Distributed Cooperative Optimal Control for Multiagent Systems on Directed Graphs: An Inverse Optimal Approach

Area of Science:

• Control Theory
• Systems Engineering
• Robotics

Background:

• Distributed consensus protocols are crucial for multiagent systems coordination.
• Achieving global optimality and specific performance metrics in consensus remains a challenge.
• Existing methods may not fully address optimal control for systems on directed graphs.

Purpose of the Study:

• To design distributed consensus protocols using an inverse optimal approach for identical linear systems.
• To guarantee both consensus and global optimality with respect to quadratic performance indices.
• To establish necessary and sufficient conditions for inverse optimality and cooperative control.

Main Methods:

• Employing the inverse optimal approach to design distributed consensus protocols.
• Developing inverse optimal theory by introducing the concept of partial stability.
• Deriving necessary and sufficient conditions for inverse optimality and globally optimal cooperative control.

Main Results:

• Proposed necessary and sufficient conditions for inverse optimality in distributed systems.
• Established conditions for globally optimal cooperative control problems on directed graphs.
• Developed basic optimal cooperative design procedures based on asymptotic properties of protocols.

Conclusions:

• The inverse optimal approach effectively designs distributed consensus protocols for linear systems.
• The proposed methods guarantee consensus and global optimality with tunable performance.
• The study provides a theoretical framework and practical design procedures for optimal multiagent coordination.