Model predictive control of vehicle maneuvers with guaranteed completion time and robust feasibility

A formulation for model predictive control is presented for application to vehicle maneuvering problems in which the target regions need not contain equilibrium points. Examples include a spacecraft rendezvous approach to a radial separation form the target and a UAV required to fly through several waypoints. Previous forms of MPC are not applicable to this class of problems because they are tailored to the control of plants about steady-state conditions. Mixed-integer linear programming is used to solve the trajectory optimizations, allowing the inclusion of non-convex avoidance constraints. Analytical proofs are given to show that the problem will always be completed in finite time and that, subject to initial feasibility, the optimization solved at each step will always be feasible in the presence of a bounded disturbance. The formulation is demonstrated in several simulations, including both aircraft and spacecraft, with extension to multiple vehicle programs.