Multiple-constraint cooperative guidance based on two-stage sequential convex programming

Abstract

An improved approach is presented in this paper to implement highly constrained cooperative guidance to attack a stationary target. The problem with time-varying Proportional Navigation (PN) gain is first formulated as a nonlinear optimal control problem, which is difficult to solve due to the existence of nonlinear kinematics and nonconvex constraints. After convexification treatments and discretization, the solution to the original problem can be approximately obtained by solving a sequence of Second-Order Cone Programming (SOCP) problems, which can be readily solved by state-of-the-art Interior-Point Methods (IPMs). To mitigate the sensibility of the algorithm on the user-provided initial profile, a Two-Stage Sequential Convex Programming (TSSCP) method is presented in detail. Furthermore, numerical simulations under different mission scenarios are conducted to show the superiority of the proposed method in solving the cooperative guidance problem. The research indicated that the TSSCP method is more tractable and reliable than the traditional methods and has great potential for real-time processing and on-board implementation.