THE FEEDBACK REALIZATION OF THE GENERALIZED NYQUIST MULTIVARIABLE PREDICTIVE CONTROL AND ITS APPLICATION

In association with multivariable frequency-design techniques, Cloud and Kouvaritakis (1988) presented a framework for the multivariable generalization of predictive self-tuning control. On the basis of it, this article proposes a closed-feedback structure of multivariable predictive control system projected onto a characteristic frame, from which the information required to assess stability can be obtained. Furthermore, the computational load and the memory storage for implementation can be effectively reduced. In order to verify the validity of the method, the simulation for predictive control algorithm to design the multivariable temperature control system of a 200 MW thermal power unit made by the People's Republic of China is illustrated. The results show that the control system has good control performance.