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MAIN RESEARCH INTERESTS:process
control / control of large scale industrial plants
model predictive control (MPC), in particular nonlinear MPC
estimation of nonlinear systems (kalman filter based, moving-horizon estimation, robust state estimation, interval observers)
system identification, in particular closed-loop system identification
(municipal solid) waste combustion
upstream oil and gas
applications (exploration and production)
MAIN RESEARCH TOPICS:
Process Control of In-Line Separation Production Systems (ISAPP, Post-Doc DUT, in collaboration with Shell and TNO)The
aim of this post-doc project is to disclose the possibilities of
process control for mitigating undesired multiphase flow phemonena,
such as slugs, on the separation facilities used for the production of
oil from wells. Particular applications are (i) existing wells that,
due to aging c.q. a lower reservoir pressure, start to produce slugs
and (ii) new wells positioned at awkward places such as very deep at
sea, which do not allow the usage of voluminous separation facilities
and which therefore are much less well capable of handling the
undesired multiphase flow phenomena properly.
Nonlinear Model Predictive Control of MSWC plants (PhD, in collaboration with TNO)Aim
of this PhD-project is to improve the control and overall economic
performance of current large-scale municipal solid waste (MSW)
combustion (MSWC) plants through the usage of the model based control
strategies, in particular nonlinear model predictive control.
combustion of municipal solid waste is used to reduce its
volume and, often, to produce energy (heat/electrcity). Its waste
reducing property has resulted in its use at many parts of the world as
an alternative to dumping, in particular at highly densily populated
places and islands, where dumping space is scarce. The energy resulting
from the combustion of the waste is used to produce heat and/or
electricity of which the part that is not used for the plant
itself is delivered (sold) to the surroundings. Waste is typically combusted at a plant as depicted below.
control systems used at MSWC plants can be divided in two parts: (i) a
control system dealing with the furnace and boiler part, also denoted
as the combustion control system, and (ii) flue gas cleaning equipment.
The focus of the PhD project is on the combustion control system of
which a typical one is schematically depicted below.
MSWC plant combustion control systems are performing non-optimally,
resulting in a non-optimal overall economic operation performance for
these plants. This due to their non-optimal handling of (i) the
multivariable nature of the MSWC plant combustion control problem, (ii)
the constraints imposed on MSWC plant MVs and, particularly, CVs out of
environmental and lifetime considerations and (iii) the disturbances
acting on these plants, which are very large for MSWC plants due to the
heavily fluctuating waste composition. The aim of the PhD project is
to improve the current combustion control performance, in
particular by means of Nonlinear Model Predictive Control because of
its good handling of the issues mentioned just above.
Supervisors: P.M.J. Van den Hof (DUT), O.H. Bosgra (DUT/TUE) and L.B.M. van Kessel (TNO).
OTHER RESEARCH TOPICS:
Soft-Sensing of Oil Wells (ISAPP work as an employee of TNO, also work together with Anton Gryzlov)The
aim here is to improve the current short-term production
performance of oil wells, in particular those with multiple branches,
by enhancing the real-time visibility of essential
well production performance parameters, in particular downhole oil, gas
and water flows. More specific, this aim is to be fulfilled with first-principles
model based soft-sensors (state estimators) that estimate the
values for these flows from surface and downhole pressure and
temperature measurements, as schematically depicted below for a single
well and for the case of using only downhole measurements:
The estimated values are to be delivered to a control system (ICVs) to optimally steer the process.
2011:Gryzlov, A., Leskens, M. and R.F. Mudde (2011).
A Semi-Implicit Approach for Fast Parameter Estimation by means of the Extended Kalman Filter. Journal of Process Control, Vol. 21, No. 4, pp. 510-518.
2007:Leskens, M. and P.M.J. Van den Hof (2007).
Closed-loop Identification of Multivariable Processes with Part of the Inputs Controlled. Int. J. Control, Vol. 80, No. 10, pp. 1552-1561.
