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X-WR-CALDESC:Events for 
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DTSTART:20250101T000000
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DTSTART;VALUE=DATE:20261002
DTEND;VALUE=DATE:20261003
DTSTAMP:20260911T131126Z
CREATED:20260911T130850Z
LAST-MODIFIED:20260911T131126Z
UID:1972-1790899200-1790985599@sacac.org.za
SUMMARY:Safe Exploration for Datadriven Real-Time Optimization Using Constraint Control
DESCRIPTION:
URL:https://sacac.org.za/event/safe-exploration-for-datadriven-real-time-optimization-using-constraint-control/
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20261012
DTEND;VALUE=DATE:20261014
DTSTAMP:20260908T132202Z
CREATED:20260724T084810Z
LAST-MODIFIED:20260908T132202Z
UID:1877-1791763200-1791935999@sacac.org.za
SUMMARY:SACAC Workshop: Observer Design For Dynamic Systems (Pretoria)
DESCRIPTION:  \nPROGRAMME\nDay 1: Basics of Observers \nThis day covers the basic concepts of observability and observers. \n\n\n\n08:00 – 08:30\nRegistration + Coffee/Tea\n\n\n08:30 – 09:00\nIntroduction\nDerik le Roux\n\n\n\nWhat is an observer?\nHow does it fit into a control loop? \n\nExample 1: Inverted PendulumBrunton\, S. L. and Kutz\, J. N. Data Driven Science and Engineering: Machine Learning\, Dynamical Systems and Control. Cambridge University Press\, 2019\n\n\nExample 2: CSTRHaseltine\, E. L. and Rawlings\, J. B. Critical evaluation of extended Kalman filtering and moving-horizon estimation. Ind. Eng. Chem. Res.\, 44:2451-2460\, 2005.\n\n\nExample 3: Falling objectJulier\, S.\, Uhlmann\, J.\, and Durrant-Whyte\, H. F. A new method for the nonlinear transformation of means and covariances in filters and estimators. IEEE Trans. Automatic Control\, 45(3):477-482\, 2000.\n\nThe introduction aims to provide an overview of what an observer is\, how it fits into a feedback control system\, and why they are important.\n\n\n\n09:00 – 10:00\nObservability\nDerik le Roux\n\n\n\n\n\nDefinition of Observability\nLinear Systems\n\nTests for observability for linear systems\n\nRank condition\nEigenvalue analysis\nObservability Gramian\n\nModel reduction and degree of observability\n\n\n\n\n\n\nNonlinear Systems\n\nObservability test using Lie derivatives\n\n\nDecomposition\n\nObservability is an important concept for the design of observers. The concept will be described mainly for linear systems\, specifically some of the basic tests to evaluate observability. Observability in the context of nonlinear systems will be discussed briefly.\n\n\n\n10:00 – 10:15\nCoffee/Tea break\n\n\n10:15 – 12:00\nObservers\nDerik le Roux / Denis Dochain\n\n\n\n\n\nLuenberger Observer and pole placement\nLinear Quadratic Regulators\, Linear Quadratic Observers and Linear Quadratic Gaussian control.\n\nThis section presents some of the foundational aspects of observers which is necessary to understand one of the most common observers\, the Kalman Observer.\n\n\n\n12:00 – 13:00\nLunch\n\n\n13:00 – 14:30\nMore Observers\nDerik le Roux / Denis Dochain\n\n\n\n\n\nKalman Observer\nExtended Kalman Observer\nOther nonlinear observers (Unscented Kalman Observer)\n\nThe most well-known observer\, the Kalman Observer\, will be discussed. Extensions of the observer for nonlinear systems and the tuning of these observers will be discussed.\n\n\n\n14:30 – 15:00\nCoffee/Tea break\n\n\n15:00 – 16:30\nSimulations\nDerik le Roux\n\n\n\n\n\nExercise A: Inverted Pendulum\nExercise B: CSTR\nExercise C: Falling object\n\nParticipants will play with MATLAB/Simulink simulations to better understand the different observers.