for nonlinear systems with higher order relative degree and some uncertainties in control input term is proposed. The controlled systems are rendered the systems with a relative degree of one by introducing two different virtual filters and applying a variable transformation. The actual control input is designed so that the virtual...
In this paper, a hybrid control strategy, variable universe adaptive fuzzy sliding mode control, is proposed to realize the synchronization of two chaotic gyros in master-slave configuration. According to the Lyapunov stability theory, the stability of the closed-loop error system is guaranteed. The adaptive control scheme is robust to the system uncertainties and external disturbances. Chaos synchronization...
In this paper, we present an iterative learning controller for interconnected nonlinear nonaffine systems with repeatable control tasks. A local learning controller for each subsystem is constructed by a fuzzy neural learning component and a robust learning component to adaptively compensate for the nonaffine nonlinearities and interconnections. The fuzzy neural learning component is designed based...
Nowadays congestion control problem of the intermediate nodes in the Internet has received extensively attention in networking and control community. In this paper, a novel adaptive PID (Proportional-Integral-Differential) controller based on neural networks for the problem of AQM with ECN marks is presented. Considering a previously developed nonlinear dynamic model of TCP/AQM system and the queue...
In this paper, we proposed a new method of a fuzzy adaptive controller design for a class of non-affine nonlinear systems in which functions of the systems are unknown. The Lyapunov stability of the closed loop system, robustness against uncertainty and external disturbance, the convergence of the output error to zero and the boundedness of the internal signal are guaranteed. An illustrative example...
A nonlinear multivariable adaptive decoupling PID control strategy based on multiple models and neural network is proposed for a class of uncertain discrete time nonlinear dynamical systems. The adaptive decoupling PID controller is composed of a linear adaptive PID decoupling controller, a neural network nonlinear adaptive PID decoupling controller and a switch mechanism. The PID parameters of such...
In this paper, adaptive neural network (NN) control is investigated for a class of block triangular multi-inputmulti-output (MIMO) nonlinear discrete-time systems with each subsystem in pure-feedback form with unknown control directions. Each subsystem is transformed into a predictor form such that the noncausal problem can be avoided in the control design. By exploring the properties of block triangular...
A method for controller design is proposed based on the approach of functional combination, which has interpreted the proportional, integral and differential expressions in PID controller as the pre-reverse regulating, overcoming deviation and turnaround accelerating functions. According to the control requirements, appropriate functions should be chosen and then combine them in linear or nonlinear...
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