Reactor temperature predictive control algorithm research based on the PSO

Batch reactor have characteristics of large lag, non-linear and complex reaction process and it´s difficult to impose temperature control. Generalized predictive control (GPC) has predicted thinking and adaptive control characteristics, we can predict the output of the system in the future time. But the predictive control also have parameter identification problem, while particle swarm optimization (PSO) can optimize the predictive parameters, so as to achieve the purpose of precise control. Therefore, according to the reactor characteristics, this paper combine both of them to propose a predictive control algorithm based on Particle Swarm, first obtain the predictive parameters based on particle swarm, and then calculate the system control increment based on the identification of parameters of the system. The simulation results show that the algorithm can meet the reaction kettle temperature control requirements and implementation is simple and the control performance is good.