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University Politehnica of Bucharest - Doctor Honoris Causa. Professor Stratos Pistikopoulos FREng. Outline. A brief introduction Chemical Engineering Process Systems Engineering On-going research areas & projects Multi-parametric programming & control. Stratos Pistikopoulos. - PowerPoint PPT Presentation

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Parametric Programming & Control

University Politehnica of Bucharest -Doctor Honoris CausaProfessor Stratos Pistikopoulos FREng

Outline A brief introductionChemical EngineeringProcess Systems EngineeringOn-going research areas & projectsMulti-parametric programming & control

Stratos PistikopoulosDiploma (Chem Eng) AUTh, 1984PhD (Chem Eng) CMU, 19881991 Imperial College London; since 1999 Professor of Chemical Engineering2002 - 2009 Director, Centre for Process Systems Engineering (CPSE), Imperial2009 - 2013 Director of Research, Chem Eng, Imperial2009 - 2013 Member, Faculty of Engineering Research Committee, Imperial

Stratos PistikopoulosProcess systems engineeringModelling, optimization & controlProcess networks, energy & sustainable systems, bioprocesses, biomedical systems250+ major journal publications, 8 books, 2 patentsh-index 40; ~5000 citations

Stratos Pistikopoulos FREng, FIChemE(Co-) Editor, Comp & Chem EngCo-Editor, Book Series (Elsevier & Wiley)Editorial Boards I&ECR, JOGO, CMSFounder/Co-founder & Director PSE Ltd, ParOS2007 co-recipient Mac Robert Award, RAEng2008 Advanced Investigator Award, ERC2009 Bayer Lecture, CMU2012 Computing in Chemical Engineering Award, CAST, AIChE 2014 21st Professor Roger Sargent Lecture, Imperial

Chemical Engineering

6Emerging Chemical EngineeringRelatively young[er] profession (societies founded in early part of 19th century, Manchester, UCL, Imperial - 1880s; MIT 1888)(Most likely the) most versatile engineering profession (strong societies & academic programmes, highly-paid in manufacturing, business, banking, consulting)Central discipline towards addressing societal grand challenges (energy & the environment/sustainability, health & the bio-(mics) revolution, Nano-engineering, Info-revolution, central to almost all Top 10 emerging technologies for 2012 World Economic Forum!)Multi-scale & multi-discipline chemical engineering

Evolution of Chemical Engineering

Recognition of length and time scalesEvolution of Chemical Engineering

Length-scaleTime-scaleFactors

Energy (algae, energy-based metabolic engineering & optimisation)Product(quality, formulation, quantity)Control(model-basedInformation pathways)Transport(MolecularDesign of Nanoparticles)Only Chemical Engineering integrates TIME, LENGTH, FACTORS (input/output)Chemical Engineering - researchResearch .. strong core chemical engineering, new opportunities in nano-driven chemical engineering, biochemical and biomedical-driven chemical engineering, energy/sustainability-driven chemical engineering, info-driven chemical engineering

Interactions/interfaces with chemistry, materials, medicine, biology, computing/applied math & beyond molecular level, nano-materials, nano/micro-reaction, micro-human, carbon dioxide conversion, bio-energy, resource efficiency & novel manufacturing, from mind to factory, systems of systems, ...

Chemical Engineering a model CoreMulti-scaleUnderstanding& Modelling

Chemical Engineering a model CoreMulti-scaleUnderstanding& Modelling

Simulation/Optimization Measurements/Visualization/AnalyticsDesign/Products &ProcessesProperties/Transport/Reaction/Separation Experiments/ValidationChemical Engineering a model Bio & Medical driven Chemical EngineeringEnergy/SustainabilityChemicalEngineeringNano-ChemicalEngineering

Molecular & Materials/ProductChemical EngineeringCoreMulti-scaleUnderstanding& Modelling

