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Volume-5 Issue-2

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Volume-5 Issue-2, May 2016, ISSN:  2277-3878 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.



Laxmi Shankar Awasthi

Paper Title:

Case Study: Business Analytical Problems

Abstract:  Now days with ever increasing size of the data and ever increasing method of the data collection, the amount of data is growing exponentially. With the downpour of such a huge amount of data from various sources, the use of automated systems and computer platforms is inevitable. The Humans are living in an information age, where the capabilities of the manual data manipulations have long been surpassed. Business Analytics aims to address such issues which are directly related to the interests of the Business. There are different types of problems, and for which there exist different solutions to tackle the specific problems.. This paper will help  to understand the existing problem by Case Study.

 Business Analytics, Machine Learning, Artificial Intelligence, Data Mining.


1.       Research In Organizational Behavior an annual series of analytical essays and critical reviews. Volume 26.
2.       Diversified business communications selects group 1 for enterprise data quality.

3.       Consumer Rights Electric, Natural Gas and Telephone(http://www.psc.state.ga.us/pscinfo/brochures/consumer_rights_brochure.pdf)






Swapnil J. Patil, V. R. Gambhire

Paper Title:

Design & Modeling of Infinite variable Transmission System Based on Constantaniesco Torque Convertor

Abstract: Infinitely variable transmission eliminates clutch and gear box for automobile and gives the required torque conversions automatically. In this paper infinitely variable transmission systems have designed and modelled based on Constantaniesco torque convertor for light to medium duty vehicles. IVT includes various parts as input and output shafts, yoke, connecting link and masses. It is necessary while designing IVT to calculate the governing parameters of the model. The study also includes the comparisons of theoretical parameters with experimental parameters as speed, torque, efficiency, power etc. on performance curves. So first of all theoretical design and calculations are carried out. Then after development of experimental set up readings are taken and calculations are carried out, from which performance parameters are plotted.

 Infinite variable transmission system, torque conversion, experimental set up, performance parameters.


1.    Timothy Cyders, Robert L. Williams II, “Analysis of a new form intrinsically automatic continuously variable transmission”, Proceedings of the ASME 2010 international design engineering technical conferences and computers and information in engineering conference IDTEC/CIE ,August 15-18,(2010).
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3.    Ion ION, “George Constantinescu torque convertor analysis by simulink”, SIMON 2007 and homogial session of the commissions of acoustics, Bucharest, 29-31 may, (2007).
4.    G. Carbone, M. Napolitano, E. Sedoni, “Design optimization of input and output coupled power split infinitely variable transmissions”, ASME journal of mechanical
design, vol. 131,(2009) .

5.    A text book “Ian Constantinesco: Geroge Constantinesco his Torque Convertor and other Inventions” (chapter 5) (1925).

6.    William T. Beale: US Patent # 7,011,322 B2: “Automatic Transmission with Steeples, Continuously Variable Speed and Torque Ratio” (2006).

7.    John G. Bolger: US Patent # 4,907,474: “Mechanical Torque Convertor” (1990).

8.    George Constantinesco: US Patent # 1,613,344: “Power Transmission” (1927).






P. Paul Clee, S.V.L. Narasimham

Paper Title:

Analyzing the Power System in the Presence of FACTS Controllers: Effect of Control Parameters

Abstract:  Now a day technological development in power electronics based controllers formerly known as Flexible AC Transmission Controllers (FACTS), the power system can operate with high security. These controllers help to enhance the transmission line loadings in terms of its thermal ratings. The line loadings and bus voltage profiles can be controlled using these FACTS controllers. To analyze the effect of the FACTS devices, these controllers should be incorporated in a given system and the load flow analysis is performed using Newton Raphson (NR) method. In this paper, very popularly used FACTS controllers known for Static VAr Compensator (SVC) and Thyristor Controlled Series Compensator (TCSC) are considered. The effect of these devices on system bus voltages, line power flows and system power losses is analyzed on standard test system such as HALE network and IEE-30 bus test systems are considered.

