i-manager Publications

i-manager's Journal on Instrumentation and Control Engineering (JIC)

Current Issue Vol. 11 Issue 2

Neural Network-Based Monitoring of Critical Parameters in Drinking Water for Enhanced Quality Assurance
Monitoring and Improvement of PV Panel Efficiency Due to Thermal Effect
Model Predictive Control of a Serial Link Robot Manipulator
Direct Torque Control (DTC) and Three Phase Induction Motor Simulation in MATLAB/Simulink
IoT-Enabled Smart Water Tank Monitoring System with Android Application Control

Most Cited

Volume 1 Issue 4 August - October 2013

Research Paper

Implementation of PI, PD and PID Controllers on FPGA for Process Control

Ravi Kumar Koride*

Asst.Professor, Electronics & Instrumentation Engineering Department, Vignan Institute of Technology & Science, Hyderabad, India.

Koride, R.K. (2013). Implementation Of PI, PD And PID Controllers On FPGA For Process Control. i-manager’s Journal on Instrumentation and Control Engineering, 1(4), 1-5. https://doi.org/10.26634/jic.1.4.2599

Abstract

This paper presents the hardware design methodology of digital control systems with different control algorithms. The control system is designed using Xilinx Spartan 3E FPGA, which consists of Analog Capture Circuit, PWM signal generator and other essential modules to control the process. The National Instruments LabVIEW is chosen as the software platform to interface with the FPGA kit. The hardware has been designed to study the Static as well as Dynamic characteristics of DC Motor, with three different control algorithms such as PI,PD and PID. The Ziegler Nichols method has been employed for tuning of controller parameters and the responses of three control algorithms are compared. The novelty in the project has been the measurement of speed, which is done through the design of Timer & Counter using the software, rather then employing the Tachometer, hence reducing the cost.

References

[1]. Ali, F.H., Mahmood, H.M & Ismael, S.M.B. (2010). “LabVIEW FPGA implementation of a PID controller for D.C. motor speed control”, pp. 139 – 144.

[2]. Antonio Visioli. (2006). "Practical PID Control", Springer- Verlag London Limited, ISBN 10: 1-84628-585-2. doi: 10.1007/1-84628-586-0.

> [3]. Curtis D.Johnson. (8th Edition). (2006). “Process Control Instrumentation Technology”. Pearson, Prentice Hall.

[4]. Dale E.Seborg. (12 April 2010). “Process Control & Dynamics”. John Wiley & Sons.

[5]. Ed Klingman. (4 March 2004). “FPGA Programming step by step”.

[6]. Guoshing Huang Shuocheng Lee. (July 2008). "PCbased PID speed control in DC motor". International Conference on Audio, Language and Image Processing, pp. 400 – 407.

[7]. Muhammad H. Rashid. (3 Edition). (2004). “Power Electronics Handbook”. Pearson, Prentice Hall.

[8]. National Instruments Co. (June 2009). "LabVIEW: PID and Fuzzy Logic Toolkit User Manual", Part Number 372192D-01.

[9]. National Instruments Co. (8 October 2010). “Introduction to FPGA Technology”.

[10]. Renee Robbins.(5 March 2010). “Advantages of FPGA”.

[11]. Seung-Min Baek & Tae-Yong Kuc. (October 1997). “An adaptive PID learning control of DC motors”. International Conference on Systems, Man & Cybernetics, Orlando, FL, vol 3, pp.2877-2882.

[12]. Shekar Chandrashekar. (30 July 2004). Advantages of FGPA Design Methodologies.

[13]. "Spartan- 3E Starter Kit Board User Guide". (9 March 2006). UG230 (v1.0), Xilinx.

[14]. "Spartan-3E FPGA Family: Complete Data Sheet". (April 2008). DS312 , Xilinx.

[15]. Dr. Vlassis Petousis. “Programming FPGAs using LabVIEW”.

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Research Paper

Methods of Placement and Installation of UFM to Extend the Linearity Range of Measurement

Sheikh Rafik Manihar Ahmed*

Control System Engineer, Fluor Daniel India Private Limited, Gurgaon, New Delhi, India.

Ahmed, S.R.M. (2013). Methods of Placement and Installation of UFM To Extend The Linearity Range of Measurement. i-manager’s Journal on Instrumentation and Control Engineering, 1(4), 6-11. https://doi.org/10.26634/jic.1.4.2600

Abstract

This paper explains the different Methods of Placement and Installation of Ultrasonic Flow Measuring Instrument on the Pipe of different configuration to extend the linearity range of measurement up to maximum of the input range. Accurate flow measurement is an essential requirement both from qualitative and economic points of view. Among the non contact type of flow measurement, Ultrasonic Flow Measurement (UFM) is widely used to measure flow, because of its advantage like high resolution and less interference of noise on output. However, non linear characteristics of Ultrasonic flow meters have restricted its use [1-2]. But the different arrangement and Installation method helps us to understand, how to linearise the overall system to maximise its full scale range and to make it adaptive to variations in pipe diameter, liquid density, and liquid temperature [3-4]. A flowmeter installed in such a pipeline should indicate the volumetric flowrate correctly and independently of the flow profile. The ultrasonic flowmeter integrates, or averages, the velocity along its measuring paths [8- 11]. Clamp-on transducers eliminate in-line installation, allowing one meter to be used at many locations. For easy installation, no moving parts and no contact between transducer and Fluid is required. Exterior installation eliminates pressure losses and prevents leaking that can be associated with in-line meter installations [15].

References

[1]. T. T. Yeh, P. I. Espina and S. A. Osella, (2001). “An Intelligent Ultrasonic Flow Meter for Improved Flow Measurement and Flow Calibration Facility”, Proc. IEEE Conf. on Instrument and Measurement Technology, Budapest, Hungary, pp. 1741-1746.

