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Backstepping Control Design For A Class Of Nonlinear Pure Feedback Systems

Posted on:2020-11-18Degree:MasterType:Thesis
Country:ChinaCandidate:L L SunFull Text:PDF
GTID:2438330590485559Subject:System theory
Abstract/Summary:PDF Full Text Request
It is well known that pure feedback nonlinear systems have more general form than strict-feedback nonlinear systems.So,this thesis addresses observer-based output feedback Backstepping control design for a class of pure-feedback nonlinear systems and the problem of state feedback control of the systems with input dead zone.The specific research contents are listed as follows;(1)The problems of observer design and observer-based output feedback tracking control are discussed for a class of single input and single output pure feedback nonlinear systems.Convex combination approach is employed to construct state observer,furthermore,neutral networks are used to approximate the unknown nonlinear function and adaptive neural backstepping method is used to design the controller to force the system output following the reference signal.The closed-loop stability analysis is given by Lyapunov stability theory.It is shown that under the action of the suggested controller the expected closed-loop performance is achieved.At last,a numeral simulation example is used to test the effectiveness of the proposed control scheme.(2)Based on the works in the Chapter 3,a robust observer design scheme is proposed to estimate the unmeasurable state variables for a class of pure feedback systems with unknown virtual control coefficients.Then,adaptive neural control approach and Backstepping are used to design controller to achieve the expected closed-loop performance.It is shown that under the disigned adaptive neural controller,all the closed-loop signals are bounded and the tracking error converges into a small neighborhood of the origin.A numerical simulation example is used to test the effectiveness of the suggested control scheme.(3)Discusses the problem of output tracking control via state feedback for a class of pure-feedback nonlinear systems with the unknown input dead zone,the unknown input dead zone is represented as the sum of two parts,that is the sum of a linear dead zone and a bounded nonlinear dead zone.A neural network system is used to approximate the unknown nonlinear functions.By adaptive Backstepping technique and the norm properties of the neural network basis function vector,an adaptive neural network state controller is designed.Stability analysis is given by Lyapunov stability theory.
Keywords/Search Tags:Neural network control, Observer, Nonlinear system, Dead zone, Backstepping technology
PDF Full Text Request
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