Simulation/Optimization Measurements/Visualization/AnalyticsDesign/Products &ProcessesProperties/Transport/Reaction/Separation Experiments/ValidationChemical Engineering a model Bio & Meddriven Chemical EngineeringEnergy/SustainabilityChemicalEngineeringNano- &Multi-scale ChemicalEngineering

Molecular/MaterialsChemical EngineeringCoreMulti-scaleUnderstanding& Modelling

Materials AnalyticalSciencesSystems Transport& Separation Reaction&CatalysisOutline A brief introductionChemical EngineeringProcess Systems EngineeringOn-going research areas & projectsMulti-parametric programming & control

Process Systems Engineering

Process Systems Engineering Scientific discipline which focuses on the study & development of theoretical approaches, computational techniques and computer-aided tools for modelling, analysis, design, optimization and control of complex engineering & natural systems with the aim to systematically generate and develop products and processes across a wide range of systems involving chemical and physical change; from molecular and genetic information and phenomena, to manufacturing processes, to energy systems and their enterprise-wide supply chain networks

PSE brief historical overview Relatively new area in chemical engineering started in the sixties/early seventies [Roger Sargent, Dale Rudd, Richard Hughes, and others & their academic trees] Chemical Engineering around 1890+ [MIT, UCL, Imperial] AIChE - 1908; IChemE - 1922

PSE brief historical overview Relatively new area in chemical engineering started in the sixties/early seventies [Roger Sargent, Dale Rudd, Richard Hughes, and others & their academic trees]Key historical dates 1961 the term introduced [special volume of AIChE Symposium Series]; 1964 first paper on SPEEDUP [simulation programme for the economic evaluation and design of unsteady-state processes]; 1968 first textbook Strategy of Process Engineering by Rudd & Watson (Wiley); 1970 CACHE Corporation; 1977 CAST division of AIChE; 1977 Computers & Chemical Engineering Journal

PSE brief historical overview 1980s FOCAPD 1980; PSE 1982; CPC, FOCAPOEarly 90s ESCAPE seriesSignificant growthCentres of excellence & critical mass CMU, Purdue, UMIST, Imperial, DTU, MIT, others around the world (US, Europe, Asia Japan, Singapore, Korea, China, Malaysia)

PSE Current Status Well recognized field within chemical engineeringPSE academics in many [most?] chemical engineering departments Undergraduate level standard courses [& textbooks] on process analysis, process design, process control, optimization, etcResearch level major activity & strong research programmes [US & Canada, Europe, Asia, Latin America, Australia]

PSE Current Status Well established global international events & conferencesHighly respected journals, books & publications Strong relevance to & acceptance by industry- across wide range of sectors [from oil & gas to chemicals, fine chemicals & consumer goods, ..]PSE software tools essential in industry & beyond [simulation, MPC, optimization, heat integration, etc PSE linked companies]

PSE impact Training & educationSignificant research advances process design process control process operations numerical methods & optimization [software & other] toolsBeyond chemical engineering .. [?]

Traditional PSE PSE Core Mathematical Modelling Process Synthesis Product & Process Design Process Operations Process Control Numerical Methods & Optimization

PSE CoreRecognition of length and time scalesFrom nano-scale (molecular) to micro-scale (particles, crystals) to meso-scale (materials, equipment, products) to mega-scale (supply chain networks, environment)

PSE evolution ..

PSE CoreRecognition of length and time scalesFrom nano-scale (molecular) to micro-scale (particles, crystals) to meso-scale (materials, equipment, products) to mega-scale (supply chain networks, environment)

Multi-scale Modelling

PSE evolution ..