 Power flow analysis, SVC, TCSC, NR-load flow, Optimal location.

1.       S. N. Singh and A. K. David, “Optimal location of FACTS devices for congestion management,” Elect. Power Syst. Res., vol. 58, no. 2, pp.71–79, 2001.
2.       Y. Lu and A. Abur, “Static security enhancement via optimal utilizationof thyristor-controlled series capacitor,” IEEE Trans. Power Syst., vol.17, no. 2, pp. 324–329, May 2002.

3.       J. G. Singh, S. N. Singh, and S. C. Srivastava, “An approach for optimal placement of static VAr compensators based on reactive power spotprice,” IEEE Trans.
Power Syst., vol. 22, no. 4, pp. 2021–2029, Nov.2007.

4.       N. Acharya and N. Mithulananthan, “Locating series FACTS devices for congestion management in deregulated electricity markets,” Elect.Power Syst. Res., vol. 77, no. 3-4, pp. 352–360, 2007.

5.       M. Gitizadeh and M. Kalantar, “A novel approach for optimum allo-cation of FACTS devices using multi-objective function,” Energy Con-vers. Manage vol. 50, no. 3, pp. 682–690, 2009.

6.       R. Benabid, M. Boudour, and M. A. Abido, “Optimal location and setting of SVC and TCSC devices using non-dominated sorting par-ticle swarm optimization,” Elect. Power Syst. Res., vol. 79, no. 12, pp.1668–1677, 2009.
7.       N. Yorino, E. E. El-Araby, H. Sasaki, and S. Harada, “A new formu-lation for FACTS allocation for security enhancement against voltagecollapse,” IEEE Trans. Power Syst., vol. 18, no. 1, pp. 3–10, Feb. 2003.
8.       R. Minguez, F. Milano, R. Zarate-Minano, and A. J. Conejo, “Optimalnetwork placement of SVC devices,” IEEE Trans. Power Syst., vol. 22,no. 4, pp. 1851–1860, Nov. 2007.

9.       M. Eghbal, N. Yorino, E. E. El-Araby, and Y. Zoka, “Multi load levelreactive power planning considering slow and fast VAR devices bymeans of particle swarm optimization,” IET Trans. Gen., Transm., Dis-trib., vol. 2, no. 5, pp. 743–751, 2008.

10.    R. Zárate-Miñano, A. J. Conejo, and F. Milano, “OPF-Based securityredispatching including FACTS devices,” IET Trans. Gen., Transm.,Distrib., vol. 2, no. 6, pp. 821–833, 2008.

11.    A.E.  Guile and W.D.  Paterson, „Electrical power systems, Vol.  2‟,

12.    (Pergamon Press, 2nd edition, 1977).

13.    W.D.  Stevenson Jr., „Elements of power system analysis‟, (McGraw-Hill, 4thedition, 1982).

14.    W.  F.  Tinney, C.  E.  Hart,  "Power  Flow  Solution  by  Newton's  Method,  "IEEE  Transactions  on  Power  Apparatus  and  systems  ,  Vol.  PAS-86, pp. 1449-1460, November 1967.

15.    W.  F.  Tinney, C.  E.  Hart, “Power Flow Solution by Newton’s Method, "IEEE TRANS.  POWER APPARATUS AND SYSTEMS, Vol.  PAS-86, pp. 1449-1460, November 1967.

16.    Carpentier “Optimal Power Flows”, Electrical Power and Energy Systems, Vol.1, April 1979, pp 959-972.

17.    D.I.Sun, B.Ashley, B.Brewer, A.Hughes and W.F.Tinney, “Optimal Power  Flow by Newton Approach”,  IEEE Transactions on Power Apparatus and systems, vol.103, No.10, 1984, pp2864-2880.

