Low-Computation Tracking Control For A Class Of Strict Feedback Nonlinear Systems

In the face of the tracking control problem in reality,it is often necessary to consider the calculation ability of the controller.The most ideal controller design is to achieve less computational complexity on the basis of ensuring the control performance and the bounded closed-loop signal.However,most of the current fuzzy tracking controllers in the case of high-order systems will generate a lot of computation,which leads to the existing hardware level is difficult to support the controller in practical applications.Based on this,this thesis takes a class of strict feedback nonlinear systems as the control object,and combines the methods of state feedback control,output feedback control and event triggering mechanism to study the low computational complexity tracking control problem of the system under different conditions.By designing the corresponding controller,we can solve the problem that the existing controller has a large amount of calculation and is difficult to realize in reality.The main work and innovation of this thesis are as follows:(1)An adaptive fuzzy tracking control scheme with low computational complexity is proposed for the case of measurable system state.First of all,this scheme relaxes the limitation of tracking signal.Secondly,this scheme avoids the iterative derivation of a large number of virtual signals without using filters,and reduces the complexity of the controller.Finally,this scheme no longer has signals other than the system state as the input of the fuzzy logic system,which greatly reduces the waste of computing power in the previous research of the fuzzy logic system.(2)Aiming at the situation that the system is in network control and the system state is measurable,a low computational complexity event triggered fuzzy tracking control scheme is proposed based on the low computational complexity adaptive fuzzy tracking control scheme.By using the fixed threshold event trigger algorithm,the controller has the advantage of low computational complexity,so that the input signal of the system can transmit data only when the difference between the input signals of the system exceeds the given threshold,which greatly reduces the amount of data transmission.(3)A low computational complexity output feedback tracking control scheme based on event triggering mechanism is proposed for the case that the system is in network control and the state is unpredictable.First,the scheme improves the error conversion function to further constrain the tracking error.Secondly,the fuzzy observer is used to observe the system state to design the controller,which avoids the problem of fuzzy logic system input explosion that may occur in the design of controller with linear observer.Thirdly,this controller also avoids the problem of controller "complexity explosion".Finally,the introduction of the relative threshold event triggered control strategy makes the output feedback controller reduce the amount of data transmission in a different way from the state feedback controller.