Prescribed-Time Tracking Control for Nonlinear MASs With Discrete Reference Signals: A Self-Regulating Control Gains...

Area of Science:

• Control Systems Engineering
• Robotics and Automation
• Networked Systems

Background:

• Nonlinear multiagent systems (MASs) face challenges with parameter uncertainties and external disturbances, impacting tracking control.
• Achieving precise and timely control in MASs is crucial for many engineering applications.
• Existing control strategies may not adequately address fault tolerance and prescribed-time convergence simultaneously.

Purpose of the Study:

• To develop a prescribed-time fault-tolerant tracking control strategy for nonlinear MASs.
• To enhance tracking precision by reconstructing discrete reference signals.
• To ensure system outputs converge to the desired trajectory within a specified time, despite uncertainties and faults.

Main Methods:

• Trajectory reconstruction using cubic spline interpolation for discrete reference signals.
• Design of prescribed-time regulators to create a fault-tolerant tracking controller.
• Stability analysis using Lyapunov methods and simulation examples to validate the approach.

Main Results:

• The proposed controller ensures that the outputs of the controlled system converge to the reconstructed trajectory with arbitrary accuracy within the prescribed tracking time.
• The strategy effectively handles parameter uncertainties and external disturbances in nonlinear MASs.
• Demonstrated effectiveness through stability analyses and a simulation example.

Conclusions:

• The developed prescribed-time fault-tolerant tracking control strategy is theoretically sound and practically applicable.
• The method offers improved tracking precision and robustness for nonlinear MASs.
• This research contributes to the advancement of control engineering for complex networked systems.