Coverage Control For Multi-agent Systems

In this thesis,we investigate the coverage control problem,which is mainly about region optimal partition strategy.As an important part of cooperative control,the main objective of coverage control is to offer an information based region partition strategy such that the more important regions can get more attentions from the agents.To achieve this goal,a cost function,depending on both a certain metric and the distribution of the information of interest(density function),is defined to describe the performance of the coverage network;then,a distributed control law will be proposed to minimize the cost function through optimization.Due to these compelling features,the coverage control has emerged in many applications.Moreover,the coverage control are in connection with the multi-agent cooperative control,two-dimension space estimation,optimization and so on.It is a combination of multiple fields and needs more theoretical research.Hence,in this thesis,we take the applications of coverage control into consideration and proposed many practical cases,such as the coverage control with unknown density function,coverage control with nonlinear vehicles and time-optimal coverage control.Invoking the current research results of coverage control and these cases.we find that there are still many problems while applying the theoretical results of coverage control.Motivated by this fact,we focus our attentions on these problems and proposed sorIme novel coverage control algorithms.Furthermore,by using some control theories,like Lyapunov stability theorem and mean-square stability theorem,we strictly show the convergency and stability of the proposed coverage control systems.For more details,the main contributions of this thesis are shown as follows:1.The coverage control with unknown density function.The density function is esti?mated by using the Gaussian estimation algorithm and a novel distributed coverage control algorithm is presented with the estimated density function.To further im?prove this coverage algorithm,we apply the parameter consensus into the estimation systerms and present a consensus based density function estimation algorithm.2.When the measurements from the agents are obtained with white noise,the Bayesian estimation algorithm is employed to approximate the density function.Then,a novel distributed coverage control algorithm based on Bayesian estimation is pro?posed for the multi-agent system.Moreover,the stability of the proposed coverage control system is demonstrated by using the mean-square stability theorem.3.For the coverage control with nonlinear dynamical vehicles,we firstly investigate the coverage control with unicycles and ASUs.After transforming the multi-agent coverage control problems into the moving target tracking problems,a novel cover-age control law is proposed for the agents in the kinermatical level.On this basis,a dynamical coverage control strategy is proposed such that the agents can asymp-totically converge to the optimal positions.4.The coverage control problem with time-optimal cost function is formulated in a drift field.Firstly,we use the optimal time for each vehicle to reach an arbitrary point in the given region as a metric.Then,a time-optimal cost function is pre-sented to evaluate the performance of the coverage network.According to the definition of Voronoi partition,a novel time-optimal Voronoi partition for a drift field is developed by using the optimal control theory and Lloyd's algorithms.On this basis,we propose a distributed coverage control law with numerical algorithms and provide a simulation to illustrate the effectiveness of the proposed approaches.