18.    W. R. Klingman and D. M. Himmelblau, "Nonlinear programming with the aid of a multiple-gradient summation technique," J. ACM, vol. 11, pp. 400-415, October 1964

19.    H.  Dommel, “Digital methods for power system analysis” (in German), Arch.  Elektrotech., vol.  48, pp.  41-68, February 1963 and pp.  118-132, April 1963.

20.    D.  Das, H.S.Nagi and D.P.  Kothari  ,  “Novel  Method  for  solving  radial distribution networks,”  Proceedings IEE Part C (GTD), vol.141, no. 4, pp.291 – 298, 1991

21.    T.K.A.  Rahman  and  G.B. Jasmon,  “A  new  technique  for  voltage  stability analysis  in  a  power  system  and  improved  load flow  algorithm  for distribution
network,”  Energy  Management  and  Power  Delivery Proceedings of EMPD '95; vol.2, pp.714 – 719, 1995.






Sabri M. Ben Mansour, Jawhar Ghommam, Saber M. Naceur

Paper Title:

Design and Visio Control for Navigation and Obstacles Detection Based on Color and Texture Attributes of Two-Wheeled Mobile Robot

Abstract: This paper addresses Visio and path following control problem of a nonholonomic Two-Wheeled Inverted Pendulum Mobile Robot. We propose control architecture based on two control layers. A speed inner loop control scheme is first designed based on state feedback technique to ensure stability of the inverted structure of the robot. A second outer loop control scheme is proposed to help the robot navigate along a desired path formed by a set of way points. It is designed inspiring the model predictive control technique. The elements of the predictive control, which are the cost function, controls and constraints, must be defined and specified: the use of different trajectories group in the control can adapt the behavior of the robot to different displacement phases. The obstacle detection architecture based on the attributes of color and texture has been developed to be implemented on an Raspberry PI and is designed as a generic high-speed image processing device. The optimization criteria are based on a maximization of performance in terms of image processing per second and a minimization of consumed resources. Our obstacles detection algorithm consists of three main steps: the color transformation, the calculation of the color and texture attributes and their classification.

 Mobile robot, navigation, stability, Predictive control, Obstacles detections, Image processing


1.        Grasser F, D’arrigo A, Colombi S and Rufer A. Joe: A  Mobile Inverted Pendulum:IEEE Transaction on Industrial Electronics;2002.
2.        Ooi R C. Balancing a Two-Wheeled Autonomous Robot: Final Year Thesis: The University of Western Australia School of Mechanical Engineering, Faculty of Engineering and Mathematical Sciences University of Western Australia, Australia;2003.

3.        Ho K C R. Balancing Wheeled Robot: Research Project, University of Southern Queensland, Australia; 2005.

4.        Grepl R. Balancing Wheeled Robot: Effective Modelling, Sensory Processing And Simplified Control: Engineering Mechanics, 16 (2), pp.141–154;2009.

5.        Takita Y, Date H and Shimazu H. Competition of Two-wheel Inverted Pendulum Type Robot Vehicle on MCR Course: The 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems,5578-5584; 2009.

6.        Chee Y O and Abidin M S Z. Design and Development of Two Wheeled Autonomous Balancing Robot; Student Conference on Research and Development; 2006.

7.        Nawawi S W, Ahmad M and Osman J H S. Real-Time Control of a Two-Wheeled Inverted Pendulum Mobile Robot: World Academy of Science, Engineering and Technology,214-220; 2008.

8.        Tsai C, Chan C and Fan Y H. Planned Navigation of a Self-balancing Autonomous Service Robot: IEEE International Conference on Advanced Robotics and Its Social Impacts, vol 6764; 2008.

9.        Latombe J.C Kluwer,Robot Motion Planning: Academic Publishers, Boston;1991.

10.     Choset. Sensor Based Motion Planning the Hierarchical Generalized Voronoi Graph” Phd thesis,  California Institure of Technology;1996.

