Design of Unmanned Swarm Combat Control Strategy Based on Lanchester Equations

Unmanned swarm confrontation is a complex dynamic process characterized by multi-agent involvement, time-sensitiveness and prominent non-linearity. In the context of a vigorous combat, it is essential to design adaptive control strategy and utilize limited resources of the swarm efficiently to prevail. This paper adopt Lanchester equations to describe the dynamic process of unmanned swarm combat and established a mathematical model for the complicated course of a combat and analyzed the stabilizability and observability of the dynamic process utilizing control theories. For the realization of an adaptive combat strategy where feedback of scenario awareness is exploited, optimal control theory and state-dependent Riccati equation were combined to linearize the expectation points as the combat proceeded, arriving at an optimal adaptive control strategy which followed an expected track of victory, enabling the unmanned swarm to adapt according to the variations of the enemy. Finally, mathematical simulations were conducted under various combat configurations, proving the adaptive mechanism worthy of securing a win for unmanned swarm in confrontations, rendering the methodology proposed by the paper pertinent for reference as a meritorious theory in the field of unmanned swarm confrontation tactic operation research.