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TU Berlin

Inhalt des Dokuments


You can find below a list of my publications.

You can also visit my google scholar profile [link]

Journal publications

Lindhorst, H., Lucia, S., Findeisen, R. and Waldherr, S. (2019). Modeling Enzyme Controlled Metabolic Networks in Rapidly Changing Environments by Robust Optimization. IEEE Control Systems Letters, 248–253.

Lucia, S., Navarro, D., Lucia, O., Zometa, P. and Findeisen, R. (2018). Optimized FPGA Implementation of Model Predictive Control Using High Level Synthesis Tools. IEEE Transactions on Industrial Informatics, 137–145.

Thangavel, S., Lucia, S., Paulen, R. and Engell, S. (2018). Dual Robust Nonlinear Model Predictive Control: A Multi-stage Approach. Journal of Process Control, 39–51.

Lucia, S., Navarro, D., Karg, B., Sarnago, H. and Lucia, O. (2018). Deep Learning-based Model Predictive Controlfor Resonant Power Converters. IEEE Transactions on Industrial Informatics (submitted), 137–145.

Karg, B. and Lucia, S. (2018). Efficient representation and approximation of model predictive control laws via deep learning. arXiv preprint arXiv:1703.02702

Lucia, S., Tatulea-Codrean, A., Schoppmeyer, C. and Engell, S. (2017). Rapid Development of Modular and Sustainable Nonlinear Model Predictive Control Solutions. Control Engineering Practice, 51-62.

Lucia, S., Kögel, M., Zometa, P., Quevedo, D. E. and Findeisen, R. (2016). Predictive control, embedded cyberphysical systems and systems of systems – A perspective. Annual Reviews in Control, 193–207.

Marti, R., Lucia, S., Sarabia, D., Paulen, R., Engell, S. and de Prada, C. (2015). Improving scenario decomposition algorithms for robust nonlinear model predictive control. Computers & Chemical Engineering, 30 - 45.

Lucia, S., Andersson, J., Brandt, H., Diehl, M. and Engell, S. (2014). Handling Uncertainty in Economic Nonlinear Model Predictive Control: a Comparative Case-study. Journal of Process Control, 1247-1259.

Finkler, T., Lucia, S., Dogru, M. and Engell, S. (2013). Simple Control Scheme for Batch Time Minimization of Exothermic Semibatch Polymerizations. Industrial & Engineering Chemistry Research, 5906-5920.

Lucia, S., Finkler, T. and Engell, S. (2013). Multi-stage Nonlinear Model Predictive Control Applied to a Semi-batch Polymerization Reactor under Uncertainty. Journal of Process Control, 1306-1319.

Conference publications

Predictive Control in the Era of Networked Control and Communication - a Perspective
Citation key lucia2015_plenary
Author Lucia, S. and M. Kögel and P. Zometa and D.E. Quevedo and R. Findeisen
Title of Book Proc. of the 5th IFAC Conference on Nonlinear Model Predictive Control
Pages 322 - 331
Year 2015
Abstract Advances in communication, information technology, and computation have led to a rapid change of todays world. Actuation, communication, sensing, and control are becoming ubiquitous. While this offers many possibilities - Smart cities, Smart buildings, Smart devices, Smart factories, Smart health monitoring a smarter world - there are also several challenges which need to be tackled. How can one handle the increasing complexity? Can one guarantee safety and performance of such networked control systems subject to erroneous communication, delays, and failures of sensors and actuators? Is it possible to design control systems with plug and play capacity? How can one guarantee privacy of the controlled subsystems while exchanging information? Predictive control is a well suited control approach to tackle some of these challenges, since its allows to directly take constraints, preview information, as well as models of the physical world into account.We limit our attention to three areas we believe predictive control methods can have a significant impact: the efficient and easy implementation of predictive control on the omnipresent embedded computation hardware, the control under resource limitations and network effects, and the control on the network level, outlining a contract based control approach which allows a structured, yet flexible hierarchical design.We briefly review results from these fields and outline some solutions related to our work, that provide possible solutions to the considered challenges.
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You can download a copy of my Dissertation, entitled Robust Multi-stage Nonlinear Model Predictive Control, clicking here

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