According to the characteristics of the large time delay,nonlinearity and the great inertia of temperature control system in biomass pyrolysis reactor,a two-degree-of-freedom Smith internal model controller based on f...According to the characteristics of the large time delay,nonlinearity and the great inertia of temperature control system in biomass pyrolysis reactor,a two-degree-of-freedom Smith internal model controller based on fuzzy control is proposed.Firstly,the mathematical model of the temperature control system is established by using the step response method,and then the two-degree-of-freedom Smith internal model controller is designed,and the good tracking performance and disturbance suppression performance can be obtained by designing the set value tracking controller and interference rejection capability.Secondly,the fuzzy control algorithm is used to realize the on-line tuning of the control parameters of the two-degree-of-freedom Smith internal model algorithm.The simulation results show that,compared with the traditional internal model control,fuzzy internal model PID control and two-degree-of-freedom Smith internal model control,the algorithm proposed in this paper improves the influence of lag time on the control system,realizes the separation control of set point tracking and anti-jamming performance and the self-tuning of control parameters,and improves the control performance of the system.展开更多
The long time-delay often exists in industrial process. In order to overcome the big overshoot and long regulating time of the long time-delay system control, a new fuzzy self-adaptive PI-Smith control method is propo...The long time-delay often exists in industrial process. In order to overcome the big overshoot and long regulating time of the long time-delay system control, a new fuzzy self-adaptive PI-Smith control method is proposed. This method combines the Smith predictive control with fuzzy self-adaptive proportional-integral (PI) control. The traditional proportional-integral-derivative (PID) controller in Smith predictive control is replaced by fuzzy PI controller which utilizes the principle of fuzzy control to tune parameters of PI controller on-line. The results of simulation for electric furnace show that the method has the advantages of shortening regulating time, no overshoot, no steady-state error, excellent control accuracy, and good adaptive ability to the change of system model.展开更多
基金financial support was given by Tianjin Technical Expert Project(19JCTPJC59300)
文摘According to the characteristics of the large time delay,nonlinearity and the great inertia of temperature control system in biomass pyrolysis reactor,a two-degree-of-freedom Smith internal model controller based on fuzzy control is proposed.Firstly,the mathematical model of the temperature control system is established by using the step response method,and then the two-degree-of-freedom Smith internal model controller is designed,and the good tracking performance and disturbance suppression performance can be obtained by designing the set value tracking controller and interference rejection capability.Secondly,the fuzzy control algorithm is used to realize the on-line tuning of the control parameters of the two-degree-of-freedom Smith internal model algorithm.The simulation results show that,compared with the traditional internal model control,fuzzy internal model PID control and two-degree-of-freedom Smith internal model control,the algorithm proposed in this paper improves the influence of lag time on the control system,realizes the separation control of set point tracking and anti-jamming performance and the self-tuning of control parameters,and improves the control performance of the system.
基金supported by the Natural Science Foundation of Shaanxi Province (2007F18)the Scientific Research Program of Shaanxi Provincial Education Department (2010JC19)
文摘The long time-delay often exists in industrial process. In order to overcome the big overshoot and long regulating time of the long time-delay system control, a new fuzzy self-adaptive PI-Smith control method is proposed. This method combines the Smith predictive control with fuzzy self-adaptive proportional-integral (PI) control. The traditional proportional-integral-derivative (PID) controller in Smith predictive control is replaced by fuzzy PI controller which utilizes the principle of fuzzy control to tune parameters of PI controller on-line. The results of simulation for electric furnace show that the method has the advantages of shortening regulating time, no overshoot, no steady-state error, excellent control accuracy, and good adaptive ability to the change of system model.