Three-Dimensional Maneuver Control of Multiagent Systems With Constrained Input.

Area of Science:

• Robotics
• Control Systems
• Artificial Intelligence

Background:

• Multiagent systems (MASs) are crucial for complex tasks but face challenges with nonholonomic constraints and control limitations.
• Existing controllers often lack flexibility for diverse formation maneuvers and practical input bounds.

Purpose of the Study:

• To develop a novel 3-D maneuver controller for nonlinear MASs with nonholonomic constraints and control saturation.
• To enhance the efficiency and flexibility of formation control in MASs for general maneuver tasks.
• To ensure practical applicability by incorporating control input bounds and natural heading alignment.

Main Methods:

• Design of a distributed controller under a specific communication topology.
• Incorporation of nonholonomic constraints and control saturation into the controller design.
• Consideration of agent heading angles for natural trajectory tracking.

Main Results:

• The proposed controller is flexible and efficient for various formation maneuver tasks.
• Control saturation ensures practical applicability by bounding control inputs.
• The controller achieves natural tracking motion, aligning formation heading with the reference trajectory.

Conclusions:

• The developed 3-D maneuver controller effectively addresses challenges in nonlinear MASs.
• Simulation results validate the controller's competence for diverse MAS maneuver tasks.
• The controller offers a practical and efficient solution for formation control in MASs.