\n\n\n\n\n  \nDay 2: Advanced topics \nThis day will cover the main topics as from the following articles: \n\nPannocchia\, G.\, Rawlings\, J.B. (2003). Disturbance Models for Offset-Free Model-Predictive Control. AIChE Journal\, 39(2)\, 426-437.\nD. (2003). State and parameter estimation in chemical and biochemical processes: a tutorial. Journal of Process Control\, 13\, 801-818.\n\n\n\n\n08:00 – 08:30\nCoffee/Tea break\n\n\n08:30 – 10:00\nOffset-free MPC using disturbance observers \nDerik le Roux\n\n\n\n\n\nWhat is offset-free MPC?\nHow to estimate disturbances and what are the limitations?\nSimulations\n\nThis section considers how Observers can be included in MPC loops to achieve offset-free setpoint tracking for MPC. It involves extending the model to include input/output disturbances\, but with specific limitations.\n\n\n\n10:00 – 10:15\nCoffee/Tea break\n\n\n10:15 – 12:00\nAsymptotic Observers and Reaction Invariants \nThe underlying idea of asymptotic observers is to take advantage of the structure of the dynamical models of a processes to rewrite part of the model in a form independent of the process kinetics. This structural property of mass and energy balance is closely related to the notion of reaction invariants.\nDenis Dochain\n\n\n12:00 – 13:00\nLunch\n\n\n13:00 – 14:30\nDecoupled parameter estimation \nImproved estimation performance is possible if the state estimation and the parameter estimation are decoupled from each other.\nDenis Dochain\n\n\n14:30 – 15:00\nCoffee/Tea break\n\n\n15:00 – 16:30\nSimulations \n\nExample A: CSTR\n\nParticipants will use MATLAB/Simulink simulations to better understand the different observer approaches.\nDenis Dochain / Derik le Roux
URL:https://sacac.org.za/event/sacac-workshop-observer-design-for-dynamic-systems-pretoria/
LOCATION:University of Pretoria
CATEGORIES:Workshop
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20261015
DTEND;VALUE=DATE:20261017
DTSTAMP:20260908T132344Z
CREATED:20260724T085002Z
LAST-MODIFIED:20260908T132344Z
UID:1880-1792022400-1792195199@sacac.org.za
SUMMARY:SACAC Workshop: Observer Design For Dynamic Systems (Stellenbosch)
DESCRIPTION:  \nPROGRAMME\nDay 1: Basics of Observers \nThis day covers the basic concepts of observability and observers. \n\n\n\n08:00 – 08:30\nRegistration + Coffee/Tea\n\n\n08:30 – 09:00\nIntroduction\nDerik le Roux\n\n\n\nWhat is an observer?\nHow does it fit into a control loop? \n\nExample 1: Inverted PendulumBrunton\, S. L. and Kutz\, J. N. Data Driven Science and Engineering: Machine Learning\, Dynamical Systems and Control. Cambridge University Press\, 2019\n\n\nExample 2: CSTRHaseltine\, E. L. and Rawlings\, J. B. Critical evaluation of extended Kalman filtering and moving-horizon estimation. Ind. Eng. Chem. Res.\, 44:2451-2460\, 2005.\n\n\nExample 3: Falling objectJulier\, S.\, Uhlmann\, J.\, and Durrant-Whyte\, H. F. A new method for the nonlinear transformation of means and covariances in filters and estimators. IEEE Trans. Automatic Control\, 45(3):477-482\, 2000.\n\nThe introduction aims to provide an overview of what an observer is\, how it fits into a feedback control system\, and why they are important.\n\n\n\n09:00 – 10:00\nObservability\nDerik le Roux\n\n\n\n\n\nDefinition of Observability\nLinear Systems\n\nTests for observability for linear systems\n\nRank condition\nEigenvalue analysis\nObservability Gramian\n\nModel reduction and degree of observability\n\n\n\n\n\n\nNonlinear Systems\n\nObservability test using Lie derivatives\n\n\nDecomposition\n\nObservability is an important concept for the design of observers. The concept will be described mainly for linear systems\, specifically some of the basic tests to evaluate observability. Observability in the context of nonlinear systems will be discussed briefly.