Adaptive Fuzzy Control of a Nonlinear Tank Process
Liquid level control of conical tank system is known to be a great challenge in many industries such as food processing, hydrometallurgical industries and wastewater treatment plant due to its highly nonlinear characteristics. In this research, an adaptive fuzzy PID control scheme is applied to the problem of liquid level control in a nonlinear tank process. A conical tank process is first modeled and primarily simulated. A PID controller is then applied to the plant model as a suitable benchmark for comparison and the dynamic responses of the control system to different step inputs were investigated. It is found that the conventional PID controller is not able to fulfill the controller design criteria such as desired time constant due to highly nonlinear characteristics of the plant model. Consequently, a nonlinear control strategy based on gain-scheduling adaptive control incorporating a fuzzy logic observer is proposed to accurately control the nonlinear tank system. The simulation results clearly demonstrated the superiority of the proposed adaptive fuzzy control method over the conventional PID controller.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1123769Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1330
 Frank M. White, “Fluid Mechanics’’, McGraw Hill, 2011.
 D. Haramniwas, A. Ahmad, V. Redhu and U. Gupta, “Liquid Level Control by Using Fuzzy Logic Controller”, International Journal of Advances in Engineering & Technology, vol.4, 2012, pp. 537-549.
 R. Arivalahan, S. Hosimin Thilagar and D. Devaraj, “Investigation of Fuzzy logic controller for conical tank process”, European Journal of scientific Research, vol.92, N0 2, 2012, pp. 191-202.
 M. Suresh, G. J. Srinivasan, R. R. Hemamalin, “Integrated Fuzzy Logic Based Intelligent Control of Three Tank system”, Serbian Journal of Electrical Engineering, vol. 6, No. 1, 2009, pp. 1-13.
 M. Disha, P. K. Pandey and R. Chug, “Simulation of Water Level control in a Tank using Fuzzy logic”, IOSR Journal of Electrical and Electronics Engineering, vol. 2, No 3, 2012, pp. 09-12.
 D. Dinesh Kumar, B. Meenakshipriya, “Design and Implementation of Nonlinear System Using Gain Scheduled PI controller, Procedia Engineering, 2012.
 K. Barriljawatha, “Adaptive control Technique for Two Tank Conical Interacting System”, International Conference on Computing and Control Engineering (ICCCE), 2012.
 D. I. H. Barr, H. R. Wallingford (Firm), “Tables for the Calculation of Friction in Internal Flows’’, Thomas Telford, 1995.
 M. N. Mahyaddin, M. Rizal Arshad and Z. Mohammad, “Simulation of Direct Model Reference Adaptive control on a Coupled –Tank System Using Nonlinear Plant Model”, International conference on control, Instrumentation and Mechatronics Engineering, 2007, pp. 560-576.
 R. Molhotra, N. Singh, Y. Singh, “Fuzzy Logic Modeling, Simulation and Control: A Review’’, International Journal of Computer Science and Technology, Vol. 1, Issue 2, 2010, pp. 183-188.