Product Value Chain (Marquardt; Grossmann et al)Recognition of length and time scalesPSE evolution ...Multi-scaleModelling

PSE evolution ...MultiscaleModelling

simulationcontroloptimizationProduct/processdesignsynthesis Recognition of length and time scalesFrom nano-scale (molecular) to micro-scale (particles, crystals) to meso-scale (materials, equipment, products) to mega-scale (supply chain networks, environment) Core, generic enabling technology provider to other domainsmolecular genomic biological materials energy automation plants oilfields global supply chains

Multi-scale process systems engineering

PSE evolution

Multi-scale Process Systems EngineeringBiological& BiomedicalSystems EngineeringEnergy/SustainabilitySystems EngineeringSupply ChainSystems EngineeringMulti-scale Modelling

MolecularSystems EngineeringsimulationcontroloptimizationProduct/processdesignsynthesisMulti-scale PSEPSE CoreDomain-driven PSEProblem-centric PSEPSE Core Multi-scale Modelling Multi-scale Optimization Product & Process Design Process Operations Control & Automation

Domain-driven PSE Molecular Systems Engineering Materials Systems Engineering Biological Systems Engineering Energy Systems Engineering Problem-centric PSE Environmental systems engineering Safety systems engineering Manufacturing supply chains

Multi-scale Process Systems EngineeringBiological& BiomedicalSystems EngineeringEnergy/SustainabilitySystems EngineeringSupply ChainSystems EngineeringMulti-scale Modelling

MolecularSystems EngineeringsimulationcontroloptimizationdesignsynthesisMulti-scale Process Systems Engineering leads to ..Biological& BiomedicalSystems EngineeringEnergy/SustainabilitySystems EngineeringSupply ChainSystems EngineeringMulti-scale Modelling

MolecularSystems Engineeringsimulationcontroloptimizationdesignsynthesis CONCEPTOPERATIONDESIGNDetailed design of complex equipmentProcess flowsheetingOptimization of plant and operating procedures

Process developmentOperationaloptimizationTCAPlantTroubleshooting/SafetyModel-based automationModel Based Innovation across the Process LifecycleProcess Systems Engineering.. provides the scientific glue within chemical engineering (Perkins, 2008)Bio-drivenChemicalEngineeringEnergy -drivenChemicalEngineeringMulti-scaleChemicalEngineeringProcessSystems Engineering

MolecularDriven ChemicalEngineeringMaterialsAnalytics/ExperimentalPropertiesReactionengineeringTransportPhenomenaProcess Systems Engineeringsystems thinking & practice essential to address societal grand challengesHealthEnergySustainableManufacturingSystems Engineering

Nano - materialssimulationcontroloptimizationdesignsynthesisOutline A brief introductionChemical EngineeringProcess Systems EngineeringOn-going research areas & projectsMulti-parametric programming & control

Research Group - research areas & current projects

AcknowledgementsFundingEPSRC - GR/T02560/01, EP/E047017, EP/E054285/1EU - MOBILE, OPTICO, PRISM, PROMATCH, DIAMANTE, HY2SEPS, IRSESCPSE Industrial Consortium, KAUSTAir Products

PeopleJ. Acevedo, V. Dua, V. Sakizlis, P. Dua, N. Bozinis, P. Liu, N. Faisca, K. Kouramas, C. Panos, L. Dominguez, A. Voelker, H. Khajuria, M. Wittmann-Hohlbein, H. ChangP. Rivotti, A. Krieger, R. Lambert, E. Pefani, M. Zavitsanou, E. Velliou, G. Kopanos, A. Manthanwar, I. Nascu, M. Papathanasiou, N. Diangelakis, M. Sun, R. OberdieckJohn Perkins, Manfred Morari, Frank Doyle, Berc Rustem, Michael GeorgiadisImperial & ParOS R&D Teams, Tsinghua BP Energy Centre

Current Research Focus OverviewMulti-parametric programming & Model Predictive Control [MPC]Energy & Sustainability (driven) Systems EngineeringBiomedical Systems Engineering

