Estimation of Process Derivatives in On-line Optimization Control: Current and Future Challenges

摘要

Estimating process derivatives in an on-line optimization scheme has been widely addressed in last few decades. This is due to the fact that earlier methods have encountered major drawbacks in the past. This paper reviews these methods and investigates a new method based on Genetic Algorithms (GA’s) for estimating these derivatives within the well-known Integrated System Optimization and parameter Estimation (ISOPE) algorithm. A comparison study is given at the end using simulations on a Continuous Stirred Tank Reactor (CSTR) system. The discussion of the results shows the advantages and disadvantages of each method.