Formation control with connectivity assurance for missile swarm: a natural co-evolutionary strategy approach

TL;DR

This paper introduces a novel metaheuristic co-evolutionary approach for missile swarm formation control that ensures connectivity and optimal convergence, addressing local optima and instability issues.

Contribution

It presents a new natural co-evolutionary strategy with model-based constraints and adaptive topology for formation control, validated both theoretically and experimentally.

Findings

Effective formation convergence demonstrated

Connectivity maintained under node failure

Feasibility of MDP-based iterative learning shown

Abstract

Formation control problem is one of the most concerned topics within the realm of swarm intelligence, which is usually solved by conventional mathematical approaches. In this paper, however, we presents a metaheuristic approach that leverages a natural co-evolutionary strategy to solve the formation control problem for a swarm of missiles. The missile swarm is modeled by a second-order system with heterogeneous reference target, and exponential error function is made to be the objective function such that the swarm converge to optimal equilibrium states satisfying certain formation requirements. Focusing on the issue of local optimum and unstable evolution, we incorporate a novel model-based policy constraint and a population adaptation strategies that greatly alleviates the performance degradation. With application of the Molloy-Reed criterion in the field of network communication, we developed an adaptive topology method that assure the connectivity under node failure and its effectiveness are validated both theoretically and experimentally. Experimental results valid the effectiveness of the proposed formation control approach. More significantly, we showed that it is feasible to treat generic formation control problem as Markov Decision Process(MDP) and solve it through iterative learning.