Research on optimization control method for cooperative coverage time of multiple smoke grenades based on model predictive control

Abstract

In dynamic electro-optical confrontation environments that require real-time target concealment, ensuring the coordinated control of multiple obscuration agents remains a challenging problem in modern control systems. Especially under visiblelight reconnaissance, infrared imaging, and laser ranging or guidance conditions, the continuity and effectiveness of smoke-based optical obscuration directly affect target survivability. This paper proposes an intelligent cooperative control strategy based on Model Predictive Control (MPC) to optimize the deployment timing and detonation delay of multiple smoke grenades for target shielding. By modeling the motion dynamics, detonation process, and optical obscuration states of the smoke grenades, a nonlinear state-space system is constructed. The proposed framework considers the attenuation effect of smoke clouds on electro-optical and infrared observation, and formulates a multi-objective cost function to maximize cumulative coverage time while minimizing redundant and discontinuous coverage. These objectives are solved under temporal and spatial constraints via a rolling optimization framework. Simulation results demonstrate that the proposed MPC-based method achieves superior performance in terms of optical occlusion continuity, robustness to disturbances, and online solution efficiency compared with traditional methods. The results indicate that the proposed method can effectively improve visible-light and infrared concealment performance in dynamic observation scenarios. This research provides a real-time deployable and scalable solution for multi-agent cooperative optical obscuration control in time-sensitive missions.