Dynamic control strategy of extended-range APU based on fuzzy PID optimized by CAHPSO

For the control of the working point switching process of the extended-range auxiliary power unit (APU), a dynamic control strategy for the extended-range APU was proposed by using the chaotic annealing hybrid particle swarm optimization (CAHPSO) algorithm to optimize the fuzzy proportional-integral-derivative (PID) control. This algorithm was used to combine chaos search and annealing mechanisms based on the standard particle swarm optimization (PSO) to enhance the global optimization ability, and optimize the fuzzy PID control parameters offline. In order to verify the effectiveness of the new control strategy, the APU system simulation model was established. The simulation results showed that during the processes of gradually switching from the warming-up point to the high load point, the new control strategy can make the APU shorten the stabilization time, the stabilization time for the three switching control processes of the working points was 2.92s, 2.88s, 2.79s, respectively; the new control strategy can make the APU reduce the speed overshoot rate, only when in the switching from the small load point to the middle load point, the speed overshoot rate was about 0.95% and there was no overshoot in other switching processes; the new control strategy can make the APU torque change smoothly, and the torque overshoot was only 0.16N•m when switching from the middle load point to the high load point, which achieved a good dynamic control effect. © 2021, Editorial Department of Journal of Aerospace Power. All right reserved.