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Extended kalman filter‐based nonlinear model predictive control of a continuous KCl‐NaCl crystallizer
Author(s) -
Tadayyon Abdulsamad,
Rohani Sohrab
Publication year - 2001
Publication title -
the canadian journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.404
H-Index - 67
eISSN - 1939-019X
pISSN - 0008-4034
DOI - 10.1002/cjce.5450790208
Subject(s) - control theory (sociology) , extended kalman filter , controller (irrigation) , kalman filter , model predictive control , nonlinear system , matrix (chemical analysis) , filter (signal processing) , engineering , mathematics , computer science , chemistry , control (management) , physics , chromatography , statistics , quantum mechanics , artificial intelligence , electrical engineering , agronomy , biology
An extended Kalman filter (EKF)‐based nonlinear quadratic dynamic matrix control (EQDMC) for an evaporative cooling draft‐tube baffled (DTB) KCl crystallizer is developed. The controller is used to maintain the productivity, crystal mean size and impurity of crystals. Since these controlled variables are not directly measurable, the EKF is used to estimate them. The nonlinear controller is a combination of an extended linear dynamic matrix control (EDMC) and the quadratic dynamic matrix control (QDMC). This combination provided good control of the system despite the process nonlinearity, constraints, and inadequate reliable online measurement of the controlled variables. The performance of the controller in the presence of plant/model mismatch, disturbance, wrong estimation and simultaneous step changes in the controller setpoints is discussed.