M., van Kessel, L.B.M. and O.H. Bosgra (2005). Model Predictive
Control as a Tool for Improving the Process Operation of MSW Combustion
Plants. Waste Management, Vol. 25, No. 8, pp. 788 - 798.
2002:Leskens, M., van Kessel, L.B.M. and P.M.J.
Van den Hof (2002). MIMO Closed-loop Identification of an MSW Incinerator.
Control Engineering Practice, Vol. 10, no. 3, pp. 315-326.
- Kessel, L.B.M. van, Leskens, M. and G. Brem (2002). On-line Calorific Value Sensor and Validation of Dynamic Models Applied
to Municipal Solid Waste Combustion. Process Safety and
Environmental Protection, Vol. 80, no. 5, pp. 245-255.
M., Huesman, A., Van den Hof, P.M.J., Belfroid,
S., Nennie, E., Verbeek, P., Fuenmayor, A. and R. Henkes (2011).
Fast Model Based Approximation of the Closed-loop Performance Limits of Gas/Liquid Inline Separators for Accelerated Design. Accepted for the 18th IFAC World Congress to be held in Milano, Italy. (.pdf-version)
2010:Leskens, M., van 't Veen, P.P., van
Kessel, R., Bosgra, O.H. and P.M.J. Van den Hof (2010). Improved economic operation of
MSWC plants with a new model based PID control strategy. Proc. IFAC 9th International Symposium on
Dynamics and Control of Process Systems (DYCOPS 2010), Leuven, Belgium, pp. 641-646. (.pdf-version)
2009:Gryzlov, A., Leskens, M. and R. Mudde (2009). Fast and Accurate Parameter Estimation by Means of a Semi-Implicit
Extended Kalman Filter. Proc. European Control Conference (ECC 2009), Budapest, Hungary. (.pdf-version)
Gryzlov, A., Leskens, M. and R. Mudde (2009). Soft Sensing for Two-phase Flow using an Ensemble Kalman Filter. Proc. International Symposium on Advanced Control of Chemical Processes (ADCHEM 2009), Istanbul, Turkey. (.pdf-version)
M., van der Linden, R.J.P., van Kessel, R.L., Bosgra, O.H. and
P.M.J. Van den Hof (2008). Nonlinear Model Predictive Control of
Municipal Solid Waste Combustion Plants. Proc. Intern.
Workshop on Assessment and Future Directions of Nonlinear Model Predictive
Control, Pavia, Italy. (.pdf-version)
Kruif, B. de, Leskens, M., van der Linden, R. and G.
Alberts (2008). Soft-Sensing for Multilateral Wells With Downhole Pressure and Temperature
Measurements. Proc. 2008 Abu Dhabi International Petroleum Exhibition and Conference (ADIPEC), Abu Dhabi, UAE, SPE 118171.Leskens, M., de Kruif, B., Belfroid, S., Smeulers, J. and A. Gryzlov
(2008). Downhole Multiphase Metering in Wells by Means of Soft-Sensing. Proc. 2008 SPE Intelligent Energy Conference and Exhibition, Amsterdam,
The Netherlands, SPE 112046.
M., van Kessel, L.B.M., Van den Hof, P.M.J. and O.H. Bosgra
(2005). Nonlinear Model Predictive Control with Moving-Horizon State
and Disturbance Estimation, with Application to MSW Combustion. Proc. 16th IFAC World Congress, Prague, July 4-8, 2005, paper
Leskens, M. and P.M.J. Van den Hof (2004).
Closed-loop Identification of Multivariable Processes with Part of the Inputs Controlled. Proc. 2004 American Control Conference, Boston, MA, pp. 2830-2835.
OTHER PUBLICATIONS:Leskens, M. en R.J.P. van der Linden (2008). Snellere en betere procesregeling door gereduceerde fysische
modellen. NPT Procestechnologie, Editie 5, pp. 22-24.
many Benelux Meetings on System and Control have been attended. Here is
the abstract submitted to the next one to be held in Belgium: AbstractLskEtAl-BL2011.
For more publications: see DCSC website.