Intelligent Tracking Control Of Uncertain Nonlinear Systems Based On Event Triggerin

For control systems,output tracking is one of the fundamental problems in control theory,and is widely used in practical fields such as aerospace,chemical production,and military tracking.On the other hand,most practical industrial systems have nonlinear characteristics,and adaptive intelligent control provides an effective control synthesis method for uncertain systems with its good approximation,learning and information processing ability for nonlinear functions.In addition,with the extensive application of computer and network technology in control system,it is a development trend of current control theory research to rationally utilize limited real-time computing resources and communication bandwidth to achieve more efficient feedback control.Therefore,under the framework of adaptive control,backstepping technology and asymptotic/fixed-time stability theory,this paper studies the event-triggered adaptive intelligent tracking control problem for different types of uncertain nonlinear systems.The main contents are as follows:First,the fixed-time tracking control of a class of nonlinear systems with strict feedback form under an event-triggered mechanism is considered.The nonlinear terms in the system can be effectively dealt with by fuzzy logic systems.For the unknown control coefficient in the system,by constructing the Lyapunov function containing its lower bound,combined with the boundary estimation method and well-defined smooth functions,the requirement that the lower bound of control coefficient must be known in the control law can be relaxed.In the case of adding an event-triggered mechanism,an adaptive fixed-time tracking scheme independent of the initial state is designed,and the practical fixed-time stability of the system is proved by the fixed-time stability criterion.The simulation results verify the effectiveness of the control scheme.Secondly,the adaptive event-triggered asymptotic tracking control based on prescribed performance is studied for a class of nonlinear systems with nonstrict feedback structure.The upper bound of the unknown external disturbance in the system is assumed to be known,and the negative impact of the disturbance on the system is successfully eliminated by the boundary estimation method.The asymptotic tracking of the system can be achieved by constructing a new type of Lyapunov function and combining the defined smooth functions containing the positive integral functions.The boundary conditions of the tracking error are designed through the error transformation and performance function.At the same time,the addition of the event trigger mechanism saves the communication bandwidth and reduces the consumption of network resources.Finally,the simulation results demonstrate the effectiveness of the controller.Finally,an adaptive event-triggered asymptotic tracking control with fixed-time prescribed performance is studied for a class of pure-feedback nonlinear systems.By constructing a new type of Lyapunov function,the restrictive requirement that the upper bounds of the partial derivative of the unknown system functions need to be known is relaxed during the controller design process.Meanwhile,by developing a new fixed-time performance function,the tracking error can converge to the neighborhood of the origin in a fixed time,and finally converges to zero asymptotically through the boundary estimation method and the well-defined smooth functions.Finally,the effectiveness of the design scheme is proved by a numerical simulation.