Performance-Based Distributed Control of Multiagent Systems: A Dual Phase Approach

Area of Science:

• Control Systems Engineering
• Networked Systems Theory
• Nonlinear Dynamics

Background:

• Networked systems present challenges due to uncertainty and interconnections.
• Distributed control requires robust strategies for uncertain parameters and topologies.
• Strict-feedback systems with unknown gains necessitate advanced adaptive control techniques.

Purpose of the Study:

• To develop a distributed tracking control strategy for uncertain nonlinear strict-feedback systems.
• To handle unknown time-varying gains and directed interaction topologies.
• To guarantee prescribed performance and robustness in networked systems.

Main Methods:

• A dual-phase approach combining robust filtering and adaptive control.
• Construction of a distributed robust filter for trajectory estimation.
• Development of an adaptive control protocol using backstepping and a novel Nussbaum function lemma.

Main Results:

• The proposed method achieves asymptotic output tracking with prescribed transient response.
• Unknown control gains, time-varying and state-dependent, are effectively managed.
• Tracking errors converge to a preassigned residual set with a predefined rate.
• All internal signals are semi-globally ultimately uniformly bounded (SGUUB).

Conclusions:

• The co-designed scheme effectively solves the distributed tracking control problem for complex networked systems.
• The approach enhances robustness and extends applicability to systems with unknown, time-varying gains.
• The results demonstrate the effectiveness through illustrative examples.