Hybrid evolutionary algorithm for synthesized optimal control problem for group of interacting robots

This paper considers the optimal control problem for a group of interacting robots. To solve the problem, a hybrid evolutionary algorithm is applied that consists of two popular evolutionary algorithms: particle swarm optimization and gray wolf optimizer. When solving the problem, we use the approach of synthesized optimal control. Initially, we make controlled objects stable in the state space with respect to a certain point. Then we look for coordinates of the stabilization points using the hybrid algorithm. Points should be located so that when switching stabilization points after each fixed time interval, the objects reach the control goal without violating the phase constraints with the optimal value of the quality criterion. © 2019 IEEE.