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Practical plantwide process control

Practical plantwide process control. Sigurd Skogestad, NTNU Thailand, April 2014. Course description. This practically oriented course shows how to control your plant for improved stability and economics .

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Practical plantwide process control

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  1. Practicalplantwideprocesscontrol Sigurd Skogestad, NTNU Thailand, April 2014

  2. Course description • This practicallyorientedcourse shows how to controlyour plant for improvedstability and economics. • The approach is systematic and basedonthe latest methods, butuses a limitedamountofmathematics. • Youwilllearnwhat to control, how to structurethe loops and how to tune your PID controllers.

  3. Course Summary • Find active constraints + self-optimizing variables (CV1). (Economic optimal operation) • Locate throughput manipulator (TPM) • “Gas pedal” • Select stabilizing CV2 + tune regulatory loops • SIMC PID rules • Design supervisory layer (control CV1) • Multi-loop (PID) ++ • MPC Difficulties: • Optimization! May need to guess active constraints (CV1) • Handling of moving active constraints • Want to avoid reconfiguration of loops

  4. Part 1 (4h): Plantwide control Introductionto plantwidecontrol (whatshouldwereallycontrol?) Part 1.1 Introduction. • Objective: Putcontrollersonflowsheet (make P&ID) • Twomainobjectives for control: Longer-term economics (CV1) and shorter-term stability (CV2) • Regulatory(basic) and supervisory (advanced) controllayer Part 1.2 Optimal operation (economics) • Active constraints • Selectionofeconomiccontrolled variables (CV1). Self-optimizing variables. Part 1.3 -Inventory (level) controlstructure • Location ofthroughputmanipulator • Consistencyand radiatingrule Part 1.4 Structureofregulatorycontrollayer (PID) • Selectionofcontrolled variables (CV2) and pairingwithmanipulated variables (MV2) • Main rule: Control drifting variables and "pair close" Summary: Sigurd’srules for plantwidecontrol

  5. Part 2 (4h): PID tuning Part 2 (4h). PID controller tuning: It paysoff to be systematic! • DerivationSIMC PID tuning rules • Controller gain, Integral time, derivative time • Obtainingfirst-order plusdelaymodels • Open-loop stepresponse • From detailedmodel (half rule) • From closed-loop setpointresponse • Special topics • Integratingprocesses (levelcontrol) • Otherspecialprocesses and examples • Whendo weneed derivative action? • Near-optimalityof SIMC PID tuning rules • Non PID-control: Is there an advantage in using Smith Predictor? (No) • Examples

  6. Part 3 (1h) + Part 4 (3h): case studies Part 3 (1h). Advanced controllayer • Design basedon simple elements: • Ratio control • Cascadecontrol • Selectors • Input resetting (valvepositioncontrol) • Split range control • Decouplers(includingphsicallybased) • Whenshouldthese elements be used? • Whenuse MPC instead? Part 4 (3h). Case studies • Example: Distillationcolumncontrol • Example: Plantwidecontrolofcomplete plant Recycleprocesses: How to avoidsnowballing

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