MIMO Controllability and Decentralized and Plantwide Control MIMO Controllability and Decentralized and Plantwide Control Sigurd Skogestad on Manfred Morari’s.

Slides:

Advertisements

Similar presentations

PROCESS CONTROL GROUP Dept. of Chemical Engineering NTNU, Trondheim.

Advertisements

1 Optimal operation and self-optimizing control Sigurd Skogestad NTNU, Trondheim Norway.

1 Plantwide control Control structure design for complete chemical plants Sigurd Skogestad Department of Chemical Engineering Norwegian University of Science.

Advanced Controls Technology An Industrial and Academic Perspective on Plantwide Control James J. Downs Eastman Chemical Company Sigurd Skogestad Norwegian.

1 CONTROLLED VARIABLE AND MEASUREMENT SELECTION Sigurd Skogestad Department of Chemical Engineering Norwegian University of Science and Technology (NTNU)

1 Outline Control structure design (plantwide control) A procedure for control structure design I Top Down Step 1: Degrees of freedom Step 2: Operational.

INTEGRATED DESIGN OF WASTEWATER TREATMENT PROCESSES USING MODEL PREDICTIVE CONTROL Mario Francisco, Pastora Vega University of Salamanca – Spain European.

Process and Tools Integration Introduction to Operability and Control of Integrated Plants 8. August 2005 Sten Bay Jørgensen CAPEC - Department of Chemical.

Certifying the robustness of model predictive controllers W. P. Heath and B. Lennox Control Systems Centre The University of Manchester.

Campus Curricula Committee Report 23 April 2015 l CCC Meetings »6 April 2015 »13 May 2015 l Committee Activity »2 Degree change requests (DC forms) Third.

1 Feedback: The simple and best solution. Applications to self-optimizing control and stabilization of new operating regimes Sigurd Skogestad Department.

GHGT-8 Self-Optimizing and Control Structure Design for a CO 2 Capturing Plant Mehdi Panahi, Mehdi Karimi, Sigurd Skogestad, Magne Hillestad, Hallvard.

1 Self-optimizing control: Simple implementation of optimal operation Sigurd Skogestad Department of Chemical Engineering Norwegian University of Science.

1 Coordinator MPC for maximization of plant throughput Elvira Marie B. Aske* &, Stig Strand & and Sigurd Skogestad* * Department of Chemical Engineering,

Offset Free Tracking with MPC under Uncertainty: Experimental Verification Audun Faanes * and Sigurd Skogestad † Department of Chemical Engineering Norwegian.

A Framework for Distributed Model Predictive Control

First African Control Conference, Cape Town, 04 December 2003

Top 10 Organizations of Thailand with Research Papers from September 2013 Derived from ISI Web of Knowledge by Mongkon Rayanakorn

1 Plantwide control: Towards a systematic procedure Sigurd Skogestad Department of Chemical Engineering Norwegian University of Science and Tecnology (NTNU)

PSE and PROCESS CONTROL

Outline Skogestad procedure for control structure design I Top Down

Temperature Controller A model predictive controller (MPC) based on the controller proposed by Muske and Rawlings (1993) is used. For the predictions we.

1 Structure of the process control system Benefits from MPC (Model Predictive Control) and RTO (Real Time Optimization) Sigurd Skogestad Department of.

Reinforcement Learning Control with Robust Stability Chuck Anderson, Matt Kretchmar, Department of Computer Science, Peter Young, Department of Electrical.

1 A Plantwide Control Procedure Applied to the HDA Process Antonio Araújo and Sigurd Skogestad Department of Chemical Engineering Norwegian University.

1 Practical plantwide process control. Extra Sigurd Skogestad, NTNU Thailand, April 2014.

1 E. S. Hori, Maximum Gain Rule Maximum Gain Rule for Selecting Controlled Variables Eduardo Shigueo Hori, Sigurd Skogestad Norwegian University of Science.

Light and the Electromagnetic Spectrum April 28, 2014.

1 Active constraint regions for economically optimal operation of distillation columns Sigurd Skogestad and Magnus G. Jacobsen Department of Chemical Engineering.

Implementation of Coordinator MPC on a Large-Scale Gas Plant

Sigurd Skogestad Department of Chemical Engineering

Integrated Process Networks: Nonlinear Control System Design for Optimality and Dynamic Performance Michael Baldea a,b and Prodromos Daoutidis a a University.

1 A SYSTEMATIC APPROACH TO PLANTWIDE CONTROL Sigurd Skogestad Department of Chemical Engineering Norwegian University of Science and Tecnology (NTNU) Trondheim,

1 Plantwide control: Towards a systematic procedure Sigurd Skogestad Department of Chemical Engineering Norwegian University of Science and Tecnology (NTNU)

1 Outline Control structure design (plantwide control) A procedure for control structure design I Top Down Step 1: Degrees of freedom Step 2: Operational.

1 Selv-optimaliserende regulering Anvendelser mot prosessindustrien, biologi og maratonløping Sigurd Skogestad Institutt for kjemisk prosessteknologi,

1 Decentralized control Sigurd Skogestad Department of Chemical Engineering Norwegian University of Science and Tecnology (NTNU) Trondheim, Norway.