Energy and Sustainability (driven) SystemsSynthesis and DesignDesign of micro-CHP systems for residential applicationsDesign of poly-generation systemsLong-term design and planning of general energy systems under uncertaintyOperations and controlScheduling under uncertainty of micro-CHP systems for residential applicationsSupply chain optimization of energy systemsIntegration of design and control for energy systems fuel cells, CHPsIntegration of scheduling and control of energy systems under uncertaintyBiomedical Systems EngineeringLeukaemia Development of optimal protocols for chemotherapy drug delivery for:Acute Myeloid Leukaemia (AML)Chronic Lymphocytic Leukaemia (CLL)Experimental, modelling and optimization activityAnaesthesia & DiabetesEmphasis on modelling and control in volatile anaesthesiathe artificial pancreasCollaboration with Prof. Mantalaris and Dr. PanoskaltsisCollaboration with Prof Frank Doyle, UC Santa-BarbaraMulti-Parametric Programming & Explicit MPCa progress reportProfessor Stratos Pistikopoulos FREng

Outline Key concepts & historical overviewRecent developments in multi-parametric programming and mp-MPCMPC-on-a-chip applicationsWhat is On-line Optimization?MODEL/OPTIMIZERSYSTEMData - MeasurementsControl Actions

What is Multi-parametric Programming?Given: a performance criterion to minimize/maximize a vector of constraints a vector of parameters

What is Multi-parametric Programming?Given: a performance criterion to minimize/maximize a vector of constraints a vector of parameters

Obtain: the performance criterion and the optimization variables as a function of the parameters the regions in the space of parameters where these functions remain valid

Multi-parametric programming

(2) Critical Regions(1) Optimal look-up function Obtain optimal solution u(x) as a function of the parameters xMulti-parametric programming

Problem FormulationMulti-parametric programmingCritical Regions

x2x1Multi-parametric programmingMulti-parametric Solution

Multi-parametric programmingOnly 4 optimization problems solved!

On-line Optimization via off-line OptimizationSystem StateControl ActionsOPTIMIZERSYSTEMPOPPARAMETRIC PROFILESYSTEMSystem StateControl ActionsFunction Evaluation!Multi-parametric/Explicit Model Predictive ControlCompute the optimal sequence of manipulated inputs which minimizes

On-line re-planning: Receding Horizon Control

tracking error = output referencesubject to constraints on inputs and outputsCompute the optimal sequence of manipulated inputs which minimizes

On-line re-planning: Receding Horizon ControlMulti-parametric/Explicit Model Predictive Control

Solve a QP at each time intervalMulti-parametric Programming ApproachState variables ParametersControl variables Optimization variables

MPC Multi-Parametric Programming problemControl variables F(State variables)Multi-parametric Quadratic ProgramExplicit Control Law

Multi-parametric ControllersSYSTEMParametric ControllerOptimization Model

(2) Critical Regions(1) Optimal look-up function MeasurementsControl ActionInput DisturbancesSystem Outputs Explicit Control Law Eliminate expensive, on-line computations Valuable insights !

MPC-on-a-chip!A framework for multi-parametric programming & MPC (Pistikopoulos 2008, 2009)High-Fidelity Dynamic ModelModel Reduction TechniquesSystem IdentificationModelling/ Simulation Identification/ ApproximationModel-Based Control & ValidationClosed-LoopControl System ValidationExtraction of Parametric Controllersu = u ( x() )Approximate ModelMulti-Parametric Programming (POP)High-Fidelity Dynamic ModelModel Reduction TechniquesSystem IdentificationModelling/ Simulation Identification/ ApproximationModel-Based Control & ValidationClosed-LoopControl System ValidationExtraction of Parametric Controllersu = u ( x() )Approximate ModelMulti-Parametric Programming (POP)REAL SYSTEMEMBEDDED CONTROLLEROn-line Embedded Control:Off-line Robust Explicit Control Design:A framework for multi-parametric programming and MPC (Pistikopoulos 2010)Key milestones-Historical Overview Number of publications

