Predictive Control in Process Engineering

PrefaceNotation and AbbreviationsINTRODUCTION TO PREDICTIVE CONTROLPreview of Predictive ControlManipulated, Reference, and Controlled SignalsCost Function of Predictive ControlReference Signal and Disturbance Preview, Receding Horizon, One-Step-Ahead, and Long-Range Optimal ControlFree and Forced Responses of the Predicted Controlled VariableMinimization of the Cost FunctionSimple Tuning Rules of Predictive ControlControl of Different Linear SISO ProcessesControl of Different Linear MIMO ProcessesControl of Nonlinear ProcessesControl under ConstraintsRobustnessSummaryLINEAR SISO MODEL DESCRIPTIONSNonparametric System DescriptionPulse-Transfer Function ModelDiscrete-Time State Space ModelSummaryPREDICTIVE ON-OFF CONTROLClassical On-Off Control by Means of Relay CharacteristicsPredictive Set Point ControlPredictive Start-Up Control at a Reference Signal ChangePredictive Gap ControlCase Study: Temperature Control of an Electrical Heat ExchangerSummaryGENERALIZED PREDICTIVE CONTROL OF LINEAR SISO PROCESSESControl Algorithm without ConstraintsLinear Polynomial Form of Unconstrained GPCTuning the Controller ParametersBlocking and Coincidence Points TechniquesMeasured Disturbance Feed-Forward CompensationControl Algorithm with ConstraintsExtended GPC with Terminal MethodsSummaryPREDICTIVE PID CONTROL ALGORITHMSPredictive PI(D) Control StructurePredictive PI Control AlgorithmPredictive PID Control AlgorithmEquivalence between the Predictive PI(D) Algorithm and the Generalized Predictive Control AlgorithmTuning of Predictive PI(D) AlgorithmsRobustifying Effects Applied for Predictive PI(D) Control AlgorithmsSummaryPREDICTIVE CONTROL OF MULTIVARIABLE PROCESSESModel DescriptionsPredictive EquationsThe Control AlgorithmPolynomial Form of the Controller (without Matrix Inversion)Pairing of the Controlled and the Manipulated VariablesScaling of the Controlled and the Manipulated VariablesTuningDecoupling ControlCase Study: Control of a Distillation ColumnSummaryESTIMATION OF THE

Robert Haber had studied electrical engineering at the Budapest University of Technology, where he also has received the Ph.D. in control theory. He is currently head of the Laboratory for Process Automation in the Faculty of Process Engineering, Energy and Mechanical Systems at the Cologne University of Applied Sciences. His research interests include process automation, experimental identification, model based control and intelligent process data analysis.Ruth Bars graduated at the Electrical Engineering Faculty of the Budapest University of Technology, Hungary, where she has gained also her Ph.D. degree. Currently she is associate professor at the Department of Automation and Applied Informatics at the Budapest University of Technology and Economics. Her research interests are in predictive control and in developing new ways of control education. He was involved in IFAC International Federation of Automatic Control as Technical and Coordinating Committee chair.Ulrich Schmitz studied chemical engineering and plant design at the Cologne University of Applied Sciences. Prior to this he was working as an operator in a petrochemical plant. From 2001 till 2005 he was a scientific assistant at the Cologne University of Applied Sciences and took part in a cooperative doctoral project between the Universities in Cologne and Budapest. In 2007 he received his Ph.D. from the Budapest University of Technology and Economics. Since 2005 he has been working as an APC technologist for Shell Deutschland Oil at the Rhineland Refinery in Germany.