11.     Chazzzelle and Guibas.Visibiliy and ontersection problems in plane geometry” , Discrete and  Computational Geometry;2000

12.     Shin and McKay. A dynamic programming approach to trajectory planning of the robotic manipulators”, IEEE Transactions on Automatic Control;1996.

13.     Hart, A Formal Basis for the Heuristic Determination of Minimum Cost Paths” , IEEE Transactions on Systems Science and Cybernetics;1986.

14.     Stentz and Anthony, Optimal and Efficient Path Planning for Partially-Known Environments, Proceedings of the International Conference on Robotics and Automation;1994.

15.     Defoort, Motion planning for cooperative unicycle-type mobile robots with limited sensing ranges, A distributed receding horizon approach , Robotics and Autonomous Systems;2009.

16.     ŠKRJANC, Igor, BLAŽIČ, Sašo, Predictive functional control based on fuzzy model : design and  stability study”, Journal of intelligent & robotic systems, ISSN 0921-0296, 2005, vol. 43, pp. 283-299 ;2005.

17.     KLANČAR, Gregor, ŠKRJANC, Igor, A case study of the collision-avoidance problem based on Bernstein-Bézier path tracking for multiple robots with known constraints”. Journal of intelligent &  robotic systems, ISSN 0921-0296, Nov. 2010, vol. 60, no. 2, pp. 317-337, ilustr., doi: 10.1007/s10846-010-9417-8;2010.

18.     Micaelli A. Trajectory tracking for unicycle-type and two-steering-wheels mobile robots: Sophia-Anitpolis, France: Institut National de Recherche en Automatique er en Automatique; 1993.

19.     Hu J S, Tsai M C, Hu F R and Hori Y. Robust Control For Coaxıal Two-Wheeled Electrıc Vehıcle: Journal of Marine Science and Technology, pp 172-180;2010.

20.     Chi G, Hausbach J and Hunter B. Segbot: Senior Design Project, University of Illinois at Urbana-Champaign, USA ; 2005.

21.     Bock H.G and Plitt K. A multiple shooting algorithm for direct solution of optimal control problems. 9th IFAC world congress Budapest. Pergamon Press; 1984.
22.     Klancar G, Skrjanc I. Tracking-error model-based predictive control for mobile robots in real time: Robotics and Autonomous Systems; 2007.
23.     Courtial E. Commande predictive et estimation d’état de systèmes non linéaires : Rapport de thèse université Claude Bernard – Lyon ;1996.

24.     Vallius T and Röning J. Embedded Object Concept: Case Balancing Two-Wheeled Robot: Proceedings of the SPIE, Vol. 6764; 2007.

25.     Bak M. Poulsen K, Ravn O. Path Following Mobile Robot in the Presence of Velocity Constraints: Kongens Lyngby, Denmark : Technical University of Denmark; 2000






Khan Zubair Zahoor, Shaikh Mohamedali A.R., Shaikh Arman Naseem, Shaikh Fuzelahmed  Mahabubali, Shaikh Shahrukh Shahid

Paper Title:

Design and Fabrication of Thal Pump

Abstract:  Thal-pump is a type of   infusion pump that is used for injecting iron chelating agent into the body of a patient suffering from Thalassemia disease. Currently the device used for treatment of Thalassemia patients in India is imported from European countries like Denmark and because of the import duty the cost of this equipment is considerably high(approx 50,000 INR) which makes it unaffordable to many hospitals in India. Similar desired output of Thal-pump has been developed by us with a total cost of 6,000 INR. The main objective of the Thal-pump is to inject the iron chelating agent at  a desired rate (ranges from 0.5ml/hr to 10ml/hr) with high precision. This paper explains the working of the Thal-pump based on the application of Mechatronics wherein the injecting rate of the chelating agent depends on the stepper motor speed used. The speed of this stepper motor is controlled through circuits governed by an arduino sketch. The discharge rate of Thal-pump can be varied and because of this it has different medical applications.

