A novel MOPSO-based ADRC controller for multi-objective control strategy of the high-precision tracking system

In this paper, a novel parameters tuning method based on the multi-objective adaptive evolutionary particle swarm optimization (MOAEPSO) algorithm is proposed for the active disturbance rejection control (ADRC) strategy of the high-precision tracking system (HTS). In the HTS, the conflict exists between disturbance rejection ability and dynamic tracking ability, thereby it is necessary to select reasonable controller parameters to solve this problem. To obtain an optimal trade-off between disturbance rejection ability and dynamic tracking ability, the proposed method transforms the parameters tuning problem into a multi-objective optimization problem. Besides that, different from the conventional MOPSO algorithm, because of particle swarm variation and novel nonlinear objective functions, the MOAEPSO algorithm obtains faster algorithm convergence speed and global optimal solution search capability. Through extensive simulation analysis and experimental verification, compared with the ADRC of the conventional parameters tuning method, the proposed method has better control performance, which proves its effectiveness and superiority.