Abstract: The accurate control of the annealing temperature is a multiple-input-multiple-output (MIMO) control problem in vacuum annealing furnace. In order to control the annealing temperature accurately, the second order plus time delay models of every temperature region are identified based on the date gathered from the vacuum annealing furnace scene. A new predictive function decoupling control algorithm for the second order plus time delay MIMO systems is proposed. This algorithm can decompose the decoupling control problem of an MIMO system into predictive function controls (PFC) of several single-input-single-output (SISO) systems. The decentralized optimization method is adopted to deal with coupled variables instead of the whole optimization. Utilizing the characteristics of PFC, the introduced base functions increase freedom of design, reduce the online calculation amount significantly, and thus efficiently simplify parameter design and calculation load. Then, an analytical control equation can be derived from the new PFC algorithm. The new PFC algorithm can solve predictive function decoupling control for the second order plus time delay MIMO systems. The simulation results show that the proposed control system is better than the traditional or modified PID control system. The proposed control system is applied to the control of annealing temperature in practical vacuum annealing furnace ( 2 100×2 100), which is efficient and effective.

Key words: Modeling, Multiple-input-multiple-output system, Predictive function decoupling control, Vacuum annealing temperature