Adaptive Neural Network Control For Nonlinear Systems With Unmodeled Dynamics

The past few years,an important research hotspot in the field of nonlinear control is the relevant theoretical research and application of nonlinear systems with unmodeled dynamics.Although the study of this system has attracted many scholars,there are still a lot of control problems with important theoretical research value need to be solved.However,there are still a lot of control challenges that need to be addressed for such systems.Therefore,the thesis studies the related control design issues of several kinds of non-strict feedback form nonlinear systems.The main contents are as follows:(1)An adaptive control method based on neural network is proposed in Chapter 2 for the systems,which are nonlinear systems with non-strict feedback structure and unmodeled dynamics.The main design difficulties are from dealing with the unmodeled dynamics and the non-strict feedback structure.In order to get the desired controller,first of all,a mild assumption related to a dynamic signal is utilized to deal with the unmodeled dynamics.In addition,the structural property of Gaussian functions is presented to handle the non-strict feedback structure.Our design approach is much simpler than the traditional variable partition method.Then,all the state variables of the system are processed under the frame work of adaptive NN and backstepping technology and the theoretical result is further given.Finally,a numerical simulation example is given to prove the boundedness and stability of the closed-loop system.(2)On the basis of Chapter 2,the partial state constraints are further considered for the studied system.To ensure that the partial states are in the constraint ranges,the method of BLFs are introduced in the process of backstepping design.The given design scheme insures that all signals of the closed-loop system are bounded,and the output tracking error can converge to a small region near the origin without violating the partial state constraints.Finally,a practical simulation example is given to prove the boundedness and stability of the closed-loop system.In brief,the study of control problems for nonlinear systems with unmodeled dynamics is still in its initial stage.In this thesis,the adaptive control problems for a class of nonlinear systems with unmodeled dynamics are preliminarily studied under the assumption that the system functions are completely unknown.Up to now,there are still many relevant control problems that need to be solved.To list a few,the control design of nonlinear systems with unmodeled dynamics and full state constraints,the control design of stochastic systems with unmodeled dynamics,and the design of pure-feedback nonlinear systems with unmodeled dynamics,and so on.