Nonrepetitive Leader-Follower Formation Tracking for Multiagent Systems With LOS Range and Angle Constraints Using...

Area of Science:

• Robotics and Control Systems
• Multiagent Systems Engineering
• Fault-Tolerant Control

Background:

• Leader-follower formation tracking is crucial for multiagent systems.
• Actuator faults and system uncertainties pose significant challenges to control.
• Existing iterative learning control (ILC) methods often require identical trajectories, limiting adaptability.

Purpose of the Study:

• To develop a novel ILC algorithm for leader-follower formation tracking in nonlinear multiagent systems with actuator faults.
• To address iteration-dependent reference trajectories and time-varying constraints.
• To handle parametric and nonparametric system uncertainties, including unknown control input gain functions.

Main Methods:

• A novel iterative learning control (ILC) algorithm is proposed.
• The algorithm accommodates iteration-dependent line-of-sight (LOS) range and angle profiles.
• It addresses iteration and time-dependent constraint requirements on tracking errors.
• Parametric and nonparametric system uncertainties are considered.

Main Results:

• The proposed ILC algorithm ensures formation tracking errors converge to zero uniformly over the iteration domain.
• Constraint requirements on LOS range and angle are satisfied without violation.
• The algorithm demonstrates efficacy in handling unknown system dynamics and actuator faults.

Conclusions:

• The developed ILC algorithm effectively solves the leader-follower formation tracking problem for nonlinear multiagent systems with actuator faults.
• It offers enhanced adaptability through iteration-dependent trajectories and robust performance under uncertainties and constraints.
• Numerical simulations validate the algorithm's practical applicability and effectiveness.