Abstract
In this paper, a novel robust cooperative tracking control algorithm is proposed for nonlinear multi-agent graphical games with disturbances based on adaptive dynamic programming approach. The robust cooperative tracking control policy is obtained by multiplying the coupling gains to the interactive Nash solution of nominal multi-agent systems. The consensus error dynamics and cost function for each node depend only on the information of itself and its neighbors. Through Lyapunov approach, the robust stability conditions are derived to guarantee all the followers synchronize to the leader. A cooperative policy iteration algorithm is utilized to approximatly solve the coupled Hamilton-Jacobi-Isaacs equations, and only critic neural network is employed to approximate the value function and control policy for each node. A novel network weight tuning laws is proposed to guarantee uniform ultimate boundedness of closed-loop systems. Simulation results are utilized to demonstrate the effectiveness of the theoretical results.
Highlights
Research on distributed consensus control for multi-agent systems has attracted increasingly significant attention due to its broad applications among the fields of shape control and target assignment for multiple vehicles [1], [2], formation control [3], cooperative tracking control for multirobot systems [4], and sensor networks schedule [5]
Combing distributed observer and backstepping technique, a distributed adaptive control law is proposed for second-order multiagent systems with heterogeneous nonlinear dynamics in [16]
ROBUST COOPERATIVE TRACKING CONTROL DESIGN In the following, a distributed cooperative tracking control policy is derived by investigating the robustness property of Nash equilibrium solution for nominal differential graphical games, which makes all followers synchronize with the leader
Summary
Research on distributed consensus control for multi-agent systems has attracted increasingly significant attention due to its broad applications among the fields of shape control and target assignment for multiple vehicles [1], [2], formation control [3], cooperative tracking control for multirobot systems [4], and sensor networks schedule [5]. This article proposes an adaptive tracking control strategy for uncertain multi-agent graphical games, by investigating the robust property of Nash equilibrium for the corresponding nominal multi-agent system. This control scheme relies on the solutions of coupled Hamilton-Jacobi (CHJ) equations which is generally impossible to be solved analytically. In [42], a distributed H∞ optimal tracking control scheme is designed for multi-agent zero-sum differential graphical games of general affine nonlinear systems in the presence of external disturbances under unknown dynamics, to guarantee that the cost function converges to the bounded L2-gain optimal value.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
