GPC parameter tuning of multivariable VAV air conditioning system based on population attenuation BSO algorithm

Aiming at the control difficulties of variable air volume (VAV) air conditioning system, such as large lag and multivariable coupling, a parameter tuning method of multivariable VAV air conditioning system generalized predictive controller (GPC) based on population attenuation beetle swarm optimization (BSO) algorithm is proposed. Firstly, the weight parameters and learning factors of BSO are dynamically selected, and the population attenuation function and event trigger (ET) conditions are reasonably selected to obtain better optimization performance. Secondly, a novel GPC parameter tuning method based on population attenuation BSO algorithm is proposed, which can improve the time-domain performance of the system. Finally, simulation and hardware in the loop experiments are carried out. The results show that the method which proposed by this paper is effective.