Event-triggered Adaptive Control For Nonlinear Interconnected Systems

With the development of modern industrialization and intelligence,the research on nonlinear interconnected systems with the characteristics of large scale and strong coupling has attracted extensive attention,such as electric power systems,transportation systems,and computer communication network systems.During the system operation,the actuators and sensors may suffer from failures and there inevitably exists time delay,which may degrade the system control performance or make the system unstable.How to alleviate the impact of the above factors on system performance and ensure the stability of the system is an important research topic.On the other hand,with the development of computer and communication technologies,the transmissions in networks increase greatly.However,the bandwidth resource is finite in general.Therefore,to effectively reduce the communication burden and the number of control updating,the event-triggered control scheme has attracted much attention.Based on the existing works,by using Lyapunov stability theory,backstepping method,decentralized control technique,fuzzy logic systems and adaptive neural network technique,etc.,this paper studies the event-triggered control problem for a class of nonlinear interconnected systems.The contents of this dissertation improve the event-triggered control theory of nonlinear interconnected systems.The main contents of this dissertation are given as follows:1.For a class of nonlinear interconnected systems,the event-triggered decentralized control problem is studied based on a state-error-triggered strategy.Fuzzy logic systems are used to approximate the unknown nonlinear functions,and a novel adaptive law is designed by using the state information at the triggering instants to reduce the calculation burden.To reduce the communication burden and deal with the errors between continuous and discrete states,an event-triggered mechanism with adjustable parameters is constructed in the sensor-to-controller channel.With the help of the proposed controller,all states of the closed-loop system can converge to the neighborhood around the origin and the Zeno phenomenon is excluded.2.The event-triggered decentralized control problem is discussed for a class of nonlinear interconnected systems with actuator faults and time delays.Fuzzy logic systems are used to estimate the unknown nonlinear functions and the upper bound of the approximation error is allowed to be unknown.To reduce the number of control updating,an event-triggered mechanism is constructed in the controller-to-actuator channel.By using the backstepping technique,command filter method and Lyapunov-Krasovskii functional technique,an adaptive fuzzy controller is designed to ensure that all states of the closed-loop system are bounded and the tracking error can converge to the neighborhood near the origin.Meanwhile,the differentiability of the functions is used to prove that the Zeno phenomenon does not occur.3.The event-triggered finite-time decentralized control problem is studied for a class of nonlinear interconnected systems with actuator faults.The adaptive neural network technique is used to approximate the unknown nonlinear functions,and the adding a power integral technique is used to design the finite-time controller to quicken the convergence rate of system state.Since the designed finite-time controller is not differentiable,the existing methods that use the functions’ differentiability to exclude Zeno behavior cannot be directly applied to this chapter.Therefore,by using the controller characteristic that is not differentiable only at the zero point,a new analysis method is provided to excluded the Zeno phenomenon.4.The event-triggered finite-time decentralized control problem is investigated for a class of nonlinear interconnected systems with sensor faults.Due to the existence of sensor failures,it is relatively difficult to design finite-time controllers by combining adding a power integral and adaptive neural network techniques.To this end,a switching-type finite-time eventtriggered controller is constructed by using the recursive technique and the Lyapunov function method to ensure that all states of the closed-loop system can converge to the neighborhood near the origin in a finite time.Meanwhile,the one-sided differentiability of the functions is used to prove that the Zeno phenomenon does not occur.5.The event-triggered fixed-time decentralized control problem is studied for a class of nonlinear interconnected systems with actuator and sensor faults.To reduce the communication burden and the number of control updating,the event-triggered mechanisms are designed both in the sensor-to-controller and the controller-to-actuator channels.The existence of the faults makes the co-design of event-triggered mechanisms difficult.To this end,an event-triggered mechanism with adjustable parameters is constructed only using the measured information compromised by the failures,and the influence of the faults is mitigated by using adaptive fuzzy control technique.Furthermore,a fixed-time controller is designed to ensure that all states of the closed-loop system can converge to the neighborhood near the origin within a fixed time and the Zeno phenomenon is excluded.