Integrated optimization of guidance and control parameters in a dual-spin ying vehicle

Abstract

In this paper, integrated optimization of the guidance and control parameters of a dual-spin ying vehicle is presented. The vehicle is composed of two parts: a freerolling aft body, including the engine and the stabilizing fins, and a roll-isolated front body, including all necessary guidance and control equipment, such as onboard computer, control fins, and an inertial navigation system. After developing the governing equations of motion, control loops and the guidance algorithm are constructed. Controllers are designed for two operating points and the guidance algorithm consists of a midcourse and a terminal phase. In midcourse phase, a virtual target, located on the nominal trajectory, is followed using proportional navigation law; while, in the terminal phase, the vehicle is guided toward the real target. A new nonlinear saturation function is defined in order to saturate the maximum lateral acceleration command as a function of dynamic pressure. Finally, the integrated tuning of 23 guidance and control parameters is formulated as an optimization problem. The optimization problem is solved using a metaheuristic algorithm, called tabu continuous ant colony system. The performance of the optimized guidance and control system is evaluated using Monte Carlo simulations based on the complete nonlinear model.