Research On Networked Control Problems Of Two Types Of Hamiltonian Systems

In recent years,network system has been widely used in automobile,aerospace,industrial manufacturing and other fields because of its standby resource sharing,modular design,low cost of the system implementation and maintenance.However,under the limitation of network bandwidth,various nodes will be affected by the complexities such as parameter uncertainty,nonlinear interference,communication delay,data loss,fading channels.These complexities also affect performance and the closed-loop stability of the control system and filtering process.On the other hand,port-controlled Hamiltonian(PCH)systems are a class of important nonlinear systems,the Hamiltonian function in the system can represent essential system properties and can be used as a satisfactory candidate of Lyapunov function which makes the stability analysis easier.But PCH systems have always been described and used in non-networked systems.There have not been reported for the control problem of Hamiltonian system in network environment and the application of Hamiltonian function method.Thus,it is the problem faced that how to design controller to deal with the complexity under network environment by using the Hamiltonian system method.This paper investigates the control problems of Hamiltonian system with network complexity.The proper control law is designed to guarantee the stability of the original systems or their estimator systems.The specific content is as follows:1)studies the problem of practical finite-time fuzzy control for a class of Hamiltonian systems by an adaptive event-triggered approach.For a class of uncertain Hamiltonian systems,a controller based on the event-triggered mechanism is designed to realize the finite time convergence of the state of the closed-loop system.An unknown function of the system is approximated by an adaptive fuzzy system.According to a semi-global practical finite-time stability criterion,a novel adaptive fuzzy finite time controller is presented.The controller is updated under the respective triggering conditions.Based on the special structure of Hamiltonian systems and Lyapunov theory,a sufficient condition is obtained so that the states of original systems converge to a small neighborhood containing the origin in a finite time.Meanwhile,with the proposed controller,there exists a positive lower bound for the interexecution time,and the Zeno phenomenon is avoided.The efficiency of the proposed controller,adaptive law and event triggered conditions are also proved by a circuit system simulation example.2)studies the problem of distributed estimation and control for a class of stochastic Hamiltonian systems under fading channels.For a class of stochastic Hamiltonian systems with fading channels in the sensor network,a distributed estimator is designed to estimate the target state of the system and guarantee the exponentially stable in the mean square sense of the estimation system.The phenomenon that the channel output is related to the target state and the estimation of the adjacent state is considered to facilitate the implementation of distributed state estimation.Based on the stochastic analysis method and the structural properties of the Hamiltonian system,the sufficient conditions are obtained for the existence of the designed estimator gain and control law for each sensor.Two simulation examples are given to indicate the validity of the result.