Adaptive particle swarm optimization with PD controller

The paper develops an adaptive particle swarm optimization(PSO) based on its simplification. With the hope to prompt its global optimization performance, the improved menthod introduces a PD controller into the architecture of the standard PSO(SPSO-PD). The PD controller can control the particle dynamics, and prompt the particles to respond to the change of their exemplars correctly and rapidly, further to surpass the limit of their exemplars with more chances, which greatly contributes to a successful global search. The proposed SPSO-PD was applied to some well-known benchmarks and compared with the standard PSO. The relative experimental results show SPSO-PD performs better than SPSO on the complex optimization functions.