Optimization-Based Predictive G &C Method

This chapter focuses on the design of predictive control-based optimization method for addressing missile interception problems. Due to the nonlinearity or inherent limitations of the missile-target dynamics, it is often hard to design control algorithms with high accuracy and efficiency. To tackle this issue, a pseudo-spectral nonlinear receding horizon control (RHPC) scheme is developed and used to generate optimal control commands. The problem of state estimation in the presence of measurement noise is also solved by the Moving Horizon Estimation (MHE) algorithm. Since the RHPC and MHE algorithms solve the optimal open-loop control problem online at each sampling time, their associated computational cost may be high. Therefore, recently proposed sensitivity-based nonlinear programming (NLP) algorithms are used and integrated into the optimization framework to reduce the computational cost of the optimization process. Simulations and numerical analysis demonstrate the effectiveness of the proposed scheme.