1 From process control to business control: A systematic approach for CV-selection Sigurd Skogestad Department of Chemical Engineering Norwegian University.

1 Self-optimizing control From key performance indicators to control of biological systems Sigurd Skogestad Department of Chemical Engineering Norwegian.

1 ECONOMIC PLANTWIDE CONTROL: Control structure design for complete processing plants Sigurd Skogestad Department of Chemical Engineering Norwegian University.

1 PLANTWIDE CONTROL Identifying and switching between active constraints regions Sigurd Skogestad and Magnus G. Jacobsen Department of Chemical Engineering.

2/25/2001Industrial Process Control1 Dynamic Matrix Control - Introduction Developed at Shell in the mid 1970’s Evolved from representing process dynamics.

Robust Nonlinear Model Predictive Control using Volterra Models and the Structured Singular Value (  ) Rosendo Díaz-Mendoza and Hector Budman ADCHEM 2009.

1 II. Bottom-up Determine secondary controlled variables and structure (configuration) of control system (pairing) A good control configuration is insensitive.

1 Feedback: The simple and best solution. Applications to self-optimizing control and stabilization of new operating regimes Sigurd Skogestad Department.

1 A SYSTEMATIC APPROACH TO PLANTWIDE CONTROL ( ) Sigurd Skogestad Department of Chemical Engineering Norwegian University of Science and Tecnology.

Control Structure Design: New Developments and Future Directions Vinay Kariwala and Sigurd Skogestad Department of Chemical Engineering NTNU, Trondheim,

Inequality Constraints Lecture 7. Inequality Contraints (I) n A Review of Lagrange Multipliers –As we discussed last time, the first order necessary conditions.

1 Self-optimizing control From key performance indicators to control of biological systems Sigurd Skogestad Department of Chemical Engineering Norwegian.

1 PLANTWIDE CONTROL Sigurd Skogestad Department of Chemical Engineering Norwegian University of Science and Tecnology (NTNU) Trondheim, Norway August/September.

1 Visit at Perstorp Daniel Greiner Edvardsen (Master student) Johannes Jäschke (PhD) April 14th, 2010.

Process control group of Sigurd Skogestad, Departmenmt of Chemical Engineering, NTNU, Trondheim,

1 A SYSTEMATIC APPROACH TO PLANTWIDE CONTROL ( ) Sigurd Skogestad Department of Chemical Engineering Norwegian University of Science and Tecnology.

Control strategies for optimal operation of complete plants Plantwide control - With focus on selecting economic controlled variables Sigurd Skogestad,

Coordinator MPC with focus on maximizing throughput

A systematic procedure for economic plantwide control

Oscar Camacho, Ph.D. Universidad de Los Andes, Venezuela

Changing between Active Constraint Regions for Optimal Operation: Classical Advanced Control versus Model Predictive Control Adriana Reyes-Lúa, Cristina.

Sigurd Skogestad 1955: Born in Flekkefjord, Norway

Sigurd Skogestad 1955: Born in Flekkefjord, Norway

Plantwide control: Towards a systematic procedure

PLANTWIDE CONTROL Sigurd Skogestad Department of Chemical Engineering

CONTROLLED VARIABLE AND MEASUREMENT SELECTION

Sigurd Skogestad 1955: Born in Flekkefjord, Norway

Plantwide control: Towards a systematic procedure

Decentralized control

Plantwide control: Towards a systematic procedure

Optimal measurement selection for controlled variables in Kaibel Distillation Column: A MIQP formulation Ramprasad Yelchuru (PhD Candidiate) Professor.

Outline Control structure design (plantwide control)

Presentation transcript:

MIMO Controllability and Decentralized and Plantwide Control MIMO Controllability and Decentralized and Plantwide Control Sigurd Skogestad on Manfred Morari’s contributions

The start (1977): A PhD thesis on plantwide control To: Terje Hertzberg & Kristian Lien From: Sigurd (April 1984): “Morari himself feels that his thesis is somewhat outdated and contains material of mainly academic interest”

Times cited: 111 (from Web of Science)

The origin of “Self-optimizing control” But: - Largely forgotten until late 90’s - No unconstrained examples - Measurement noise not included

Controllability: Chem. Eng. Sci. Series on “Design of resilient processing plants” I. Process Design Under Consideration of Dynamic Aspects (w/ Lenhoff), (40 citations) II. Design and Control of Energy Management Systems (w/ Marselle & Rudd), 1982 (46 citations) III. A General framework for the assessment of dynamic resilience (alone), 1983 (112 citations) IV. Some New Results on Heat Exchanger Network Synthesis (w/ Saboo), 1984 (42 citations) V. The Effect of Deadtime on Dynamic Resilience (w/ Holt) (69 citations) VI. The Effect of Right-Half-Plane Zeros on Dynamic Resilience (w/ Holt), 1985 (85 citations) VII. Design of Energy Management System for Unstable Reactors: New Insights (w/ Grimm, Ogelsby, Prosser), 1985 (20 citations) VIII. A Resilience Index for Heat Exchanger Networks (w/ Saboo, Woodcock), 1985, (49 citations) IX. Effect of Model Uncertainty on Dynamic Resilience (w/ Skogestad), 1987 (30 citations) NaN. New characterization of the effect of RHP zeros (w/ Zafiriou and Holt), 1987 (9 citations)

