The reality is a bit more complex, as it turns out.Case study confirms that, on the basis of the proposed model and recursive algorithms, the dynamic and static characteristics of soft sensor system can be described efficiently, and the primary variables are ensured to be estimated accurately. His research interest includes model predictive control, multirate soft sensor and control in chemical industry, online real-time optimization of chemical process, simultaneous process and control design, the bypass optimal control of heat exchanger networks, and margin analysis based on dynamic model.Xionglin Luo is a Professor in the Research Institute of Automation of the China University of Petroleum. The uniform convergence for dynamic model parameter and the existence of estimation deviations for static model parameters are proved for time-invariant soft sensor system.
The parameters of time-variant soft sensor system would be boundedly convergent. He and his group have published a large number of technical papers and two monographs on process control and process system engineering.
Soft sensor technology is an important means to estimate important process variables in real-time.