Research on Predictive Control of Reactor Temperature Based on Chaotic Particle Swarm Optimization Algorithm
As a core production vessel in chemical industry,the optimization of temperature control of reactor plays an important role in chemical production field.Aiming at the difficult problem of reactor temperature control,a reactor temperature predictive control strategy based on Tent mapping chaotic particle swarm optimization(CPSO)algorithm to optimize dynamic matrix control(DMC)-proportional integral differential(PID)is proposed.Since it is difficult to select better parameters for DMC,the CPSO algorithm with Tent mapping is utilized to improve the speed of dynamic matrix parameter optimization.Through tests,and the comparison and analysis with the conventional PID and DMC-PID control,the CPSO-DMC-PID series control based on the Tent mapping has better control accuracy and response speed for the temperature control system and can reduce the amount of overshooting significantly.The control strategy has certain reference significance for the predictive control research of reactor temperature.
ReactorChaotic particle swarm optimization(CPSO)Dynamic matrix control(DMC)Proportional integral differential(PID)Cascade controlParameter optimization
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维普
