Multi-modeling for nonlinear distributed parameter processes using spatio-temporal kernel

Many industrial processes are nonlinear distributed parameter systems (DPS) that have significant spatio-temporal dynamics. Due to different production and working conditions, they often need to work at a large operating range with multiple working points. However, direct global modeling and persistently exciting experiment in a large working region are very costly in many cases. Complex spatio-temporal coupling and infinite-dimensional nature make the problem more difficult. In this study, a kernel based spatio-temporal multi-modeling approach is proposed for the nonlinear DPS with multiple working points. The effectiveness of the proposed modeling approach is verified by simulations.