iosr-JEEE   Volume-2 ~ Issue-3

Abstract: As people over the world continue to search for renewable energy sources, innovative and interesting ideas for generating power are constantly being devised. Those interested in keeping fit and doing exercise in a day to day life, they are using various equipments to burn their calories. Now-a-days spin bike was commonly used in gym as well as home for fitness purpose. In that 4-5 kcal/min of human calories is wasted without any usage. To know the fitness level of human can be find out through laboratory based Vo2 Max test. This is much costly and needs more complex equipments The objective of the project is to generate the power from the spin bike and to find out the fitness level of human by conducting VO2 max Level test. In this project, the ergo meter cycle is coupled with the PMDC generator which will produce the electrical power when we pedal the cycle. Due to the rotational movement of wheel the generator start rotating and cut the magnetic flux, an EMF get induced. The voltage produced by the bike can be stored in a battery. The heartbeat of the person can be obtained from the heart beat sensor which is used to find the v2 max level of the person. Here the Lab VIEW is used for monitor and control the various parameters of bike such as Calories burned, VO2 max level, heart rate, MET, BMI, Power, battery Status, Speed, Workout Time and Distance.

[1] http://en.wikipedia.org/wiki/VO2_max
[2] http://stevejenkins.com/blog/2012/05/knowing-myself-part-deux-and-updated-vo2-max-data-from-cycling-test/
[3] http://pedalpowergenerator.com/how-to-build-a-bicyle-generator-free-power.html.
[4] http://www.brianmac.co.uk/astrand.html.
[5] http://www.topendsports.com/testing/tests/astrand.htm
[6] ASTRAND,P.O.& RHYMING,I.(1954) a monogram for calculate the aerobic capacity
[7] MACKENZIE .B.(2007) Astrand 6 minute cycle test

Abstract: In our enhancing world power production is very less and the power production causes many factors. So we should manage power with efficient way and should reduce power wastage. Use the power in proper manner. And also we need a source that will not affect our environment. Need of power in our world is very high, so for producing electricity some renewable energy sources are required. This type of renewable source is "RUBBER ANACONDA". Wave power is used to produce electricity from this rubber anaconda. Let us peep inside the real world of Rubber Anaconda. This is one of the renewable energy using wave power. In this a rubber tube is used to produce power. In the rubber tube both ends are closed and one end of the tube connected with turbine and generator. Wave energy from the sea is converted inside the rubber as kinetic energy. This kinetic energy is used to drive the turbine and the turbine shaft is connected with the generator from that we produce electricity. This electricity is taken outside via cable. The production of power by using this anaconda is very low cost. Electricity produced from anaconda is capable of supplying power for more than 2000 houses. Since water in the sea will not shrunken till the end of the mankind, the production of power will be continuous.

[1] Farley, F.J.M., 1982 Wave energy conversion by flexible resonant rafts Appl. Ocean Res, 4 1, 57-63
[2] Farley, F.J.M., 2006 Buckling beam wave energy converter. British Patent Application
[3] Farley, F.J.M. & Rainey, R.C.T., 2006 Distensible tube wave energy converter. British Patent Application
[4] Lamb, H. 1932 Hydrodynamics, 6th Ed. CUP.
[5] Lighthill, M.J. 1978 Waves in Fluids. CUP.

Abstract: In control systems there are a number of generic systems and methods which are encountered in all areas of industry and technology. From the dozens of ways to control any system, it turns out that fuzzy is often the very best way. The only reasons are faster and cheaper. One of successful application that used fuzzy control is water tank level control. The purpose of this project is to design a simulation system of fuzzy logic controller for water tank level control by using simulation package which is Fuzzy Logic Toolbox and Simulink in MATLAB software. In order to find the best design to stabilize the water level in the system, some factors will be considered. For this project, the water level was controlled by using three rules of membership function which then extended to five rules and seven rules for verification purpose and further improvement of the system. Besides that, several of different methods also been used in order to design the most stabilize system and this project was focused to the software part only. By doing some modification of this project, the design will be very useful for the system relates to liquid level control that widely use in industry nowadays.

[1] Fuzzy PID Supervision for a Nonlinear, System: Design and Implementation Multimedia Communications (Mediacom), 2010 International Conference on, Date of Conference: 7-8 Aug. 2010 Author(s): Qianhua Xiao Dept. of Inf. Eng., Nanchang Univ., Nanchang, China Deqiong Zou ; Ping Wei
[2] Fuzzy PID Supervision for a Nonlinear, System: Design and Implementation Fuzzy Information Processing Society, 2007. NAFIPS '07. Annual Meeting of the North American Date of Conference: 24-27 June 2007 Author(s): Sehab, R. Pare Univ. Laval-Change, Laval
[3] Parallel distributed compensator design for process control based on fuzzy Takagi-Sugeno model Power Engineering and Automation Conference (PEAM), 2011 IEEE Date of Conference: 8-9 Sept. 2011 Author(s): Sadeghi, M.S. Control & Power Eng. Dept., Shiraz Univ. of Technol., Shiraz, Iran Farughian, A.
[4] Swarm Intelligence Based Fuzzy Controller -- A Design for Nonlinear Water Level Tank Intelligent Systems, Modelling and Simulation (ISMS), 2012 Third International Conference on Date of Conference: 8-10 Feb. 2012 Author(s): Joshani, M. Dept. of Robot. & Autom. Control, Univ. of Technol. of Malaysia, Malaysia Khalid, M. ; Yusof, R. ; Cahyadi, A.I.
[5] Development and application of a gradient descent method in adaptive model reference fuzzy control. TENCON 2000. Proceedings Date of Conference: 2000 Author(s): Naman, A.T. Electr. Eng. Dept., Univ. Malaya Abdulmuin, M.Z. ; Arof, H.
[6] Level Control in Horizontal Tank by Fuzzy Logic Controller SICE-ICASE, 2006. International Joint Conference Date of Conference: 18-21 Oct. 2006 Author(s): Tunyasrirut, S. Dept. of Instrum. Eng., Pathumwan Inst. Of Technol., Bangkok Wangnipparnto, S.
[7] L.A. Zadeh. Fuzzy
[8] Babuˇska, R., H.A.B. te Braake, A.J. Krijgsman and H.B. Verbruggen (1996). Comparison of intelligent control schemes for real-time pressure control. Control Engineering Practice 4(11), 1585–1592.
[9] Babuˇska, R., H.J.L. van Can and H.B. Verbruggen (1996). Fuzzy modeling of enzymatic Penicillin–G conversion. In Preprints 13th IFACWorld Congress, Volume N, San Francisco,USA, pp. 479–484.
[10] Babuˇska, R. and H.B. Verbruggen (1995). Identification of composite linear models via fuzzy clustering. In Proceedings European Control Conference, Rome, Italy, pp. 1207–1212.Bezdek, J.C. (1981). Pattern Recognition with Fuzzy Objective Function. Plenum Press, NewYork.