Adaptive Control Of Switching Uncertain Stochastic Nonlinear Systems Based On Neural Networks

During the past few years,the applications of switching control technology and switched system theory are wider than before with the development of science and technology,social economy,and culture.The design of switched stochastic nonlinear systems is now a hot topic in the study of switched systems.By employing the backstepping method,adaptive neural network control technique and average dwell time(ADT)scheme,this dissertation discusses the controller design problems for several classes of switched stochastic nonlinear systems,and studies the boundedness problem of the corresponding closed-loop systems.The main contents of this dissertation are listed as follows:1.For a class of stochastic nonlinear switched systems with completely unknown nonlinearities,a new adaptive neural-networks-based tracking controller design approach is developed.In the design procedure,the universal approximation capability of radial basis function(RBF)neural networks(NNs)is used for identifying the unknown compounded nonlinear functions,and the variable separation technique is employed to overcome the design difficulty caused by the nonstrict-feedback structure,respectively.The most outstanding novelty of this paper is that individual Lyapunov function of each subsystem is constructed by flexibly adopting the upper and lower bounds of the control gain functions of each subsystem.Furthermore,by combining the average dwell time(ADT)scheme and adaptive backstepping design,a valid adaptive neural state-feedback controller design algorithm is presented such that all the signals of the switched closed-loop system are in probability semiglobally uniformly ultimately bounded(SGUUB),and the tracking error eventually converges to a small neighborhood of the origin in probability.Finally,the availability of the developed control scheme is verified by two simulation examples.2.A new adaptive neural tracking controller is proposed for a class of non-strict-feedback stochastic nonlinear switching systems with input saturation.In the design process,an auxiliary signal is introduced such that the design difficulties caused by input saturation is handled,the variable separation technique is adopted to deal with the problem of the non-strict-feedback structure,and the common Lyapunov function is constructed via the backstepping technique.Finally,it is proved that all signals of the closed-loop system uniformly bounded,and thetracking error converges to a small neighborhood around the origin.