 (ranges from 0.5ml/hr to 10ml/hr), (approx 50,000 INR), 6,000 INR.

1.    Machine design by V. B. Bhandari


2.    http://micrelmed.com/

3.    www.wikipedia.com

4.    www.nhlbi.nih.gov





Santosh S.K, Shivashankar S.B, Noushad K.R, Kishan N.K, S.G. Goudar, Prabhu, K.

Paper Title:

An Experimental Study on Laterally Loaded Piles in Sand

Abstract:   The behaviour of pile under lateral load is studied through laboratory experiments on model cemented group of piles driven into testing tank containing dry river sand. The load-displacement diagrams were drawn to study the effect of strength comparison between the group of cemented piles and different densities of sand on the lateral load capacity of pile. It was found that the lateral load capacity of piles increases with increase in number of piles and increase in sand density. It is also found that lateral load capacity is more in high density sand as compared to that of low density sand.

  ultimate lateral load capacity, cemented pile, sand.


1.    Boominathan, A., and Ayothiraman R. (2007) “An experimental study on static and dynamic bending behaviour of piles in soft clay”, Journal of Geotechnical and Geoenvironmental Engineering, Vol. 25,No. 2, pp. 177 – 189.
2.    Gandhi, S. R., and Selvan, S. (1997) ‘‘Group Effect on Driven Piles Under Lateral Load’’ Journal of Geotechnical and Geoenvironmental Engineering, Vol. 123, No. 8, pp. 702 – 709.

3.    Fan, C. C., and Long, J. H. (2005) ‘‘Assessment of Existing Methods for Predicting Soil Response of Laterally Loaded Piles in Sand’’ Computers and Geotechnics, Vol. 32, pp. 274-289.

4.    IS: 2720 (Part 4) – 1985, Methods of Test for Soils: Grain Size Analysis, Bureau of Standards, New Delhi, India.
5.    IS 2720 (Part 13) – 1972, Method of Test for soils: Direct Shear Test (Second Revision), Bureau of Standards, New Delhi, India.
6.    IS: 2911-IV (1985), “Indian Standard code of practice for design and construction of pile foundations”, Part 4, Load test on piles, Bureau of Standards, New Delhi, India.

7.    Kim, B. T., Kim, N. K., Lee, W. J., and Kim, Y. S. (2004) “Experimental Load–Transfer Curves of Laterally Loaded Piles in Nak-Dong River Sand”, Journal of Geotechnical and Geoenvironmental Engineering, Vol. 130, No. 4, pp 416 – 425.

8.    Ranjan, N. P., and Jagannath, P. P. (2001) “Ultimate Lateral Resistance of Pile Groups in Sand”, Journal of Geotechnical and Geoenvironmental Engineering, Vol.127,
No.6, pp.481 – 486.

9.    Som, N. N. and Das, S. C. (2003) “Theory and Practice of Foundation Design”, Prentice Hall of India Private Limited, New Delhi, pp 232-250.






Chetan.B.P, Irana.K, Raghavendra.K.S, Shivabasava.M.P, S.G.Goudar, Prabhu, K

Paper Title:

Behaviour of Uplift Capacity of Piles in Sand

Abstract: Understanding the pile behavior and predicting the capacity of piles under uplift loading are important topics in foundation design. Experimental model tests have been conducted on single piles and pile groups embedded in cohesion less soil and subjected to pure uplift loading. The piles are made up of cement.  The influences of pile embedment depth, relative density of soil, and arrangement of piles in a group on the uplift capacity of piles are investigated. The study revealed that the behavior of single piles under uplift loading depends mainly on both the pile embedment depth-to-diameter ratio and the soil property . When the net uplift load per pile in a group is equal to a single pile load, the upward displacement increased in the pile group due to interaction effects between piles. The obtained group efficiency under uplift loading is illustrated and found to be in a good agreement with previous studies.

 cemented pile, sand. Testing tank


1.       Birger Schinidt (1987). Pull Out Capacity of Single Batter Pile in Sand. Canadian Geotechnical Journal. 24. pp. 467-468.
2.       Chattopadhyay and Pise, P.J. (1986a). Uplift Capacity of Pile in Sand. Journal of the Geotechnical Engineering Division ASCE. 112. No. 9 paper No. 20919.

