Fractional-Order PID and Active Disturbance Rejection Control with Tuning Parameter Optimization for Induction Heating

Abstract

Induction heating systems are characterized by model uncertainty, nonlinearity, and external disturbances, and the control accuracy of the system directly affects the performance of the heated workpiece. In order to improve the temperature control accuracy and anti-interference performance of induction heating systems, this paper proposes a composite control strategy combining fractional-order PID (FOPID) and active disturbance rejection control (ADRC). Meanwhile, for the problem of too many controller tuning parameters, an improved quantum behavior particle swarm optimization (QPSO) algorithm is used to transform the nine parameters to be tuned in fractional-order PID active disturbance rejection control (FOPID-ADRC) into a minimization value optimization problem for solving. The simulation results show that the FOPID-ADRC controller improves the anti-interference capability and control accuracy of the temperature control system, and the improved QPSO algorithm has better global search capability and local optimal adaptation value.