Three-Dimensional Active Defendin Control Method Based on Heuristic Dynamic Programming

This paper addresses the multi-party optimal control problem of real-time nonlinear systems in the active defense process of the aircraft and defending missiles, proposing a Dual-Action-Dependent Heuristic Dynamic Programming Algorithm based on Three-Dimensional Zero-Control Miss Distance (DADHDP). The algorithm combines approximate dynamic programming with the Actor-Critic framework in reinforcement learning, effectively approximating the infinite-horizon optimal control problem of complex nonlinear systems by iterating dynamic adversarial information in real-time. Compared with traditional methods, DADHDP introduces three-dimensional zero-control miss distance, an Actor network structure with embedded saturation constraints, and a non-quadratic cost functional in the algorithm design, which maintains system stability under control input limitations (such as saturation constraints), enhances solution efficiency, and effectively avoids control failure due to constraint violations in traditional methods.