2002 Automatica paper - citations [Sep 2014]: 900+ WoS; 1200+ Scopus; 1650+ Google ScholarMulti-parametric programming until 1992 mostly analysis & linear modelsMulti-parametric/explicit MPC post-2002 much wider attentionMulti-Parametric ProgrammingMulti-Parametric MPC & applicationsPre-1999>1000 Post-1999~70250+AIChE J.,Perspective (2009)Multi-parametric Programming Theory mp-LPGass & Saaty [1954], Gal & Nedoma [1972], Propoi [1975], Adler and Monterio [1992], Gal [1995], Acevedo and Pistikopoulos[1997], Dua et al [2002], Pistikopoulos et al [2007]mp-QPTownsley [1972], Propoi [1978], Best [1995], Dua et al [2002], Pistikopoulos et al [2002,2007]mp-NLPFiacco [1976],Kojima [1979], Bank et al [1983], Fiacco [1983], Fiacco & Kyoarisis [1986], Acevedo & Pistikopoulos [1996], Dua and Pistikopoulos [1998], Pistikopoulos et al [2007]mp-DOSakizlis et al.[2002], Bansal [2003], Sakizlis et al [2005], Pistikopoulos et al [2007]mp-GOFiacco [1990], Dua et al [1999,2004], Pistikopoulos et al [2007]mp-MILPMarsten & Morin [1975], Geoffrion & Nauss [1977], Joseph [1995], Acevedo & Pistikopoulos [1997,1999], Dua & Pistikopoulos[ 2000]mp-MINLPMcBride & Yorkmark [1980], Chern [1991], Dua & Pistikopoulos [1999], Hene et al [2002], Dua et al [2002]Multi-parametric/Explicit Model Predictive Control Theorymp-MPCPistikopoulos [1997, 2000], Bemporad, Morari, Dua & Pistikopoulos [2000], Sakizlis & Pistikopoulos [ 2001], Tondel et al [2001], Pistikopoulos et al [2002], Bemporad et al [2002], Johansen and Grancharova [2003], Sakizlis et al [2003], Pistikopoulos et al [2007]mp-Continuous MPCSakizlis et al [2002], Kojima & Morari[ 2004], Sakizlis et al [2005], Pistikopoulos et al [2007]Hybrid mp-MPCBemporad et al [2000], Sakizlis & Pistikopoulos [2001], Pistikopoulos et al [2007]Robust mp-MPCKakalis & Pistikopoulos [2001], Bemporad et al [2001], Sakizlis et al [2002], Sakizlis & Pistikopoulos [2002], Sakizlis et al [2004], Olaru et al [2005], Faisca et al [2008]

mp-DPNunoz de la Pena et al [2004],Pistikopoulos et al [2007],Faisca et al [2008]mp-NMPCJohansen [2002], Bemporad [2003], Sakizlis et al [2007], Dobre et al [2007], Narciso & Pistikopoulos [2009]68

