Abstract
The presence of hard nonlinearities, such as control valve stiction, may severely degrade the plant profitability by introducing limit cycles in the process variable. This paper presents an innovative use of a recently developed intelligent controller for effective ratio control in the presence of a sticky control valve. The intelligent controller, stiction combating intelligent controller (SCIC), is inherently a fuzzy controller which makes use of Takagi–Sugeno model and changes its gain in run time to deal with stiction nonlinearity. Some of the various advantages which SCIC controller offers are, its simple structure, non-requirement of process parameters’ estimation and its capability to provide standalone solution to stiction nonlinearity. These qualities of SCIC controller make it a front runner among other solutions, for the effective ratio control in the presence of a sticky pneumatic control valve. The efficacy of the SCIC controller in ratio control is experimentally verified on a laboratory scale plant with uncertain parameters. A performance comparison between SCIC and linear proportional integral (PI) controller is also made for their setpoint tracking, disturbance rejection and trajectory tracking capabilities at various operating points. Based on extensive experimental studies, it can be concluded that SCIC controller, undoubtedly, outperformed the linear PI controller for all investigated cases and also efficiently handled uncertainties in the plant parameters.
Similar content being viewed by others
References
Choudhury M.A.A.S., Jain M., Shah S.L.: Stiction-definition, modelling, detection, quantification. J. Process Control 18(3-4), 232–243 (2008)
Mishra P., Kumar V., Rana K.P.S.: A novel intelligent controller for combating stiction in pneumatic control valves. Control Eng. Pract. 33, 94–104 (2014)
Armstrong-Hèlouvry B., Dupont P., De Wit C.C.: A survey of models, analysis tools and compensation methods for the control of machines with friction. Automatica 30(7), 1083–1138 (1994)
Kayihan A., Doyle F.J.: Friction compensation for a process control valve. Control Eng. Pract. 8(7), 799–812 (2000)
Gerry, J.; Ruel, M.: How to measure and combat valve stiction online. Instrumentation, systems and automation society. http://www.expertune.com/articles/isa2001/StictionMR.htm (2014). Accessed 10 Dec 2014
Hägglund T.: A friction compensator for pneumatic control valves. J. Process Control 12(8), 897–904 (2002)
Srinivasan R., Rengaswamy R.: Approaches for efficient stiction compensation in process control valves. Comput. Chem. Eng. 32(1-2), 218–229 (2008)
Farenzena, M.; Trierweiler, J.O.: Modified PI controller for stiction compensation. In: Proceedings of the 9th International Symposium on Dynamics and Control of Process Systems (DYCOPS 2010), Leuven, Belgium, pp. 791–796 (2010)
Mohammad M.A., Huang B.: Compensation of stiction through controller tuning. J. Process Control 22(9), 1800–1819 (2012)
Cuadros M.A.D.S., Munaro C.J., Munareto S.: Improved stiction compensation in pneumatic control valves. Comput. Chem. Eng. 38, 106–114 (2012)
Mokayed H., Mohamed A.H.: A robust thresholding technique for generic structured document classifier using ordinal structure fuzzy logic. Int. J. Innov. Comput. Inf. Control 10(4), 1543–1554 (2014)
Wang L.X., Mendel J.M.: Fuzzy basis functions, universal approximation and orthogonal least-squares learning. IEEE Trans. Neural Netw. 3(5), 807–814 (1992)
Ziegler J.G., Nichols N.B.: Optimum settings for automatic controllers. Trans. ASME 64(11), 759–765 (1942)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Mishra, P., Kumar, V. & Rana, K.P.S. Intelligent Ratio Control in Presence of Pneumatic Control Valve Stiction. Arab J Sci Eng 41, 677–689 (2016). https://doi.org/10.1007/s13369-015-1853-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13369-015-1853-0