Research On Adaptive Control Of Nonlinear Feedback System Based On BLF

As we all know,many practical systems are modeled in the forms of nonlinear systems with constraints such as state constraint,input constraint,output constraint and so on.Recently,constrained nonlinear feedback system has been a hot topic.However,most of results are all about nonlinear feedback systems with full state constraints and there are relatively few results for partial state constraints.In fact,full state constraint and output constraint are the special cases of partial state constraint,so the phenomenon of partial state constraint is ubiquitous.Thus it is vital to solve the adaptive control problem of nonlinear feedback system with partial state constraint.In this paper,an adaptive fuzzy control problem of pure feedback system is addressed.Because of unmeasured state,the state observer is designed while the FLS is employed to approximate unknown nonlinear function.Combining with backstepping and logarithm-type Barrier Lyapunov function(BLF),we design an adaptive fuzzy output feedback controller,and then obtain the sufficient conditions for the stability of the nonlinear system.Finally,a numerical example is given to verify the correctness of the results.In addition,an adaptive dynamic surface controller is designed for state constrained nonlinear nonstrict feedback with unknown control direction and time-delay.The FLS is employed to approximate the part of unknown nonlinear function,and one-order sliding mode differentiator is proposed to overcome the explosion of complexity problem.With the help of Nussbaum-type function and Lyapunov-Krasovskii functional method,we can handle the time delay and unknown control direction,and we design the adaptive dynamic surface fuzzy controller to guarantee the boundedness of all the close-loop signals.Finally,an example will verify the effectiveness of the conclusion.