Robust Predefined Output Containment for Heterogeneous Nonlinear Multiagent Systems Under Unknown Nonidentical...

Area of Science:

• Control Theory
• Nonlinear Systems
• Multiagent Systems

Background:

• Heterogeneous nonlinear multiagent systems present challenges in control due to uncertain and nonidentical leader dynamics.
• Achieving robust predefined output containment (RPOC) is crucial for coordinated behavior in such systems.

Purpose of the Study:

• To develop a distributed observer-based control framework to address the RPOC problem for heterogeneous nonlinear multiagent systems with multiple uncertain nonidentical leaders.
• To design adaptive observers that can estimate leader dynamics without prior knowledge and an adaptive controller that compensates for uncertainties.

Main Methods:

• Construction of four types of fully distributed adaptive observers to estimate unknown leader dynamics, including parameters, states, and outputs.
• Development of a novel robust predefined output containment controller using adaptive learning techniques and the designed observers.
• Application of output regulation methods and Lyapunov stability theory to derive RPOC criteria.

Main Results:

• The adaptive observers successfully estimate the dynamics of uncertain nonidentical leaders without requiring prior knowledge.
• The developed adaptive controller effectively compensates for uncertainties in follower dynamics and achieves output regulation.
• The derived RPOC criteria guarantee system stability and performance under unknown leader dynamics.

Conclusions:

• The proposed distributed observer-based RPOC control framework is effective for heterogeneous nonlinear multiagent systems with uncertain nonidentical leaders.
• The adaptive nature of the observers and controller allows for handling unknown system parameters and dynamics.
• Simulation results validate the effectiveness of the proposed control strategy.