{"title":"Adaptive Fuzzy Control of a Nonlinear Tank Process","authors":"A. R. Tavakolpour-Saleh, H. Jokar","volume":110,"journal":"International Journal of Mechanical and Mechatronics Engineering","pagesStart":416,"pagesEnd":425,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/10004167","abstract":"
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.<\/p>\r\n","references":"[1]\tFrank M. White, \u201cFluid Mechanics\u2019\u2019, McGraw Hill, 2011.\r\n[2]\tD. Haramniwas, A. Ahmad, V. Redhu and U. Gupta, \u201cLiquid Level Control by Using Fuzzy Logic Controller\u201d, International Journal of Advances in Engineering & Technology, vol.4, 2012, pp. 537-549.\r\n[3]\tR. Arivalahan, S. Hosimin Thilagar and D. Devaraj, \u201cInvestigation of Fuzzy logic controller for conical tank process\u201d, European Journal of scientific Research, vol.92, N0 2, 2012, pp. 191-202.\r\n[4]\tM. Suresh, G. J. Srinivasan, R. R. Hemamalin, \u201cIntegrated Fuzzy Logic Based Intelligent Control of Three Tank system\u201d, Serbian Journal of Electrical Engineering, vol. 6, No. 1, 2009, pp. 1-13.\r\n[5]\tM. Disha, P. K. Pandey and R. Chug, \u201cSimulation of Water Level control in a Tank using Fuzzy logic\u201d, IOSR Journal of Electrical and Electronics Engineering, vol. 2, No 3, 2012, pp. 09-12.\r\n[6]\tD. Dinesh Kumar, B. Meenakshipriya, \u201cDesign and Implementation of Nonlinear System Using Gain Scheduled PI controller, Procedia Engineering, 2012.\r\n[7]\tK. Barriljawatha, \u201cAdaptive control Technique for Two Tank Conical Interacting System\u201d, International Conference on Computing and Control Engineering (ICCCE), 2012.\r\n[8]\tD. I. H. Barr, H. R. Wallingford (Firm), \u201cTables for the Calculation of Friction in Internal Flows\u2019\u2019, Thomas Telford, 1995.\r\n[9]\tM. N. Mahyaddin, M. Rizal Arshad and Z. Mohammad, \u201cSimulation of Direct Model Reference Adaptive control on a Coupled \u2013Tank System Using Nonlinear Plant Model\u201d, International conference on control, Instrumentation and Mechatronics Engineering, 2007, pp. 560-576.\r\n[10]\tR. Molhotra, N. Singh, Y. Singh, \u201cFuzzy Logic Modeling, Simulation and Control: A Review\u2019\u2019, International Journal of Computer Science and Technology, Vol. 1, Issue 2, 2010, pp. 183-188.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 110, 2016"}