Consensus Impulsive Control For A Class Of Multi-agent Systems

Over the past few years,the multi-agent cooperative control has been greatly developed.In addition,Multi-agent control method has been applied to all walks of life,such as industrial robots,aerospace technology,unmanned aerial vehicles,traffic scheduling,smart power grid and other fields.Most of the existing reports on multiagent control adopted the continuous control method which has high energy consumption and low control efficiency,but the research on impulsive control is relatively few.In this paper,the problem of consensus impulse control for a class of nonlinear multi-agent systems is studied.The main work contents of this paper are as follows:(1)The consensus problem of multi-agent systems is studied,which has the known nonlinear dynamics and impulsive control input.We consider both leadless and leader-following multi-agent systems and two impulsive control protocols are designed respectively.Firstly,consensus impulse control method based on event triggering mechanism are constructed by using the introduced reference quantity.Then,the sufficient conditions for the system to achieve consistency were analyzed and the Zeno behavior was excluded by using the impulse equation theory and Lyapunov stability analysis method.Finally,the correctness and validity of the conclusions are given to verify for numerical example.The control method only requires the agent to communicate with the neighbor at the impulsive time,which can reduce the control and communication cost of the system.(2)The consensus problem of multi-agent systems is studied,which has the unknown nonlinear dynamics and impulsive control input.Firstly,consensus impulse control method based on event triggering mechanism are constructed by using the Radial Basis Neural Network.Then,the sufficient conditions for the system to achieve consistency were analyzed and the Zeno behavior was excluded by using the impulse equation theory and Lyapunov stability analysis method.Finally,the correctness and validity of the conclusions are given to verify for numerical example.The control method have removed the dependence on the system model is beneficial to improve the robustness and practicability of the system.