Linearizing Controller for Higher-degree Nonlinear Processes with Compensation for Modeling Inaccuracies - Practical Validation and Future Developments
Pawel Nowak, Jacek Czeczot, Tomasz Klopot, Mateusz Szymura, Bogdan Gabrys
2014
Abstract
This work shows the results of the practical implementation of the linearizing controller for the example laboratory pneumatic process of the third relative degree. Controller design is based on the Lie algebra framework but in contrast to the previous attempts, the on-line model update method is suggested to ensure offset-free control. The paper details the proposed concept and reports the experiences from the practical implementation of the suggested controller. The superiority of the proposed approach over the conventional PI controller is demonstrated by experimental results. Based on the experiences and the validation results, the possibilities of the potential application of the data-driven soft sensors for further improvement of the control performance are discussed.
References
- Ang K. H., Chong G., Li Y., 2005. PID control system analysis, design, and technology. IEEE Transactions on Control Systems Technology, 13(4), 559-576.
- Åström K. J., Hägglund T., 2005. Advanced PID design. Research Triangle Park, NC: ISA-The Instrumentation Systems and Automation Society.
- Albertos P., Goodwin G.C., 2002. Virtual sensors for control applications. Annual Reviews in Control 26, 101-112.
- Czeczot J., 1998. Model-based adaptive control of fedbatch fermentation process with the substrate consumption rate application, Proc. of IFAC Workshop on Adaptive Systems in Control and Signal Processing, University of Strathclyde, Glasgow, Scotland, UK, 357-362.
- Czeczot J., 2001. Balance-Based Adaptive Control of the Heat Exchange Process, Proc. of 7th IEEE International Conference on Methods and Models in Automation and Robotics MMAR 2001, Miedzyzdroje, Poland, 853-858.
- Czeczot J., 2006. Balance-Based Adaptive Control Methodology and its Application to the Nonlinear CSTR. Chemical Eng. and Processing, 45(5), 359- 371.
- Czeczot J., 2006a. Balance-Based Adaptive Control of a Neutralization Process, International Journal of Control 79(12), 1581-1600.
- Fortuna L., Graziani S., Rizzo A., Xibilia M. G., 2007. Soft sensors for monitoring and control of industrial processes. Springer.
- Golda P., 2013. Application of HMI/SCADA zenon environment for visualization and simulation of pneumatic laboratory setup. B.Sc. Thesis, Silesian University of Technology, Gliwice, Poland (in polish).
- Henson M. A., Seborg D. E., 1997. Nonlinear Process Control, Prentice Hall PTR.
- Isidori A., 1989. Nonlinear Control Systems: An Introduction, 2nd edition. Springer Verlag.
- Jin Q. B., Liu Q., 2014. IMC-PID design based on model matching approach and closed-loop shaping. ISA Transactions, 53, 462-473.
- Kadlec P., Gabrys B., 2008. Adaptive Local Learning Soft Sensor for Inferential Control Support, Proc. of the International Conference on Computational Intelligence for Modelling Control & Automation CIMCA 2008. Vienna, Austria, 243-248.
- Kadlec P., Gabrys B., 2009. Architecture for development of adaptive on-line prediction models, Memetic Computing, 1(4), 241-269.
- Kadlec P., Gabrys B., 2010. Adaptive on-line prediction soft sensing without historical data. Proc. of the Int. Joint Conf. on Neural Networks (IJCNN), Barcelona, Spain, 1-8.
- Kadlec P., Gabrys, B., 2011. Local learning-based adaptive soft sensor for catalyst activation prediction, AIChE Journal. 57(5), 1288-1301.
- Kadlec P., Gabrys B., Strandt S., 2009. Data-driven Soft Sensors in the Process Industry, Computers and Chemical Engineering, 33 (4), 795-814.
- Kadlec P., Grbic R., Gabrys B., 2011. Review of Adaptation Mechanisms for Data-driven Soft Sensing, Computers and Chemical Engineering. 35 (1), 1-24.
- Klopot T., Czeczot J., Klopot, W. 2012. Flexible Function Block For PLC-Based Implementation of the BalanceBased Adaptive Controller. Proc. of the American Control Conference, ACC 2012, Fairmont Queen Elizabeth, Montréal, Canada.
- Kravaris C., Hahn J., Chu Y., 2013. Advances and selected recent developments in state and parameter estimation. Computers and Chemical Engineering 51, 111-123.
- Lee P.L., Sullivan G.R., 1988. Generic model control (GMC), Computers and Chemical Engineering 12(6), 573-580.
- Lin B., Recke B., Knudsen J. K., Jørgensen, S. B., 2007. A systematic approach for soft sensor development. Computers and Chemical Engineering 31(5), 419-425.
- Maciejowski J. M., 2002. Predictive control with constraints. Prentice Hall.
- Metzger M., 2001. Easy programmable MAPI controller based on simplified process model. Proc. of the IFAC Workshop on Programmable Devices and Systems, Gliwice, Elsevier, 166-170.
- Rhinehart R. R., Riggs J. B., 1991. Two simple methods for on-line incremental model parameterization, Computers and Chemical Engineering 15(3), 181-189.
- Stebel K., Czeczot J., Laszczyk P., 2014. General tuning procedure for the nonlinear balance-based adaptive controller, International Journal of Control, 87(1), 76- 89.
Paper Citation
in Harvard Style
Nowak P., Czeczot J., Klopot T., Szymura M. and Gabrys B. (2014). Linearizing Controller for Higher-degree Nonlinear Processes with Compensation for Modeling Inaccuracies - Practical Validation and Future Developments . In Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-039-0, pages 691-698. DOI: 10.5220/0005048606910698
in Bibtex Style
@conference{icinco14,
author={Pawel Nowak and Jacek Czeczot and Tomasz Klopot and Mateusz Szymura and Bogdan Gabrys},
title={Linearizing Controller for Higher-degree Nonlinear Processes with Compensation for Modeling Inaccuracies - Practical Validation and Future Developments},
booktitle={Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2014},
pages={691-698},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005048606910698},
isbn={978-989-758-039-0},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Linearizing Controller for Higher-degree Nonlinear Processes with Compensation for Modeling Inaccuracies - Practical Validation and Future Developments
SN - 978-989-758-039-0
AU - Nowak P.
AU - Czeczot J.
AU - Klopot T.
AU - Szymura M.
AU - Gabrys B.
PY - 2014
SP - 691
EP - 698
DO - 10.5220/0005048606910698