Distributed Fuzzy Adaptive Output-Feedback Control of Unknown Nonlinear Multiagent Systems in Strict-Feedback Form

Area of Science:

• Control Systems Engineering
• Robotics
• Artificial Intelligence

Background:

• Cooperative tracking control is crucial for multiagent systems (MAS).
• Heterogeneous MAS with unknown dynamics present significant control challenges.
• Leader-following architectures are common in distributed control applications.

Purpose of the Study:

• To develop a fully distributed output-feedback control algorithm for heterogeneous MAS.
• To achieve cooperative tracking control in a leader-following configuration.
• To ensure prescribed performance and signal boundedness in closed-loop systems.

Main Methods:

• Utilized fuzzy-logic systems for approximating unknown dynamics.
• Implemented input filters and constraint-handling schemes.
• Designed a distributed output-feedback control strategy using relative output measurements.

Main Results:

• Achieved output synchronization for heterogeneous multiagent systems.
• Guaranteed boundedness of all signals within the closed-loop system.
• Demonstrated a simplified control design avoiding explosion of complexity.

Conclusions:

• The proposed algorithm effectively addresses cooperative tracking for MAS with unknown strict-feedback dynamics.
• The control design is simple, relying only on relative outputs and avoiding complex techniques.
• Simulation results validate the theoretical findings and the algorithm's performance.