Distributed Finite-Time Optimization of Second-Order Multiagent Systems With Unknown Velocities and Disturbances

Area of Science:

• Control Theory
• Optimization
• Robotics

Background:

• Distributed optimization is crucial for multiagent systems.
• Challenges include unknown velocities, disturbances, and local cost functions.
• Finite-time control offers faster convergence than traditional methods.

Purpose of the Study:

• To investigate distributed finite-time optimization for second-order multiagent systems.
• To develop an output feedback-based composite distributed control scheme.
• To address unknown velocities and disturbances.

Main Methods:

• Combining finite-time observers (FTOs), homogeneous systems theory, and distributed finite-time estimators.
• Developing FTOs for velocity and disturbance estimation.
• Designing centralized and then distributed finite-time optimization controllers.

Main Results:

• A novel output feedback-based feedforward-feedback composite distributed control scheme is proposed.
• The proposed controllers achieve the distributed finite-time optimization goal.
• Simulations demonstrate the effectiveness and superiority of the control scheme.

Conclusions:

• The developed control scheme successfully addresses distributed finite-time optimization in complex multiagent systems.
• The integration of FTOs and distributed estimators is key to the solution.
• The approach offers enhanced performance and faster convergence for optimization tasks.