Robust Adaptive Tracking Control For Interconnected Nonlinear Systems

With the increasing complexity of modern industrial production process,the modeling requirements of controlled system become higher.At present,the common single body model of nonlinear system can not meet its modeling requirements,while the interconnected nonlinear system is composed of multiple interconnected subsystems,which can describe complex large-scale systems.In interconnected nonlinear systems,the unmodeled dynamics of the system itself and the existence of time delay in information interaction have an impact on the stability of the system.At the same time,for the consideration of safety performance,the system needs to meet certain constraints in order to operate stably and reliably.Therefore,it is of great significance to study the control strategy of interconnected nonlinear systems with state constraints in the case of unmodeled dynamics and time delay.In order to solve the above problems,this paper studies the adaptive tracking control of a class of strict feedback interconnected nonlinear systems by using control methods such as dynamic surface control and adaptive neural network online estimation technology.The main research contents of this paper are as follows:Firstly,for a class of strict feedback interconnected nonlinear systems with asymmetric full state dynamic constraints,unstructured uncertainties and external disturbances,in order to reduce the impact of asymmetric full state dynamic constraints on the safety performance of the system,the state dependent nonlinear conversion function is introduced to convert the original constrained interconnected nonlinear system into an equivalent "unconstrained" interconnected nonlinear system,An adaptive tracking control strategy based on dynamic surface control is proposed by using adaptive neural network to estimate the unknown unstructured uncertain function.Secondly,based on the above research,the strict feedback interconnected nonlinear system with unknown control gain and unknown output delay is further studied.The unknown control gain is estimated online by designing adaptive parameters,so as to eliminate the influence of unknown control gain on the controllability and stability of the system.The Lyapunov Krasovskii function is used to deal with the unknown output delay,A decentralized adaptive tracking control strategy based on dynamic surface control is proposed.Thirdly,based on the above research,the strict feedback interconnected nonlinear system with unmodeled dynamics is further studied.In order to reduce the impact of unmodeled dynamics on the accurate modeling of the system in the actual system,a dynamic signal is introduced into the design process of dynamic surface to process the unmodeled dynamics,and combined with the online estimation technology of adaptive neural network,A dynamic surface tracking control strategy based on adaptive neural network is proposed.