Search

This paper investigates the observer-based adaptive fuzzy quantized control problem for a class of fractional-order nonlinear time-delay systems with unknown control gains based on a modified fractional-order dynamic surface control (FODSC) technique and an indirect Lyapunov method. First, a fractional-order, high-gain state observer is constructed to estimate unavailable state information. Furthermore, the Nussbaum gain technique and a fractional-order filter are adopted to cope with the problem of unknown control gains and to reduce the computational complexity of the conventional recursive procedure, respectively. Moreover, through integration with the compensation mechanism and estimation model, the adaptive fuzzy quantized controllers and adaptive laws are designed to ensure that all the signals of the closed-loop system are bounded. In the end, the proposed controller is applied to a numerical example and a single-machine-infinite bus (SMIB) power system; the simulation results show the validity, superiority, and application potential of the developed control strategy. [ABSTRACT FROM AUTHOR]

In this paper, a fractional-order backstepping dynamic surface control (DSC) method is developed to cope with the stabilization problem for fractional-order nonlinear systems with uncertainties and external disturbances. In each step, a neuro-fuzzy network system is employed to approximate the unknown nonlinear function existing in fractional-order subsystem. Furthermore, a modified fractional-order filter is designed to avoid the problem of explosion of complexity caused by the recursive procedure. Then based on the fractional-order Lyapunov stability theory, the corresponding adaptive backstepping DSC controller is proposed to guarantee the stability of the fractional-order closed-loop systems. Finally, three examples are given in simulation part to demonstrate the validity of the proposed control method. [ABSTRACT FROM AUTHOR]

This paper studies the issue of adaptive hybrid fuzzy output feedback control for a class of commensurate fractional-order (FO) nonlinear systems with time-varying delays and input saturation. First, a hybrid fuzzy state observer is designed to estimate the unmeasured system states, where the neuro-fuzzy network systems (NFNSs) are introduced to handle the unknown nonlinear functions. Furthermore, based on DSC technique, a modified FO filter is designed to avoid the issue of the "explosion of complexity" generated by the traditional backstepping control design approach. Moreover, based on the recursive technique and an indirect Lyapunov method, an adaptive controller is constructed to ensure that all the signals of FO closed-loop systems are bounded. Finally, the simulation results are presented to demonstrate the effectiveness of the presented control scheme. [ABSTRACT FROM AUTHOR]