Economically Effective Control of Energy Intensive Chemical Processes
Grant: Excellent Teams of Young Researchers at STU in Bratislava
Principal Investigator: M. Klaučo
Participating solvers: J. Holaza, P. Bakaráč
Period: 2018 - 2019
This project deals with designing of advanced model predictive control synthesis for energy-demanding chemical processes. Especially in these type of process, the choice of a suitable control strategy is largely affecting the economic aspects of production. The main of such control strategy is to minimize the input raw materials and decrease the maintenance costs. Into the family of energy-demanding chemical, processes belong, for example, the distillation column or steam-gas powerhouses. In these types of processes, even a small reduction of input raw materials has the a huge economic impact.
In this project, we will present a synthesis of an advanced model predictive controller which the main purpose will be to optimize setpoints for current control algorithms. This type of control strategy is called "MPC-based Reference Governor Control". By implementing this kind of controller, we will avoid upgrading current control strategies, which is often costly process. Furthermore, since the advanced MPC controller is an optimization-based control strategy, the use of such strategy naturally leads to optimal plant behavior.
- M. Furka – M. Klaučo: Development and Implementation of Control Algorithms for Furuta Pendulum. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 22nd International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, 2019.
- K. Kiš – M. Klaučo: Machine Learning Approaches Applied to Generation of Explicit Control. Editor(s): M. Fikar and M. Kvasnica, In Proceedings of the 22nd International Conference on Process Control, Slovak Chemical Library, Štrbské Pleso, Slovakia, 2019.
- M. Klaučo – M. Kvasnica: MPC-Based Reference Governors, Springer, Springer International Publishing, 2019.
- P. Bakaráč – P. Valiauga – M. Kvasnica: Energy-Efficient Swing up and Explicit MPC Stabilization of an Inverted Pendulum. In Preprints of the 6th IFAC Conference on Nonlinear Model Predictive Control, Madison, Wisconsin, USA, 2018.
- M. Klaučo – Ľ. Čirka – J. Kukla: Non-linear model predictive control of conically shaped liquid storage tanks. Acta Chimica Slovaca, no. 2, vol. 11, pp. 141–146, 2018.
- M. Klaučo – M. Kvasnica: Towards On-Line Tunable Explicit MPC Using Interpolation. In Preprints of the 6th IFAC Conference on Nonlinear Model Predictive Control, Madison, Wisconsin, USA, 2018.
Responsibility for content: Ing. MSc. Martin Klaučo, PhD.
Last update: 08.06.2018 7:57