According to the error between the model predictive output and the future expected output, ILPC carries out an iterative learning and amending process on the current and the future control input vector, namely performs "forecast, iterative amendment, forecast again, iterative amendment again" repeatedly in the iterative domain. This paper gives a fast high-precision temperature control system's structure, characteristics and realization method. CARI model and the improved generalized predictive control method are used to improve the control precision of the system, and shorten the response time. The quick high precision temperature control system's structure and realization method are given, and according to the requirements of the task, the existing predictive control algorithm has been improved. Through the experiment, its temperature predictive control system's design scheme and realization method is proved to be reasonable and feasible. It can meet the demands for the expected temperature control.
