NMPC-Based Cooperative Strategy For A Target Pair To Lure Two Attackers Into Collision

TL;DR

This paper introduces a cooperative control strategy using nonlinear model predictive control (NMPC) and state estimation to help two targets lure attackers into collisions, enhancing their chances of survival in a game-theoretic scenario.

Contribution

The paper develops a novel NMPC-based cooperative strategy combined with EKF state estimation for targets to effectively lure attackers into collisions.

Findings

The strategy successfully increases target survival rates in simulations.

The NMPC approach effectively computes optimal control commands under constraints.

Theoretical analysis identifies initial conditions leading to target survival.

Abstract

This paper presents a cooperative target defense strategy using nonlinear model-predictive control (NMPC) framework for a two--targets two--attackers (2T2A) game. The 2T2A game consists of two attackers and two targets. Each attacker needs to capture a designated target individually. However, the two targets cooperate to lure the attackers into a collision. We assume that the cooperative target pair do not have perfect knowledge of the attacker states, and hence they estimate the attacker states using an extended Kalman filter (EKF). The NMPC scheme computes closed- loop optimal control commands for the targets while respecting imposed state and control constraints. Theoretical analysis is carried out to determine regions that will lead to the targets' survival, given the initial positions of the attacker and target agents. Numerical simulations are carried out to evaluate the performance of the proposed NMPC- based strategy for different scenarios.