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A two dimensional model of Series RLC circuit is considered for discussion. The system possess only the trivial equilibrium point and local stability conditions are obtained. The phase portraits are obtained for suitable parameter values. Oscillations and damping effects are illustrated with numerical examples.

Keywords : LCR Circuit, Differential Equations, Oscillation, Numerical Simulation, Stability

Recent

[1] R.Murali and A. PonmanaSelvan, “Ulam stability of a LCR Electric Circuit with Electromotive Force”, Int. J. Math. and its Appl., 6(1)(2018), (special Issue), 61-66. [2] V.K.Mehta, Rohit Mehta, “Principles of Electronics”, S.Chand& Company Pvt.Limited, Eleventh Edition, ISBN-81-219-2450-2, 2013. [3] R.S.Sedha, “A Textbook of Applied Electronics”, S.Chand& Company Pvt.Limited, Third Edition, ISBN-81-219-2783-8, 2012. [4] Dennis G. Zill, “A First Course in Differential Equations with Modelling Applications”, Brooks/cole, ISBN-13: 978-0-495-10824-5, ISBN-10: 0-495-10824-3, Ninth Edition, 2009. [5] https://en.m.wikipedia.org/wiki/RLC circuit

In today's day to day life, it is very difficult to have free to stay relaxed while doing work. According to the research of 48% slip disk problem can occurs in workers due to only standing work. There is a need to have arrangement such that when worker get free time and during working can sit and relax. Therefore the idea of chair less chair comes in picture. It gives ability to sit anywhere and everywhere. One can easily walk or even can run with this chair, and can easily sit when get some free time. This new concept is very useful for the industrial worker, farmers, and old peoples. In this paper we will study the basic formation of this chair less seating arrangement. This paper illustrates the results followed by design consideration.

Keywords : Chair less seating, Worker Wight, Design Cylinder and Lever Arm, Load, Deflection

Recent

[1] Nancy Owano “Chair less chair solution offered as leg exoskeleton for work” 22 Aug 2010, [2] Suhail.P.S., Akhil.R, MuhammedAfsal, M. A, Premkrishan, “Fabrication and Analysis of Chair less Chair” P B. Tesh Student Dept. Of Mechanical Engineering College, Edathala, Kerala, India [3] “Design And Development Of Lower Body” Exoskeletons A.A.Shan, M.M Awang, Z. Azraee, A. Allias , Faculty Of Mechanical Engineering, University Malaysia Pahang 26600 Pekan (11 Dec 2015.) [4] Development & Control of a soft Actuated Exoskeleton for Use in Physiotherapy &Traninin N. G. Tsagarakis, University of Salford Manchester Netherlands UK 2003 [5] The Roboknee an Exoskeleton for Enhancing Strength and Endurance during Walking. Jerry E. Pratt (IEEE April 2004) [6] “Design and fabrication of Exoskeleton Based Hydraulic Support” Cyril Varghese, Vedakasha Joshi, LokmanyTilAK College of Engineering Dept. of Mechanical Engineering Koparkhairane [7] T. Yuvarajan Naidu, M. Syafiq, M. Fikri, Ebrahim M, M. Haeiz “Design & Improvement of Lower Body”Automotive Engineering Research Group, University Malaysia Pahang 26600 Malaysia (May 2016) [8] Jie Zhao, Jun Zhong, Jizhuang Fan “Position Control of a Pneumatic Muscale Actuator Using RBF Neural Neteork Tuned PID Controller” statekay laboratory of Robotic & system, Harbin Institute Of Technology Harbin 15001, China (March 2015) [9] Work-Related Musculoskeletal Disorders (Wrmsds) Statistics In Great Britain 2017 [10] Design And Analysis of Lower Limb Exoskeleton N. Siva Nagamani V. Mohan SrikanthPG Student Assistant Professor Department of Mechanical Engineering Department Of Mechanical Engineering Gudlavalleru Engineering College Gudlavalleru Engineering College D. Tarun Assistant Professor Department Of Mechanical Engineering Gudlavalleru Engineering College [11] ‘VIRTUAL CHAIR: An Exoskeleton’ Mithil R. Mogare1, Sugat S. Sravasti2, Rushikesh V. Ashtekar3, Ganesh. C. Sovani4 Former Students of Kolhapur Institute of Technology’s College Of Engineering GokulShirgaon, Kolhapur, Maharashtra, India. [12] BookMachine Design by R.S.KHURMI Book

The main element for load forecasting is power system energy management system. Load forecasting helps to reduce the generation cost, spinning reserve capacity and increase the reliability of power system. The unit commitment, economic allotment of generation preservation schedule is crucial for short term load forecasting. In present many techniques have been used for load forecasting, but Artificial Intelligence Technique (Fuzzy Logic and ANN) gives better efficiency as contrast to conventional technique (Regression and Time Series). In this paper, the author main purpose is to reduce the error in the middle of the forecasted load and actual load value. The paper represents a technique of short term load forecasting using fuzzy logic. Using mamdani implication the fuzzy rule base are prepared. The software used for this is Matlab simulink and fuzzy tool box. By using triangular membership function the forecasted load results are obtained.

Keywords : Component, Fuzzy Logic, Short Term Load Forecasting, Absolute Percentage Error, Fuzzy Interface System, Mamdani

Recent

[1] Idil Isikli Esener, Togna Yukksel, Mehmet kurban, Short term load forecasting without metrological data using AI-based structures, Turk. J. Electr. Eng. Comput. Sci. (February 2015) 370-380. [2] J. Choong, Powerful Forecasting with MS Excel, 2012, pp. 1-257. [3] Al-Kandari A, Soliman S, El-Hawary M (2004) Fuzzy short-term electric load forecasting. Int J Electr Power Energy Syst 26(2):111-122. [4] Feinberg EA, Genethliou D (2005) Load forecasting. Applied mathematics for restructured electric power systems, chap 12. Springer, New York, pp 269-285. [5] Fan S, Hyndman RJ (2012) Short-term load forecasting based on a semi-parametric additive model. Power Syst IEEE Trans 27(1):134-141. [6] Li-Xin Wang and Jerry M. Mendel,”Generating Fuzzy Rules by Learning from Examples” 1991 IEEE international Symposium. [7] Engr. Badar Ul Islam, Head of Department Computer Science & Engineering, NFC-Institute of Engineering & Fertilizer Research, Faisalabad – Pakistan, “Comparison of Conventional and Modern Load Forecasting Techniques Based on Artificial Intelligence and Expert Systems”, IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 5, No 3, September 2011. [8] Su, Yuan-Yih, and Chien-Chuen Yang. "Design of artificial neural networks for short-term load forecasting. Part 1: Self-organising feature maps for day type identification." In IEE Proceedings C (Generation, Transmission and Distribution), vol. 138, no. 5, pp. 407-413. IET Digital Library, 1991.E. [9] D K Ranaweera, N F Hubele and & G G Karady, “Fuzzy logic for short term load forecasting”, IEEE Electrical Power & Energy Systems Vol. 18 No. 4, pp. 215-222, 1996. [10] Wang Feng Yu Er Keng Liu Yong Qi Liu Jun Yan Chen Shan, “Short-term Load Forecasting Based On Weather Information” IEEE 1997.