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Research And Application Of Improved Adaptive Fuzzy Control Algorithm

Posted on:2019-02-13Degree:MasterType:Thesis
Country:ChinaCandidate:W WeiFull Text:PDF
GTID:2428330572469125Subject:Control Engineering
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Nonlinear systems are widely found in practical industrial control systems.It has complex characteristics such as strong coupling,large inertia and large time lag.Its control problem has always been a hot topic in the field of control.Uncertainties in nonlinearity and unknown factors such as external disturbances can seriously affect the control accuracy of the system.It can even cause instability.Therefore,it has important theoretical and practical value for controller design and optimization of nonlinear systems.This paper designs and analyzes the stability of controllers for strict feedback uncertain nonlinear systems based on the backstepping,nonlinear tracking differentiator,fuzzy state observer,precise disturbance observer,fuzzy logic system,Lyapunov function stability theory and other theories.This aims to improve the accuracy of the control system.Several improved adaptive fuzzy control schemes are proposed,and the stability of the closed-loop system and the effectiveness of the control algorithm are proved.The main research contents of this paper are as follows:(1)The application of backstepping in strict feedback nonlinear system is studied.Combined with fuzzy logic system to estimate the unknown uncertain function in the system,an adaptive fuzzy control method is proposed.Design a second-order nonlinear tracking differentiator by studying the smooth nonlinear function.The computational expansion problem inherent in the traditional backstep method is effectively avoided.The stability of the closed-loop system is proved by the Lyapunov function.The numerical simulation highlights the superiority of the nonlinear tracking differentiator proposed in this paper by comparing the effects of several different tracking differentiators.The effectiveness of the method is further verified by applying it to the control of a car inverted pendulum system.(2)An adaptive fuzzy control method based on nonlinear tracking differentiator and fuzzy state observer is proposed for a class of switched uncertain nonlinear systems with strict feedback and unknown nonlinear functions.The unknown states of the closed-loop system can be directly observed by the switching fuzzy state observer.Aiming at the filtering error caused by nonlinear tracking differentiator,a compensation signal is constructed to improve the control accuracy.The stability analysis of Lyapunov function proves that all signals in the closed-loop system are bounded.And the tracking error can converge to a small neighborhood of zero in a finite time.At the same time,the proposed control method is applied to Two continuous stirred tank reactor system.The practicability and robustness of the control method are fully proved.(3)An adaptive variable proportional gain fuzzy controller based on exact disturbance observer is proposed for a class of strict feedback nonlinear systems with uncertain functions and unknown external disturbances.The unknown uncertain function in closed loop system is approximated by fuzzy logic system.At the same time,the approximation error and unknown external disturbance of the fuzzy logic system are defined as the total disturbance.A high-order accurate disturbance observer is introduced to feed forward differential compensation for the total disturbance signal.An adaptive variable proportional gain state feedback controller is proposed by designing an adjustable output feedback gain using a nonlinear function.The tracking error of the system can be controlled in any small neighborhood of zero.It is proved by the Lyapunov function that all signals in the closed-loop system are bounded.The effectiveness of the proposed scheme is verified by numerical simulations.
Keywords/Search Tags:Strict feedback nonlinear system, Adaptive fuzzy control, Backstepping, Nonlinear switching system, Nonlinear tracking differentiator, Precise disturbance observer, Fuzzy state observer, Lyapunov function, Variable proportional gain
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