\n\n\n\n10:00 – 10:15\nCoffee/Tea break\n\n\n10:15 – 12:00\nObservers\nDerik le Roux / Denis Dochain\n\n\n\n\n\nLuenberger Observer and pole placement\nLinear Quadratic Regulators\, Linear Quadratic Observers and Linear Quadratic Gaussian control.\n\nThis section presents some of the foundational aspects of observers which is necessary to understand one of the most common observers\, the Kalman Observer.\n\n\n\n12:00 – 13:00\nLunch\n\n\n13:00 – 14:30\nMore Observers\nDerik le Roux / Denis Dochain\n\n\n\n\n\nKalman Observer\nExtended Kalman Observer\nOther nonlinear observers (Unscented Kalman Observer)\n\nThe most well-known observer\, the Kalman Observer\, will be discussed. Extensions of the observer for nonlinear systems and the tuning of these observers will be discussed.\n\n\n\n14:30 – 15:00\nCoffee/Tea break\n\n\n15:00 – 16:30\nSimulations\nDerik le Roux\n\n\n\n\n\nExercise A: Inverted Pendulum\nExercise B: CSTR\nExercise C: Falling object\n\nParticipants will play with MATLAB/Simulink simulations to better understand the different observers.\n\n\n\n\n  \nDay 2: Advanced topics \nThis day will cover the main topics as from the following articles: \n\nPannocchia\, G.\, Rawlings\, J.B. (2003). Disturbance Models for Offset-Free Model-Predictive Control. AIChE Journal\, 39(2)\, 426-437.\nD. (2003). State and parameter estimation in chemical and biochemical processes: a tutorial. Journal of Process Control\, 13\, 801-818.\n\n\n\n\n08:00 – 08:30\nCoffee/Tea break\n\n\n08:30 – 10:00\nOffset-free MPC using disturbance observers \nDerik le Roux\n\n\n\n\n\nWhat is offset-free MPC?\nHow to estimate disturbances and what are the limitations?\nSimulations\n\nThis section considers how Observers can be included in MPC loops to achieve offset-free setpoint tracking for MPC. It involves extending the model to include input/output disturbances\, but with specific limitations.\n\n\n\n10:00 – 10:15\nCoffee/Tea break\n\n\n10:15 – 12:00\nAsymptotic Observers and Reaction Invariants \nThe underlying idea of asymptotic observers is to take advantage of the structure of the dynamical models of a processes to rewrite part of the model in a form independent of the process kinetics. This structural property of mass and energy balance is closely related to the notion of reaction invariants.\nDenis Dochain\n\n\n12:00 – 13:00\nLunch\n\n\n13:00 – 14:30\nDecoupled parameter estimation \nImproved estimation performance is possible if the state estimation and the parameter estimation are decoupled from each other.\nDenis Dochain\n\n\n14:30 – 15:00\nCoffee/Tea break\n\n\n15:00 – 16:30\nSimulations \n\nExample A: CSTR\n\nParticipants will use MATLAB/Simulink simulations to better understand the different observer approaches.\nDenis Dochain / Derik le Roux
URL:https://sacac.org.za/event/sacac-workshop-observer-design-for-dynamic-systems-stellenbosch/
LOCATION:Stellenbosch University
CATEGORIES:Workshop
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20270906
DTEND;VALUE=DATE:20270909
DTSTAMP:20260904T131734Z
CREATED:20260904T131623Z
LAST-MODIFIED:20260904T131734Z
UID:1929-1820188800-1820447999@sacac.org.za
SUMMARY:Control Conference Africa and Mining\, Minerals and Metals workshop (CCA/MMM2027)
DESCRIPTION:JOIN THE CONFERENCE MAILING LIST
URL:https://sacac.org.za/event/control-conference-africa-and-mining-minerals-and-metals-workshop-cca-mmm2027/
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