Practical Output Containment of Heterogeneous Nonlinear Multiagent Systems Under External Disturbances

Area of Science:

• Control Systems Engineering
• Nonlinear Systems Theory
• Multiagent Systems

Background:

• Investigates the practical output containment problem in heterogeneous nonlinear multiagent systems.
• Addresses challenges posed by external disturbances from an exosystem.
• Requires follower outputs to converge to a predefined convex combination of leader outputs.

Purpose of the Study:

• To develop a distributed observer-based control protocol for heterogeneous nonlinear multiagent systems.
• To overcome challenges related to coupled nonlinearities, state dimensions, and system matrices.
• To ensure practical output containment under external disturbances.

Main Methods:

• Construction of an adaptive state observer for leader state estimation using neighboring interactions.
• Development of two new observer classes for followers, utilizing output information and adaptive neural networks (NNs) for nonlinearity compensation.
• Generation of a practical output containment control protocol with a two-step parameter determination algorithm.
• Derivation of containment criteria using Lyapunov stability theory and output regulation methods.

Main Results:

• A novel distributed observer-based control protocol is successfully developed.
• Adaptive neural networks effectively compensate for unknown nonlinearities in follower dynamics.
• Practical output containment criteria are derived for the closed-loop system under external disturbances.

Conclusions:

• The proposed distributed observer-based control strategy effectively solves the practical output containment problem for heterogeneous nonlinear multiagent systems.
• The method demonstrates robustness against external disturbances.
• Simulation results validate the theoretical findings.