Adaptive Synchronization Control Of Uncertain Multi-agent Systems With Prescribed Performance

During the last two decades,multi-agent systems have drawn much attention of many researchers in the robotics and control communities owing to its unique and widespread applications on various engineering problems including cooperative exploration,surveillance,and coordinated searching.A typical multi-agent system consists of a team of mobile robots,robotic manipulators,unmanned surface vehicles(USVs),unmanned aerial vehicles(UAVs).The fundamental idea of multi-agent coordination is to use a team of vehicles instead of using only one single vehicle to cooperatively perform the complex tasks that usually cannot be accomplished by a single vehicle.Multi-agent coordination has several remarkable advantages on higher flexibility,adaptability,and robustness.One fundamental issue in multi-agent coordination is the synchronization control problem.An important concern of synchronization control of multi-agent systems is the communication range constraint.Wireless sensor networks or on-board sensors are typically required for each agent in the group to obtain its neighbors' information.The communication range of a wireless device or on-board sensor is often limited in practical applications.Consequently,considerable attention has been paid to the study of synchronization control of multi-agent systems under communication range constraints.In addition,the transient and steady-state performance of synchronization control system is also of great importance in practice.The thesis studies the synchronization control problem for multi-agent systems with prescribed transient and steady-state performance under communication range constraints.The main contents are summarized as follows.Chapter 2 presents adaptive synchronization tracking control with prescribed performance for a class of uncertain multi-agent systems in the Brunovsky form.We assume that the leader's information(reference information)could only be directly obtained by several followers,and each follower could obtain its neighbors' information within its communication range.Therefore,the synchronization control strategy is distributed in the sense that the control action on each agent in the group could only depends on the information about itself and its neighbors to decide its own movement.Firstly,we employ the graph theory to convert the tracking errors between the followers and the leader into the relative neighbor distance errors and the relative neighbor angle errors.Secondly,we apply the prescribed performance control(PPC)methodology to design an adaptive synchronization tracking controller such that the neighbor distance and angle errors stay always within the prescribed regions that are bounded by the desired performance functions.Using tan-type barrier function and Lyapunov stability theory,the closed-loop adaptive system is proven to be stable,while guaranteeing the transient and steady-state performance of the neighbor error(include the convergence speed,and the maximum overshoot).Simulation results show the effectiveness of the proposed adaptive synchronization tracking controller.Chapter 3 studies the synchronization control problem of a group of USVs with prescribed performance and connectivity preservation under communication range constraints.Firstly,the limited communication range of each agent is given according to the relative distance with receptive to its neighbors.According to the constraint conditions of connectivity preservation and prescribed performance,then we could design the exponentially decaying boundary functions.Secondly,using backstepping procedure,logarithmic barrier Lyapunov functions,and Lyapunov synthesis,a distributed model-based synchronization tracking controller is designed to achieve the connectivity preservation among the initial connected agents and to guarantee system stability with prescribed performance.Besides the nominal case where exact knowledge of the vehicle model is available,we also deal with scenarios wherein both linearin-the-parameter and functional nonlinear uncertainties are present.Subsequently,we employ model-based adaptive control technique to solve the parametric uncertainties and present neural network(NN)approximators to approximate the uncertain nonlinear dynamics.Finally,a stable adaptive synchronization tracking control scheme is presented for the uncertain multiple USV systems with prescribed performance and connectivity preservation.Simulation results show the effectiveness of the proposed adaptive synchronization control scheme.