Tracking Control of Heterogeneous Multiagent Systems With Intrinsic Nonlinear Dynamics in Noisy and Time-Delayed...

Area of Science:

• Control Systems Engineering
• Nonlinear Dynamics
• Stochastic Systems

Background:

• Heterogeneous multiagent systems (MASs) exhibit complex nonlinear dynamics.
• Real-world applications involve noisy and time-delayed environments, complicating control.
• Existing control strategies often struggle with intrinsic nonlinearities and stochastic disturbances.

Purpose of the Study:

• To develop a robust tracking control strategy for heterogeneous MASs with nonlinear dynamics.
• To address challenges posed by multiplicative noise and time-varying delays.
• To establish theoretical conditions for reliable tracking performance.

Main Methods:

• A novel stability criterion for nonlinear stochastic delay systems was developed using Lyapunov-Krasovskii functionals.
• Sufficient conditions for mean square (m.s.) and almost sure (a.s.) tracking were derived.
• Conditions were simplified for integrator heterogeneous MASs, including a delay-free case.

Main Results:

• The proposed stability criterion facilitates the design of effective tracking controllers.
• Derived conditions guarantee m.s. and a.s. tracking for the complex MASs.
• Explicit scalar inequalities were obtained for integrator MASs, clarifying noise and control gain relationships.

Conclusions:

• The developed control protocol effectively manages tracking in heterogeneous MASs with nonlinear dynamics, noise, and delays.
• The theoretical framework provides a foundation for designing robust control systems in challenging environments.
• Simulation results confirm the practical efficacy of the proposed control approach.