40 citations

DPI = Integral squared error J

112 citations

9 citations

97 citations

67 citations

152 citations

Aside (and small comfort for young researchers): In fact, Early M 2 work is not highly cited… 1 st journal paper Title: FINITE STABILITY REGIONS FOR LARGE-SCALE SYSTEMS WITH STABLE AND UNSTABLE SUBSYSTEMS Author(s): MORARI M; STEPHANOPOULOS G; ARIS R Source: INTERNATIONAL JOURNAL OF CONTROL Volume: 26 Issue: 5 Pages: Published: 1977 Times Cited: 2 (from Web of Science). 2 nd journal paper Title: FINDING GENERIC RANK OF A STRUCTURAL MATRIX - COMMENTS Author(s): MORARI M; STEPHANOPOULOS G;; Source: IEEE TRANSACTIONS ON AUTOMATIC CONTROL (Technical Note), , 1978 Tines Cited: 5 3rd journal paper Title: SYNTHESIS OF DISTILLATION SCHEMES WITH ENERGY INTEGRATION Author(s): FAITH DC; MORARI M Source: COMPUTERS & CHEMICAL ENGINEERING Volume: 3 Issue: 1-4 Pages: Published: 1979 Times Cited: 3 4th journal paper Title: STABILITY ANALYSIS OF STRUCTURED CHEMICAL-ENGINEERING SYSTEMS VIA DECOMPOSITION Author(s): MORARI M; STEPHANOPOULOS G; ARIS R Source: CHEMICAL ENGINEERING SCIENCE Volume: 34 Issue: 1 Pages: Published: 1979 Times Cited: 4 Title: STABILITY OF MODEL-REFERENCE ADAPTIVE-CONTROL SYSTEMS Author(s): MORARI M Source: INDUSTRIAL & ENGINEERING CHEMISTRY PROC. DES. & DEV. Volume: 19 Issue: 2 Pages: Published: 1980 Times Cited: 0 Title: USING AN ADAPTIVE-OBSERVER TO DESIGN POLE-PLACEMENT CONTROLLERS FOR DISCRETE-TIME- SYSTEMS Author(s): SHAHROKHI M; MORARI M Source: INTERNATIONAL JOURNAL OF CONTROL Volume: 36 Issue: 4 Pages: Published: 1982 Times Cited: 0

Coleman Brosilow Manfred Morari

Times cited: 412

Decentralized control

Citations: 163

Citations: 156

Times cited: 83

Times cited: 80

A little confusion on “constrained control”: Is it active constraints control (steady-state) ? Is it dealing with constraints dynamically (today: MPC) ?

Rule of plantwide control: Control active constraints (steady-state optimal operation)

??

Manfred, seems you are mixing 1.optimally active constraints (steady-state) 2.dynamic saturation Example car: J = T (minimize driving time from A to B) u = engine power Constraints: u < umax v < vmax (speed limit) 1. Steady-state. What should we control? Flat road: CV = v (active constraint with setpoint = vmax – backoff) Steep hill: CV = u (active constraint with setpoint = umax) Switching between these two cases is trivial. 2. Dynamic. Flat road with increase in speed limit (vmax): May temporary reach umax-constraint (use MPC?)

Caltech group 1987

Caltech ChE brochure 1988

March 1990

No plantwide, decentralized or controllability/resilience. 2 on distillation design!

Conclusion: Contributions M 2 Plantwide: Some major, a little confusion? Controllability (“dynamic resilience”): Major Decentralized: Major

Top 3 robustness papers 1.Title: Robust constrained model predictive control using linear matrix inequalities Author(s): Kothare MV; Balakrishnan V; Morari M Source: AUTOMATICA Volume: 32 Issue: 10 Pages: DOI: / (96) Published: OCT 1996 Times Cited: 567 (from Web of Science) 2.Title: ROBUST-CONTROL OF ILL-CONDITIONED PLANTS - HIGH-PURITY DISTILLATION Author(s): SKOGESTAD S; MORARI M; DOYLE JC Source: IEEE TRANSACTIONS ON AUTOMATIC CONTROL Volume: 33 Issue: 12 Pages: DOI: / Published: DEC 1988 Times Cited: 151 (from Web of Science) 3.Title: ROBUST-CONTROL OF PROCESSES SUBJECT TO SATURATION NONLINEARITIES Author(s): CAMPO PJ; MORARI M Source: COMPUTERS & CHEMICAL ENGINEERING Volume: 14 Issue: 4- 5 Pages: DOI: / (90)87011-D Published: MAY 1990 Times Cited: 124 (from Web of Science)