Robust Average Formation Tracking for Multi-Agent Systems With Multiple Leaders

In this paper, the formation tracking problem of the multi-agent system under disturbances and unmodeled uncertainties has been studied. An identifier-based robust control algorithm using the neighboring relative information has been proposed to ensure the followers to maintain a given, and time-varying formation and track the average state of the leaders at the same time. Some sufficient conditions for the second-order multi-agent system with multiple leaders in the presence of disturbances and unmodeled uncertainties have been proposed based on the graph theory and the Lyapunov method. Numerical simulations are provided to testify the validity of the algorithm

A Neural-Network based Approach for Nash Equilibrium Seeking in Mixed-order Multi-player Games

Noticing that agents with different dynamics may work together, this paper considers Nash equilibrium computation for a class of games in which first-order integrator-type players and second-order integrator-type players interact in a distributed network. To deal with this situation, we firstly exploit a centralized method for full information games. In the considered scenario, the players can employ its own gradient information, though it may rely on all players' actions. Based on the proposed centralized algorithm, we further develop a distributed counterpart. Different from the centralized one, the players are assumed to have limited access into the other players' actions. In addition, noticing that unmodeled dynamics and disturbances are inevitable for practical engineering systems, the paper further considers games in which the players' dynamics are suffering from unmodeled dynamics and time-varying disturbances. In this situation, an adaptive neural network is utilized to approximate the unmodeled dynamics and disturbances, based on which a centralized Nash equilibrium seeking algorithm and a distributed Nash equilibrium seeking algorithm are established successively. Appropriate Lyapunov functions are constructed to investigate the effectiveness of the proposed methods analytically. It is shown that if the considered mixed-order game is free of unmodeled dynamics and disturbances, the proposed method would drive the players' actions to the Nash equilibrium exponentially. Moreover, if unmodeled dynamics and disturbances are considered, the players' actions would converge to arbitrarily small neighborhood of the Nash equilibrium. Lastly, the theoretical results are numerically verified by simulation examples

COORDINATION OF LEADER-FOLLOWER MULTI-AGENT SYSTEM WITH TIME-VARYING OBJECTIVE FUNCTION

This thesis aims to introduce a new framework for the distributed control of multi-agent systems with adjustable swarm control objectives. Our goal is twofold: 1) to provide an overview to how time-varying objectives in the control of autonomous systems may be applied to the distributed control of multi-agent systems with variable autonomy level, and 2) to introduce a framework to incorporate the proposed concept to fundamental swarm behaviors such as aggregation and leader tracking. Leader-follower multi-agent systems are considered in this study, and a general form of time-dependent artificial potential function is proposed to describe the varying objectives of the system in the case of complete information exchange. Using Lyapunov methods, the stability and boundedness of the agents\u27 trajectories under single order and higher order dynamics are analyzed. Illustrative numerical simulations are presented to demonstrate the validity of our results. Then, we extend these results for multi-agent systems with limited information exchange and switching communication topology. The first steps of the realization of an experimental framework have been made with the ultimate goal of verifying the simulation results in practice

Cooperative Adaptive Learning Control for a Group of Nonholonomic UGVs by Output Feedback

A high-gain observer-based cooperative deterministic learning (CDL) control algorithm is proposed in this chapter for a group of identical unicycle-type unmanned ground vehicles (UGVs) to track over desired reference trajectories. For the vehicle states, the positions of the vehicles can be measured, while the velocities are estimated using the high-gain observer. For the trajectory tracking controller, the radial basis function (RBF) neural network (NN) is used to online estimate the unknown dynamics of the vehicle, and the NN weight convergence and estimation accuracy is guaranteed by CDL. The major challenge and novelty of this chapter is to track the reference trajectory using this observer-based CDL algorithm without the full knowledge of the vehicle state and vehicle model. In addition, any vehicle in the system is able to learn the knowledge of unmodeled dynamics along the union of trajectories experienced by all vehicle agents, such that the learned knowledge can be re-used to follow any reference trajectory defined in the learning phase. The learning-based tracking convergence and consensus learning results, as well as using learned knowledge for tracking experienced trajectories, are shown using the Lyapunov method. Simulation is given to show the effectiveness of this algorithm

Pose consensus based on dual quaternion algebra with application to decentralized formation control of mobile manipulators

This paper presents a solution based on dual quaternion algebra to the general problem of pose (i.e., position and orientation) consensus for systems composed of multiple rigid-bodies. The dual quaternion algebra is used to model the agents' poses and also in the distributed control laws, making the proposed technique easily applicable to time-varying formation control of general robotic systems. The proposed pose consensus protocol has guaranteed convergence when the interaction among the agents is represented by directed graphs with directed spanning trees, which is a more general result when compared to the literature on formation control. In order to illustrate the proposed pose consensus protocol and its extension to the problem of formation control, we present a numerical simulation with a large number of free-flying agents and also an application of cooperative manipulation by using real mobile manipulators