Considering some characteristics of large-scale standing quench furnace, such as great heat inertia, evident time lag, strong coupling influence, hard to establish exact mathematical models of plant and etc, an artifi...Considering some characteristics of large-scale standing quench furnace, such as great heat inertia, evident time lag, strong coupling influence, hard to establish exact mathematical models of plant and etc, an artificial intelligent fuzzy control algorithm is put forward in this paper. Through adjusting the on-off ratio of electric heating elements, the temperature in furnace is controlled accurately. This paper describes structure and qualities of the large-scale standing quench furnace briefly, introduces constitution of control system, and expounds principle and implementation of intelligent control algorithm. The applied results prove that the intelligent control system can completely satisfy the technological requirements. Namely, it can realize fast increasing temperature with a little overshoot, exact holding temperature, and well-distributed temperature in quench furnace. It has raised the output and quality of aluminum material, and brought the outstanding economic and social benefits.展开更多
Due to the large uncertainty in the municipal solid waste incineration(MSWI)process,the furnace temperature of the MSWI process is difficult to control and the controller is updated frequently.To improve the accuracy ...Due to the large uncertainty in the municipal solid waste incineration(MSWI)process,the furnace temperature of the MSWI process is difficult to control and the controller is updated frequently.To improve the accuracy and reduce the number of controller updates,a novel event-triggered control method based correntropy self-organizing TS fuzzy neural network(ETCSTSFNN)is proposed.Firstly,the neurons of the rule layer are grown or pruned adaptively based on activation intensity and control error to meet the dynamic change of the actual operating condition.Meanwhile,the performance index is designed based on the correntropy of tracking errors,and the parameters of the controller are adjusted by gradient descent algorithm.Secondly,a fixed threshold event-triggered condition is designed to determine whether the current controller is updated or not.The stability of the control system is proved based on the Lyapunov stability theory.Finally,the furnace temperature control experiments are conducted based on the actual data of a municipal solid waste incineration plant in Beijing.The experimental results show that the proposed ET-CSTSFNN controller shows a better control performance,which can reduce the number of the controller update significantly while achieving accurate furnace temperature control compared with other traditional control methods.展开更多
基金Supported by The National Natural Science Foundation of China (No. 59835170).
文摘Considering some characteristics of large-scale standing quench furnace, such as great heat inertia, evident time lag, strong coupling influence, hard to establish exact mathematical models of plant and etc, an artificial intelligent fuzzy control algorithm is put forward in this paper. Through adjusting the on-off ratio of electric heating elements, the temperature in furnace is controlled accurately. This paper describes structure and qualities of the large-scale standing quench furnace briefly, introduces constitution of control system, and expounds principle and implementation of intelligent control algorithm. The applied results prove that the intelligent control system can completely satisfy the technological requirements. Namely, it can realize fast increasing temperature with a little overshoot, exact holding temperature, and well-distributed temperature in quench furnace. It has raised the output and quality of aluminum material, and brought the outstanding economic and social benefits.
基金supported by the National National Science Foundation of China(Grant Nos.62073006 and 62021003)Beijing Natural Science Foundation(Grant No.4212032)。
文摘Due to the large uncertainty in the municipal solid waste incineration(MSWI)process,the furnace temperature of the MSWI process is difficult to control and the controller is updated frequently.To improve the accuracy and reduce the number of controller updates,a novel event-triggered control method based correntropy self-organizing TS fuzzy neural network(ETCSTSFNN)is proposed.Firstly,the neurons of the rule layer are grown or pruned adaptively based on activation intensity and control error to meet the dynamic change of the actual operating condition.Meanwhile,the performance index is designed based on the correntropy of tracking errors,and the parameters of the controller are adjusted by gradient descent algorithm.Secondly,a fixed threshold event-triggered condition is designed to determine whether the current controller is updated or not.The stability of the control system is proved based on the Lyapunov stability theory.Finally,the furnace temperature control experiments are conducted based on the actual data of a municipal solid waste incineration plant in Beijing.The experimental results show that the proposed ET-CSTSFNN controller shows a better control performance,which can reduce the number of the controller update significantly while achieving accurate furnace temperature control compared with other traditional control methods.