3.       Clemence, C.P. and Brumund, W.F. (1975). Large Scale Model Test of Drilled Piers in Sand. Journal of the Geotechnical Engineering Division ASCE. 101. GT.6.paper No. 11369.

4.       Das, B. M. (1983). A Procedure for Estimation of Uplift Capacity of Rough Piles. Journal of Soil and Foundation Division ASCE. 109. No.3. pp. 122-126.

5.       Das, B. M. and Seeley, G. R. (1975b). Uplift capacity of buried model pile in Sand.

6.       Journal of the Geotechnical Engineering Division ASCE. 101. No. 20. pp. 1091-1094.

7.       Dickin, E.A. and Leung, C.F. (1990). Performance of Pile With Enlarge Base Subject to Uplift Force. Canadian Geotechnical Journal. 27. pp. 546-556.

8.       Meyerhof, G. G. and Adams (1968). The Ultimate Uplift Capacity of Foundations.

9.       Canadian Geotechnical Journal. 5. No. 4. Nov. pp. 225-244.

10.    Dickin, E.A. and Leung, C.F. (1992). The Influence of Foundation Geometry on the Uplift Behavior of Pile With Enlarge Bases. Canadian Geotechnical Journal. 29. pp. 498-505.

11.    Zheng zhang (2009), “Simplified nonlinear analysis methods for vertically loaded piles and piled raft in layered soil” Brdge science research institute, civil eng. Dalian university of technology, Dalian, Vol.14.

12.    Basu .D, Salgado .R, Prezzi.M, Lee.J and Paik.K “Recent advances in the design of axially loaded piles in sandy soils” GSP 132 Advances in deep foundation, ASCE, 2012.

13.    Poulos.G.H (1989), “Cyclic axial loading analysis of piles in sand” Journal of geotechnical and geo environmental engineering, ASCE, Vol.115. No.6, 1989.

14.    Indian Standard-IS: 2720 (Part 3)1980 “Methods of test for soils, determination of specific gravity, fine, medium and coarse grained soils", New Delhi.

15.    Indian Standard-IS: 2720 (Part 4)-1985 “Methods of test for soils, grain size analysis-mechanical method”, New Delhi

16.    IS: 2386 (Part III) – 1963 “Part III Specific Gravity, Density, Voids, Absorption and Bulking” Indian standard methods of test for aggregates for concrete.

17.    2911 (Part4)-1985 “Part 4 Load Test on Piles” Indian Standard Code of Practice for Design and Construction of Pile Foundations.






Prashant A.Bhalge, Salim.Y.Amdani

Paper Title:

Categories for Fast Block Matching Algorithm

Abstract:  Motion  Estimation  plays  a  vital role  in  a  motion compensated  hybrid  DCT  video  compression  scheme.  To reduce the computational complexity in finding the near to exact match of the block, many fast search algorithms have been proposed. This paper is survey paper in  which fast block matching algorithm are categorized. Unsymmetrical multi hexagon search, Adaptive rood pattern search, Fast full search are described.

  Block matching, Hexagonal search, Adaptive rood pattern, Validity Metrics


1.       Yue Chen, Yu Wang, Ying Lu, “ A New Fast Motion Estimation Algorithm” ,  Literature     Survey        October (1998).
2.       Fulvio Moschetti, “A Statistical  Approach to Motion Estimation”,  École    Polytechnique Fédérale  De Lausanne, a  Thesis  report, Lausanne,   EPFL      (2001).

