Simulation of Adaptive Neuro Fuzzy Logic Controlled Wireless Intelligent Telemetry System
Rajwinder Kaur1, Kanwalvir Singh Dhindsa2
1Er. Rajwinder Kaur, Department of Computer Science and Engineering, Baba Banda Singh Bahadur Engineering College, Fatehgarh Sahib (Punjab), India.
2Prof. Kanwalvir Singh Dhindsa, Department of Computer Science and Engineering, Baba Banda Singh Bahadur Engineering College, Fatehgarh Sahib (Punjab), India.
Manuscript received on 6 April 2014 | Revised Manuscript received on 17 April 2014 | Manuscript Published on 30 April 2014 | PP: 117-121 | Volume-3 Issue-11, April 2014 | Retrieval Number: K16230431114/14©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper presents the simulation of a telemetry system for controlling the flow of water in water tanks used in industrial process using adaptive neuro fuzzy logic with the help of “neuro fuzzy design” module in matlab .Basically three ANFIS(Adaptive neuro Fuzzy Inference System) models are taken for simulation and then compared. First model is using single input variable “level”, second model is using two input variables “level” and “flow” and third model is using three input variables “level”, “flow” and “rate”. All these three models are using Sugeno type fuzzy model because only Sugeno type fuzzy models can be simulated in neuro fuzzy design module of matlab. Thus all models are using single output variable “motorstatus” which is either “ON” or “OFF”. Simulation is performed by taking constant and linear type output membership functions as major parameters. Training and checking of models is simulated for each type of output membership functions using two optimization methods “hybrid” and “back propagation” alternatively and number of epochs is considered 30, 60 and 120 for each method.
Keywords: ANFIS, Neuro Fuzzy Design, Telemetry System, Water Level Control.
Scope of the Article: Fuzzy Logics