Time-space ARX modeling and predictive control for distributed parameter system
分布参数系统的时空ARX建模及预测控制

For a class of distributed parameter systems described by parabolic partial differential equations (PDEs), we investigate their modeling and control by using the input-output data. Based on the characteristics of parabolic PDEs, the Karhunen-Loève (K-L) decomposition method is applied to extract the dominant spatial basis functions of the system, which is in turn employed for executing the time-space decomposition. After the time-space decomposition, a temporal auto-regresive model with external input (ARX) model is identified by using the temporal coefficients obtained from the decomposition along with the excitation input signal. A generalized predictive controller is developed based on this ARX model. Simulation results show that this control method results in desirable performances for a distributed parameter system.