Robust Coordination of Small UAVs for Vision‐Based Target Tracking Using Output‐Feedback MPC with MHE

Abstract

This chapter highlights solutions for the robust, coordinated control of multi-agent systems that represent the state of the art, where a special emphasis is placed on output-feedback approaches. It presents a novel, output-feedback approach that both enables the robust, optimal control of smaller multi-agent systems with nonlinear dynamics and is suitable for real-world implementation, as corroborated by real-time, high-fidelity simulations. The chapter shows that the output-feedback model predictive control (MPC)/moving horizon estimation (MHE) approach is a viable approach for addressing high-dimensional, very nonlinear (nonconvex) problems involving the robust coordination of mobile robots under realistic settings. It describes the dynamics and measurement model that compose the problem of vision-based target tracking. The chapter demonstrates the effectiveness of the MPC/MHE control approach to the problem of two fixed-wing unmanned aerial vehicles (UAVs) performing vision-based target tracking of a moving ground vehicle.