Cooperative guidance laws against highly maneuvering target with impact time and angle

Abstract

To address the issue that multiple missiles intercepting a highly maneuvering target simultaneously with desired angles, a novel cooperative guidance law based on the decoupled model in the line-of-sight (LOS) and normal LOS direction is proposed in LOS frame. However, there is control coupling in the two directions of the cooperative guidance model. In this article, we first decouple the guidance model and then separately design estimation decouple cooperative guidance law in two directions based on the decoupled model. The guidance law component in the LOS direction is designed with the integral sliding mode control and multi-agent consensus theory, where the combining disturbance is compensated by an adaptively estimated term. The guidance law component in the normal LOS direction is designed based on nonsingular terminal sliding mode control with fast power reaching law, and a nonlinear disturbance observer is introduced to estimate the combining disturbance. Then, the finite time convergence of time-to-go and LOS angle is proved. Finally, numerical simulation results demonstrate the effectiveness and superiority of the proposed cooperative guidance law.

Cooperative optimal guidance of hypersonic glide vehicles by real-time optimization and deep learning

“…As a result, we formulate the COG problem as the following optimal control problem: Problem P0: minimize (9) subject to ( 1), ( 4)-( 8)…”

“…Based on the above discussion, Problem P0 is equivalently transformed into the following optimal control problem: Problem P1: minimize (9) subject to (4), ( 5), ( 15)-( 17)…”

“…where δ 2 R 6 is a constant vector and the inequality corresponds to each component in the vector. Now, an optimal control problem with linear system dynamics can be expressed as Problem P2: minimize (9) subject to (4), ( 5), ( 16), ( 17), ( 20), ( 21)…”

“…When the non-convex constraint is convexified, Problem P2 becomes the following optimal control problem with linear system dynamics and convex constraints: Problem P3: minimize (9) subject to (4), ( 5), ( 17), ( 20)À (22) It should be pointed out that the relaxation technique expands the feasible set of Problem P2. If the optimal solution of Problem P3 lies in the interior or on the upper plane of the solid truncated cone, the solution is meaningless since it is infeasible with respect to the control constraint in Problem P2.…”

“…Further, Zhao et al 5 considered information interaction and proposed two cooperative guidance algorithms based on the proportional navigation guidance law, one of which came into effect when the global information of the time-to-go was available, while another was designed for the situation when each vehicle can only collect information from its neighbors. Other methods related to optimal control, 6,7 sliding mode control, 8,9 and trajectory shaping 10 also showed good performance under some ideal assumptions, mainly including planar engagement, constant velocity, and ignorance of practical constraints. In recent years, with the rapid development on embedded computational capability, the second category, that is, numerical methods, has attracted much attention for solving guidance problems.…”