Shrinking Horizon MPC Strategy for Impact Time and Angle Guidance

Abstract

In this paper, a new model predictive control (MPC) strategy is proposed for the impact-time-and-angle guidance problem subject to input limits. The nonlinear dynamic model of the guidance system is linearized by first-order Taylor-series expansions, resulting in an optimization problem that can be effectively solved via convex programming solvers. The prediction and control horizons of the MPC strategy are adaptively shrinking to cover the whole mission duration. Therefore, the terminal impact time and angle constraints can be integrated into the optimization procedure even during the early guidance phase. The robustness, control-effort optimality, and computational simplicity of the new MPC strategy are demonstrated via numerical simulations.