摘要
An improved generalized predictive control algorithm is presented in thispaper by incorporating offline identification into online identification. Unlike the existinggeneralized predictive control algorithms, the proposed approach divides parameters of a predictivemodel into the time invariant and time-varying ones, which are treated respectively by offline andonline identification algorithms. Therefore, both the reliability and accuracy of the predictivemodel are improved. Two simulation examples of control of a fixed bed reactor show that this newalgorithm is not only reliable and stable in the case of uncertainties and abnormal disturbances,but also adaptable to slow time varying processes.
An improved generalized predictive control algorithm is presented in this paper by incorporating offline identification into onlie identification.Unlike the existing generalized predictive control algorithms.the proposed approach divides parameters of a predictive model into the time invariant and time-varying ones,which are treated respectively by offline and onlie identification algorithms.Therefore,both the reliability and accuracy of the predictive model are improved,Two simulation examples of control of a fixed bed reactor show that this new algorithm is not only reliable and stable in the case of uncertainties and abnormal distrubances,but also adaptable to slow time varying processes.
基金
Supported by the National Natural Science Foundation of China (No. 20206028) and the Qingdao Municipal Major Lab of Industry Information Technology.