3.       Zaynab Ahmed , Abir Jaafar Hussain and Dhiya Al-Jumeily, “ Fast Computations        Of   Full Search Block Matching Motion Estimation  (FCFS)”, 2011.

4.       Aroh Barjatya ,“ Block Matching  Algorithms For Motion Estimation  ”,DIP 6620   Final Project Paper ,  2004 .

5.       Yih-Chuan Lin and Shen-Chuan      Tai, “Fast Full-Search Block- Matching Algorithm for Motion- Compensated Video Compression”, IEEE Transactions On      Communications, Vol. 45, No. 5,      May 1997.

6.       Michael Santoro, “Valid Motion   Estimation For Super-Resolution Image Reconstruction”, A Dissertation, School of Electrical and Computer Engineering  Georgia Institute of Technology ,August 2012.

7.       Yuan Gao, Peng-yu Liu and Ke-bin Jia, “ A Fast Motion Estimation Algorithm Based on Motion Vector Distribution Prediction”, Journal of Software, Vol. 8, No. 11, November  2013.

8.       V.K.Ananthashayanal,Pushpa.M.K,“ Joint Adaptive Block Matching Search(JABMS) Algorithm for Motion Estimation”,  International Journal of Recent Trends   in Engineering, Vol 2, No. , November 2009.

9.       S. Sowmyayani, P. Arockia Jansi  Rani, “Block based Motion Estimation using    Octagon and

10.    Square Pattern”, International Journal  of Signal Processing, Image   Processing and Pattern Recognition   Vol.7, No.4 , pp.317-324,2014.

11.    Ou Yu,“Research and optimization  of  a H.264AVC motion estimation algorithm based on a 3G network”  ,report Uppsala university,2013.

12.    Ismael Daribo, Dinei  Florencio,Gene Cheung” Arbitrarily Shaped Motion  Prediction for Depth Video   Compression Using Arithmetic Edge Coding”, IEEE Transactions On   Image Processing, Vol. 23, No. 11,   November 2014.






Dhanraj Suman, Rajesh Bhatt

Paper Title:

Comparative Analysis of PID and Fuzzy Controller for Control of Magnetic Levitation System

Abstract:   This paper provides a comparative analysis of performance of different controllers for magnetic levitation system. Magnetic levitation system is a highly nonlinear and unstable system and it is very challenging to develop accurate controller for the same. This paper provides mathematical model of magnetic levitation system and develops controller for the same. Two different controllers such as PID controller and fuzzy controller have been designed and simulation results have been provided.

   Magnetic levitation system; PID controller; Fuzzy controller


1.       Rafael Morales, Vicente Feliu, and Hebertt Sira-Ramírez, “Nonlinear control for magnetic levitation system based on fast online algebric identification of the input gain,” IEEE Transactions on Control System Technology, vol. 19. No. 4, Jul 2011, pp. 757-771.
2.       Panayiotis S. Shiakolas, Stephen R. Van Schenck, Damrongrit Piyabongkarn, and Ioannis Frangeskou, “Magnetic Levitation Hardware-in-the-Loop and MATLAB-Based Experiments for Reinforcement of Neural Network Control Concepts,” IEEE Transactions on Education, vol. 47, no. 1, Feb 2004, pp. 33-1

3.       F. Beltran-Carbajal, A. Valderrabano-Gonzalez, J.C. Rosas-Caro, A. Favela-Contreras, “Output feedback control of a mechanical system using magnetic levitation,” ISA Transactions, 57, 2015, pp. 352-359

4.       Jinquan Xu, He-Hwa Chen, Hong Guo, “Robust levitation control for maglev systems with guranteed bounded airgap,” ISA Transactions, 59, 2015, pp. 205-214.

5.       Yemei Qin, Hui Peng, Wenjie Ruan, Jun Wu, Jiacheng Gao, “A modeling and control approach to magnetic levitation system based on state-dependent ARX model,” Journal of Process Control, 24, 2014, pp. 93-112.

