UAV swarm formation reconfiguration control based on variable-stepsize MPC-APCMPIO algorithm

For a complex operational environment, to actualize safe obstacle avoidance and collision avoidance, a swarm must be capable of autonomous formation reconfiguration. First, this paper introduces the basic pigeon-inspired optimization (PIO) algorithm, and establishes the unmanned aerial vehicle motion model and the virtual leader swarm formation control structure. Then, given the above knowledge, the basic error objective function of a UAV swarm, obstacle avoidance objective function, and collision avoidance objective function are devised based on the variable-stepsize model predictive control technique. Next, the adaptive perception Cauchy mutation PIO algorithm is proposed by introducing the Cauchy mutation operator, adaptive weight factor, and roulette wheel selection into the basic PIO. This algorithm is used to optimally solve the abovementioned swarm objective functions. Ultimately, a set of comparative simulations are performed to verify the effectiveness and reliability of the proposed algorithm.