Non-Linear Tank Level Control for Industrial Applications
- 1 School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough, UK
- 2 Design and Automation Research group, School of Mechanical and Building Sciences, Vellore Institute of Technology, Chennai, Tamil Nadu, India
Abstract
Tank level control is ubiquitous in industry. The focus of this paper is on accurate liquid level control in single tank systems which can be actuated continuously and modulation of the level setpoint is also required, for example in cascade control loops or supervisory Model Predictive Control (MPC) applications. To avoid common problems encountered when using fixed gain or adaptive/gain scheduled schemes, an accurate technique based around feedback linearization and Proportional Integral (PI) control is introduced. This simple controller can maintain linear performance over the full operating range of a uniform tank. As will be demonstrated, the implementation overhead compared to a regular PI controller is negligible, making it ideal for industrial implementation. Implementation details and parameter identification for adaptive implementation are discussed. Simulations coupled with experimental results using a large-scale laboratory level control system using commercial industrial control equipment validate the approach, and illustrate its effectiveness for both level tracking and disturbance rejection.
- Dorf, R.C. and Bishop, R.H. (2004) Modern Control Systems. 10th Edition, Prentice-Hall, Englewood Cliffs, NJ.
- Smith, R.S. and Doyle, J. (1988) The Two Tank Experiment: A Benchmark Control Problem. Proceedings of the American Control Conference, Atlanta, 15-17 June 1988, 403-415. https://doi.org/10.23919/ACC.1988.4790058
- Liptak, B.G. (2005) Instrument Engineers’ Handbook Volume Two: Process Control and Optimization. 4th Edition, CRC Press, Boca Raton, 2464 p. https://doi.org/10.1201/9781420064001
- Bolton. W. (2015) Instrumentation and Control Systems. 2nd Edition, Elsevier, Amsterdam. https://doi.org/10.1016/B978-0-08-100613-9.00004-3
- Camacho, E.F. and Bordons, C. (2004) Model Predictive Control. 2nd Edition, Springer Verlag, Berlin.
- Cartes, D. and Wu, L. (2005) Experimental Evaluation of Adaptive Three-Tank Level Control. ISA Transactions, 44, 283-293. https://doi.org/10.1016/S0019-0578(07)60181-5
- Short, M. and Abugchem, F. (2017) A Microcontroller-Based Adaptive Model Predictive Control Platform for Process Control Applications. Electronics, 6, 88. https://doi.org/10.3390/electronics6040088
- Xiao, Q.H., Zou, D.Q. and Wei, P. (2010) Fuzzy Adaptive PID Control of Tank Level. 2010 International Conference on Multimedia Communications, Hong Kong, 7-8 August 2010, 149-152.
- Sislin, R., Da Silva, F.V., Gedrite, R., Jokinen, H. and Rajan, D.K. (2016) Mathematical Modeling and Development of a Low Cost Fuzzy Gain Schedule Neutralization Control System. Engineering Letters, 26, 353-357.
- Wang, M. and Crusca, F. (2002) Design and Implementation of a Gain Scheduling Controllerfor s Water Level Control System. ISA Transactions, 41, 323-331. https://doi.org/10.1016/S0019-0578(07)60091-3
- Vilanova, R., Alfaro, V.M. and Arrieta, O. (2011) Analytical Robust Tuning Approach for Two-Degree-of-Freedom PI/PID Controllers. Engineering Letters, 19, 204-214.
- Slotine, J.J. and Li, W. (1988) Applied Non-Linear Control. Pearson Education, London.
- Astrom, K.J. and Wittenmark, B. (1995) Adaptive Control. 2nd Edition. Addison Wesley, Boston.
- Short, M. (2012) Fast Online Identification of Low-Order Time-Delayed Industrial Processes. Electronics Letters, 48, 152-153. https://doi.org/10.1049/el.2011.3400
- Kamiyama, T., Tamura, M., Soeda, T., Yoo, M. and Yokoyama, T. (2012) An Embedded Control Software Development Environment with Simulink Models and UML Models. IAENG International Journal of Computer Science, 39, 261-268.