6.       Thomas Bachle, Sebastian Hentzelt, Knut Graichen, “Nonlinear model predictive control of a magnetic levitation system,” Control Engineering Practice, 21, 2013, pp. 1250-1258.

7.       Wen Yu, Xiaoou Li, “A magnetic levitation system for advanced control education,” in Proc. International Federation of Automatic Control, 2014, pp. 9032-9037.

8.       Vinodh Kumar E, Jovitha Jerome, “LQR based optimal tuning of PID for trajectory tracking of magnetic levitation system,” Procedia Engineering, 64, 2013, pp. 254-264.

9.       Santanu Kumar Pradhan, Bidyadhar Subudhi, “Nonlinear control of a magnetic levitation system using a new input-output feedback linearization,” in Proc. International Federation of Automatic Control, 49-1, 2016, pp. 332-336

10.    Shekhar Yadav, S K Verma, S K Nagar, “Optimized PID controller for magnetic levitation system,” in Proc. International Federation of Automatic Control, 49-1,
2016, pp. 778-782

11.    Jing-Chung Shen, “H-∞ control and sliding mode control of magnetic levitation system,” Asian Journal of Control, vol. 4, no. 3, 2002, pp. 333-340

12.    Hatem Elaydi and Mohammed Elamassie, “Multi-rate ripple free dead beat control for nonlinear system using diophantine equations,” IACSIT International Journal of Engineering and Technology, vol. , no. 4, 2012, pp. 489-494

13.    Zi-Jiang Yang, Michitaka Tateishi, “Adaptive robust nonlinear control of a magnetic levitation system,” Automatica, 37, 2001, pp. 1125-1131
14.    Walter Barie, John Chiasson, “Linear and nonlinear state space controllers for magnetic levitation,” International Journal of Systems Science, vol. 27, no. 11, 1996, pp. 1153-1163
15.    Zi-Jiang Yang, Kazuhiro Kunitoshi, Shunshoku Kanae and Kiyoshi Wada, “Adaptive robust output-feedback control of magnetic levitation system by K-filter approach,” IEEE Transactions on Industrial Electronics, vol. 55, no. 1, Jan 2008, pp. 390-399

16.    Rong-Jong Wai, Kun-Lun Chuang, and Jeng-Dao Lee, “On-line supervisory control design for Maglev transportation system via total sliding mode approach and particle swarm optimization, IEEE Transactions on Automatic Control, vol. 55, no. 7, July 2010, pp. 1544-1559

17.    CHAO-LIN KUO, TZUU-HSENG S. LI and NAI REN GUO, “Design of a novel fuzzy sliding mode control for magnetic ball levitation system,” Journal of Intelligent and Robotic Systems, 42, 2005, pp. 295-316

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Legeto Cosmas Kirui, Kivaa Titus Mbiti, Ahmed Alkizim

Paper Title:

Investigating the Effect of Chemical Admixtures on the Quality of Concrete in the Construction Industry in Kenya

Abstract: Quality of concrete has been the focus of key stakeholders of the construction industry in Kenya for sometimes now after several storey buildings have collapsed. The question has been what really leads to concrete failure; quality of material used; design mix adopted; method of batching concrete; method of handling and placing. This study has set out to find whether chemical admixtures are being used in the construction industry in Kenya and their influence on quality of concrete in a bid to solve the problem. The study adopted a mixed design approach which incorporates both qualitative and quantitative elements of research.  The study came to several conclusions key among them; that chemical admixture are used in the construction sector with good effect on the quality of concrete; chemical admixtures enable projects to be managed easily. The study recommended formulation of legislation to guide the use of admixtures which will lead to solving of the current challenges of counterfeit chemical admixtures, lack of proper training by contractors and lack of interest from building statutory bodies on its use.

 Quality of Concrete, Construction Chemicals, Construction Industry.


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