Output Feedback

Output feedback control aims to design controllers that stabilize or regulate a system's behavior using only partial or noisy measurements of its output, rather than its full internal state. Current research emphasizes developing robust and efficient output feedback controllers, particularly focusing on data-driven approaches, linear and neural network-based methods, and Lyapunov stability analysis to guarantee performance and safety. These advancements are significant for applications requiring limited sensing, such as robotics and multi-agent systems, where obtaining full state information is impractical or impossible, enabling more reliable and efficient control in real-world scenarios.