Document Type: Research Paper


1 Northern india Engineering College, GGSIP University, New Delhi.

2 Mechanical Engineering Department, The NorthCap University, Gurugram - 122017, India

3 Division of Instrumentation and Control Engineering, Netaji Subhas Institute of Technology, New Delhi - 110078, India


Inherent nonlinearities like, deadband, stiction and hysteresis in control valves degenerate plant performance. Valve stiction standouts as a more widely recognized reason for poor execution in control loops. Measurement of valve stiction is essential to maintain scheduling. For industrial scenarios, loss of execution due to nonlinearity in control valves is an imperative issue that should be tackled. Thus, an intelligent technique is required for automated execution, observation and enhancement. The paper shows the creative utilization of an intelligent controller for nonlinearity diagnosis in control valves. This is a Fuzzy Gain Scheduling (FGS) PID smart controller that tunes its gain parameters in real time to manage a control valve’s inherent nonlinearity. The viability of the FGS PID controller is experimentally verified in a laboratory scale plant. An execution comparison between FGS PID and classical PID controllers are undertaken for their set point following and disturbance rejection at different operating points. Experimental results show that the FGS PID controller outperforms the classical PID controller for all explored cases effectively managing stiction based oscillation in the controller output.

Graphical Abstract


Main Subjects

[1]     M. S. Choudhury, M. Jain, and S. L. Shah, “Stiction–definition, modelling, detection and quantification”, Journal of Process control, Vol. 18, No. 3, pp. 232-243, (2008).


[2]     Puneet Mishra, Vineet Kumar, and K. P. S. Rana. “A novel intelligent controller for combating stiction in pneumatic control valves”, Control Engineering Practice, Vol. 33, pp. 94-104, (2014)


[3]    M. Jelali, Huang and B. Eds, “Detection and diagnosis of stiction in control loops: state of the art and advanced methods”, Springer Science & Business Media, (2009).


[4]     Tore Hägglund, “A control-loop performance monitor”, Control Engineering Practice, Vol. 3, No.11, pp. 1543-1551, (1995).  


[5]     N. F. Thornhill, B. Huang, and  H. Zhang, “Detection of multiple oscillations in control loops”, Journal of Process Control, Vol. 13, No. 1, pp. 91-100, (2003).


[6]     T. Matsuo, H. Sasaoka, and Y. Yamashita, “Detection and diagnosis of oscillations in process plants”, International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, Springer Berlin Heidelberg. pp. 1258-1264, (2003).


[7]     M. Jelali, “Estimation of valve stiction in control loops using separable least-squares and global search algorithms”, Journal of Process Control, Vol. 18, No. 7, pp. 632-42, (2008).


[8]     S. Karra and M. N. Karim, “Oscillatory Control Loops: The Lost Economic Benefits. Can Anything Be Done?”, In Proceedings of the Process Control and Optimization, AIChE Spring Meeting, (2009).


[9]     D. Beckman, “Reducing process variability with control valves-Improving dynamic response times”, Chemical processing, Vol. 60, No. 11, pp. 42-46, (2008).


[10]   Ranganathan Srinivasan and Raghunathan Rengaswamy, “Stiction compensation in process control loops: A framework integrating stiction measure and compensation”, Industrial and engineering chemistry research. Vol. 44. No. 24, pp. 9164-9174, (2005).


[11]   Armstrong-Hélouvry, Brian, Pierre Dupont, and Carlos Canudas De Wit, "A survey of models, analysis tools and compensation methods for the control of machines with friction", Automatica, Vol. 30, No.7, pp. 1083-1138, (1994).


[12]   Arkan Kayihan, and J. Doyle Francis, "Friction compensation for a process control valve", Control Engineering Practice, Vol. 8, No. 7, pp. 799-812, (2000).


[13]   John Gerry, and Ruel Michel, "How to measure and combat valve stiction online." ISA International Fall Conference. pp. 10-13, (2001).


[14]   Tore Hägglund, “A friction compensator for pneumatic control valves”, Journal of Process Control, Vol.12, No. 8, pp. 897-904, (2002).


[15]   Ranganathan Srinivasan and Raghunathan Rengaswamy, “Approaches for efficient stiction compensation in process control valves”, Computers and Chemical Engineering, Vol. 32, No.1, pp. 218-229, (2008).


[16]   Marcelo Farenzena, and J. O. Trierweiler, “Modified PI controller for stiction compensation.” IFAC Proceedings, Vol. 43, No. 5, pp. 799-804, (2010).


