On Consensus Control of Uncertain Multiagent Systems Based on Two Types of Interval Observers

Area of Science:

• Control Theory
• Systems Engineering
• Robotics

Background:

• Multiagent systems often face challenges due to model uncertainties and parameter variations.
• Achieving robust consensus is critical for coordinated behavior in distributed systems.
• Existing methods may impose constraints that limit design flexibility.

Purpose of the Study:

• To investigate the multiagent robust consensus problem under interval-bounded model uncertainties.
• To develop novel methods for robust consensus that enhance design freedom.
• To ensure state values remain within specified bounds and errors converge to zero.

Main Methods:

• Construction of upper and lower dynamic systems based on positive system theory.
• Application of the Lyapunov stability principle to guarantee error convergence.
• Development of local and neighborhood protocols using novel parametric matrices.

Main Results:

• Guaranteed bounds for state values using constructed dynamic systems.
• Convergence of observation and consensus errors to zero, enabling state reconstruction.
• Successful achievement of robust consensus under model uncertainties.
• Elimination of the Metzler constraint on the error matrix.

Conclusions:

• The proposed methods effectively solve the multiagent robust consensus problem under model uncertainties.
• The approach enhances design flexibility by introducing novel parametric matrices.
• The theoretical results are validated through numerical simulations, confirming the effectiveness of the protocols.