Consensus Control

Consensus control focuses on coordinating the behavior of multiple agents, such as robots or sensors, to achieve a common goal, often involving distributed algorithms and communication strategies. Current research emphasizes robust and efficient consensus algorithms under various constraints, including unknown dynamics, limited communication (event-triggered control), and noisy or unreliable information, often employing techniques like Gaussian process regression, Lyapunov stability analysis, and model predictive control. These advancements are crucial for improving the reliability and scalability of multi-agent systems in diverse applications, from cooperative robotics and distributed optimization to resilient sensor networks.