A Measurement Method about the Key Parameters of Nonlinear System Based on Generalized Predictive Control

As modern industrial process’ requirement for control, metering, energy efficiency and operational reliability are getting higher and higher, the accuracy requirement for measurement instruments is getting higher too. However, because the complexity and uncertainty of production systems in industrial process have led to the difficulties of process parameter measurement, there exists many important process parameters which can not be measured by sensor or process measurement instrument directly. This paper employs the new generalized predictive control algorithm to realize simulation and optimization parameters of complex system, solving the problem of low accuracy and low speed in simulating and on-line parameter estimation. Through indirect measurement and use of other easily-obtained measurement information, it can achieve the soft-sensor of key parameters of complex system, which has great significance for realizing the closed-loop control and optimization operation of the complex industrial system.