[17]   Marco Antonio de Souza L. Cuadros, Celso J. Munaro, and Saul Munareto, “Improved stiction compensation in pneumatic control valves”, Computers and Chemical Engineering, Vol. 38, pp. 106-114, (2012).


[18]   Puneet Mishra, Vineet Kumar and K. P. S. Rana, “Stiction Combating Intelligent Controller Tuning: A Comparative Study,” in Proceedings of the IEEE International Conference on Advances in Computer Engineering and Applications (ICACEA), IMS Ghaziabad, India, March 19-20, pp. 534-541, (2015).


[19]   Puneet Mishra, Vineet Kumar and K. P. S. Rana, “An online tuned novel nonlinear PI controller for stiction compensation in pneumatic control valves,” ISA Transactions, Elsevier, Vol. 58, pp. 434-445, (2015). 


[20] Puneet Mishra, Vineet Kumar, K. P. S. Rana, “A Comparative Study for Flow Control using SCIC and NPIC Controllers,” in the proceedings of 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT-17), July 3-5, IIT, Delhi, India, pp. 1-6, (2017).


[21]   Puneet Mishra, Vineet Kumar, and K. Rana. “Intelligent Ratio Control in Presence of Pneumatic Control Valve Stiction”, Arabian Journal for Science and Engineering (Springer Science & Business Media BV), Vol. 41, No. 2, (2016).


[22]   Pardeep Rohilla, Vineet Kumar and B.C. Nakra, “Investigation of Intelligent Control System for Non-Linear Real Time Pressure Control System, “International Journal of Advanced Computer Research, Vol. 5, No.19, pp.212-219, (2015).


[23]   Pardeep Rohilla, Vineet Kumar, Feras Al Hakkak, “Fuzzy I+PD controller for stiction compensation in pneumatic control valve,” International Journal of Applied Engineering Research, Vvol. 12, No. 13, pp.3566-3575, (2017)   .


[24]   Pardeep Rohilla, Vineet Kumar, Feras Al Hakkak, “Fuzzy gain scheduling of a IPD controller for oscillation compensation in a sticky pneumatic control valve,” International Journal of Mechanical Engineering and Robotics Research, Vol. 7, No. 3, pp. 240-249, (2018).


[25] R. B. di Capaci, and C. Scali, "Review and comparison of techniques of analysis of valve stiction: From modeling to smart diagnosis," Chemical Engineering Research and Design, Vol. 130, pp. 230-265, (2018).


[26]   R. B. di Capaci, C. Scali, B. Huang, “A Revised Technique of Stiction Compensation for Control Valves,” in proceedings of 11th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems, NTNU, Trondheim, Norway, pp. 1038-1043, June 6-8, (2016).


[27]   R. B. di Capaci, and C. Scali, "An augmented PID control structure to compensate for valve Stiction." IFAC-PapersOnLine, Vol. 51, No. 4, pp. 799-804, (2018).


[28]   L. Fang, J. Wang, X. Tan, “Analysis and compensation  of  oscillations  induced  by control valve tiction,” IEEE/ASME Transactions on Mechatronics, Vol. 21, No. 6, pp. 2773-2783, (2016).


[29]   Lotfi A. Zadeh, "Fuzzy sets", Information and control, Vol. 8, No. 3, pp. 338-353, (1965).


[30]   Vineet Kumar, B. C. Nakra and A.P. Mittal, “A Review of Classical and Fuzzy PID Controllers,” International Journal of Intelligent Control and Systems, Vol. 16, No. 3, pp. 170-181, (2011).


[31]   Vineet Kumar, K. P. S. Rana and Vandana Gupta, “Real-Time Performance Evaluation of a Fuzzy PI + Fuzzy PD Controller   for    Liquid-Level   Process,” International Journal of Intelligent Control and Systems, Vol. 13, No. 2, pp. 89-96, (2008).


[32]   Zhen-Yu Zhao, Masayoshi Tomizuka, and Satoru Isaka, "Fuzzy gain scheduling of PID controllers", IEEE Transactions on Systems, Man, and Cybernetics, Vol. 23, No. 5, pp. 1392-1398, (1993).


[33]   Kuhu Pal, Rajani K. Mudi, and Nikhil R. Pal, "A new scheme for fuzzy rule-based system identification and its application to self-tuning fuzzy controllers", IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), Vol. 32, No. 4, pp. 470-482, (2002).


[34]   J. G. Ziegler and N. B. Nichols, “Optimum settings for automatic controllers,” Transaction of the American. Society of Mechanical Engineers (ASME), Vol. 64, pp. 759-768, (1942).