Patented TechnologyImproved Process ControlEuropean Patent No EP1399784, 2004

Process Control Using Co-ordinate SpaceUnited States Patent No US7433743, 2008

Multi-parametric programming & Model Predictive Control [MPC]Theory of multi-parametric programmingMulti-parametric mixed integer quadratic programming [mp-MIQP]Multi-parametric dynamic optimization [continuous-time, mp-DO]Multi-parametric global optimizationTheory of multi-parametric/explicit model predictive control [mp-MPC]Explicit robust MPC of hybrid systemsExplicit MPC of continuous time-varying [dynamic] systemsExplicit MPC of periodic systemsMoving Horizon Estimation & mp-MPCMulti-parametric programming & Model Predictive Control [MPC] contdFramework for multi-parametric programming & controlModel approximation [from high fidelity models to the design of explicit MPC controllers]Software development, prototype & demonstrations [for teaching & research]Application areasFuel cell energy system experimental/laboratoryCar system control prototypes/laboratoryEnergy systems [CHP and micro-CHP]Bio-processing [continuous production & control of monoclonal antibodies]Pressure Swing Absorption [PSA] and hybrid systemsBiomedical SystemsMPC-on-a-chip Applications Recent DevelopmentsProcess Control Air Separation (Air Products)Hybrid PSA/Membrane Hydrogen Separation (EU/HY2SEPS, KAUST)AutomotiveActive Valve Train Control (Lotus Engineering)Energy SystemsHydrogen Storage (EU/DIAMANTE)Fuel Cell MPC-on-a-chip Applications Recent DevelopmentsBiomedical Systems (MOBILE - ERC Advanced Grant Award)Drug/Insulin, Anaesthesia and Chemotherapeutic Agents Delivery SystemsImperial Racing GreenFuel cell powered Student Formula CarAeronautics (EPSRC)(Multiple) Unmanned Air Vehicles with Cranfield UniversitySmall Air Separation Units (Air Products, Mandler et al,2006)Enable advanced MPC for small separation unitsOptimize performanceMinimize operating costsSatisfy product and equipment constraints

Parametric MPC ideally suitedSupervises existing regulatory controlOff-line solution with minimum on-line loadRuns on existing PLCRapid installation compared to traditional MPC

Advantages of Parametric MPC5% increased throughput5% less energy usage90% less wasteInstallation on PLC in 1-day

Active Valve Train Control (Lotus Engineering, Kosmidis et al, 2006)Active Valve Trains (AVT):Optimum combustion efficiency, Reduced Emissions, Elimination of butterfly valve, Cylinder deactivation, Controlled auto-ignition (CAI), Quieter operationBasic idea:Control System sends signal to valveThis actuates piston attached to engine valveEnables optimal control of valve timing over entire engine rpm rangeChallenges for the AVT controlNonlinear system dynamics: Saturation, flow non-linearity, variation in fluid properties, non-linear opening of the orificesRobustness to various valve lift profilesFast dynamics and sampling times (0.1ms)

Multi-parametric Control of H2 Storage in Metal-Hydride Beds (EU-DIAMANTE, Georgiadis et al, 2008)Tracking the optimal temperature profileEnsure economic storage expressed by the total required storage timeSatisfy temperature and pressure constraints

Optimal look-up table(Projected on the yt - ut plane)

PEM Fuel Cell Unit Collaborative work with Process Systems Design & Implementation Lab (PSDI) at CERTH - Greece

Unit Specifications Fuel Cell : 1.2kW Anode Flow : 5..10 lt/min Cathode Flow : 8..16 lt/min Operating Temperature : 65 75 C Ambient PressureControl StrategyStart-up OperationHeat-up Stage : Control of coolant loopNominal OperationControl Variables :Mass Flow Rate of Hydrogen & AirHumidity via Hydrators temperatureCooling system via pump regulation Known Disturbance : CurrentUnit Design : Centre For Research & Technology Hellas (CERTH)

(2) Critical Regions(1) Optimal look-up function PEM Fuel Cell SystemmH2mAir mcoolTYHydratorsVfanTst HTst

PEM Fuel Cell Unit 79

80

81

82

Imperial Racing Green CarStudent Formula Project

Control of Start-up/Shut-down of the FCTraction Motion Control

Control & Acquisition SystemFPGA(MPC-on-a-Chip)Biomedical Systems (MOBILE ERC Advanced Grant)

Step 1: The sensor measures the glucose concentration from the patient Step 2: The sensor then inputs the data to the controller which analyses it and implements the algorithmStep 3: After analyzing the data the controller then signals the pump to carry out the required actionStep 4: The Insulin Pump delivers the required dose to the patient intravenously ControllerSensorPatientInsulin Pump

1234University Politehnica of Bucharest -Doctor Honoris CausaMulumesc!

University Politehnica of Bucharest -Doctor Honoris CausaProfessor Stratos Pistikopoulos FREng