[2]. O. Keitmann-Curdes and B. Funck, (2008). “A new calibration method for ultrasonic clamp-on transducers”, IEEE Symposium on Ultrasonic's, Berlin, pp. 517-520.

[3]. Ch. Buess, (1988). “Transit-Time Ultrasonic Airflow Meter for Medical Application”, Thesis, Swiss Federal Institute of Technology.

[4]. Santhosh KV and BK Roy, (2012). “An Intelligent Flow Measuring Scheme Using Ultrasonic Flowmeter”, 31st International Conference on Modelling, Identification and Control, Thailand.

[5]. J. Yang and H. Jiao, (2010). “Design of Multi-channel Ultrasonic Flowmeter based on ARM”, Proc. IEEE Conf. on Electrical and Control Engineering, Yichang, China, pp. 758-761.

[6]. E. Aziz, Z. Kanev, M. Barboucha, R. Maimouni and M. Staroswiecki, (1996). “An ultrasonic flowmeter designed according to smart sensors concept”, Proc. IEEE 8th Mediterranean Electro technical Conference, France, pp. 1371-1374.

[7]. L. Guowei and C. Wuchang, (2002). “The Measurement Technology of Flow Rate and Instrument”, China Machine Press.

[8]. P. I. Espina, P. I. Rothfleisch, T. T. Yeh and S. A. Osella, (1999). “Telemetrology and advanced ultrasonic flow metering”, Proc. of the 4th International Symposium on Fluid Flow Measurement, Denver, USA.

[9]. L. C. Lynnworth, (1989). “Ultrasonic measurements for process control”, Academic Press, San Diego, CA.

[10]. L. Z. Yang., Z. Zhang and Dongsheng, (2006). “The Experiment Study of Ultrasonic Flowmeter Precision”, Journal of Xi'an University of Technology, Vol. 22, No. 1, pp. 70-72 .

[11]. A. Chupyra, M. Kondaurov, A. Medvedko, S. Singatulin, E. Shubin, (2004). “SAS family of hydrostatic level and tilt Sensors for slow ground motion studies and precise alignment” Proceeding of 8th IWAA04, Geneve.

[12]. M. Shlösser, A. Herty, (2002). “High precision accelerator alignment of large linear colliders – vertical alignment” Proceedings of the 7th IWAA, Spring-8.

[13]. J.S. Charlton, Synetix-Dialog Alliance, and R.P. Lees, (2002). “The Future of Three Phase Separator Control”, SPE 77891.

[14]. Betta et al, (1998). Microcontroller-based performance enhancement of an optical fiber level transducer, IEEE Transactions on Instrumentation and Measurements, Vol. 45, No 2.

[15]. G. Betta , L. Ippoto and A. Scaflione, (1995). “An optical fiber based technique for continuous level sensing”, IEEE. Transactions Measurement, Vol. 44, pp. 686-689.

[16]. J. Yoder, (2006). “Many Paths to Successful Flow Measurement”, Flow Control Network.

[17]. R. J. Plaza, (2006). “Sink or Swim: The Effects of Temperature on Liquid Density and Buoyancy”, California state science fair.

[18]. B. G. Liptak, (2003). “Instrument Engineers' Handbook: Process Measurement and Analysis”, 4th Edition, CRC Press.

[19]. D. Karaboga, (2005). “An idea based on honey bee swarm for numerical optimization”, Technical report-tr06, Erciyes university, Engineering faculty, Computer Engineering Department.

[20]. F. M. Dias, A. Antunes, J. Vieira and A. M. Mota, (2004). “Implementing the Levenberg-Marquardt Algorithm Online: a sliding window approach with early stopping”, Int. Conf. Proc. IFAC, USA.

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Research Paper

A Closed Loop Transformer Monitoring Using Virtual Instrumentation

Saranya Ponnuswamy* , S. Manoharan**

* Assistant Professor, Department of Electronics and Instrumentation Engineering, Karpagam College of Engineering, Coimbatore.

** Professor and Head, Department of Electronics and Instrumentation Engineering, Karpagam College of Engineering, Coimbatore.

Saranya, P., and Manoharan, S. (2013). A Closed Loop Transformer Monitoring Using Virtual Instrumentation. i-manager’s Journal on Instrumentation and Control Engineering, 1(4), 12-17. https://doi.org/10.26634/jic.1.4.2601

Abstract

This paper proposes a new concept for monitoring the remote electrical parameters like voltage, current, oil temperature, oil level, active power, reactive power, apparent power, power factor of a remotely located distribution transformer and to transmit it over a communication network and these real time values are displayed using Virtual Instrumentation platform on the PC which is located at the Substation. In addition, it will protect the distribution transformers from various faults like over current and over voltage. Distribution transformers which are the critical components in power distribution systems are located on the feeders of the substation and monitoring of which is a long time need and there is no proper medium for it.

References

[1]. Amit Sachan, (2012). ''Microcontroller Based Substation Monitoring and Control System with GSM Modem” IOSR Journal of Electrical and Electronics Engineering (IOSRJEEE) ISSN: 2278-1676 Volume 1, Issue 6 (July-Aug., pp. 13-21.

[2]. V. Thiyagarajan & T.Palanivel (2010). ''An Efficient Monitoring of Substations using Microcontroller based monitoring System'', IJRRAS 4,.

[3]. Jaswinder Singh et al., NexGEN Consultancy Pvt. Ltd. “Using CompactRIO and LabVIEW Real-Time to Build a Transformer Monitoring System”.

[4]. Taha Landolsi, A. R. Al-Ali, Tarik Ozkul, and Mohammad A. Al-Rousan, (2010). “Wireless Distributed Load-Shedding Management System for Non-Emergency Cases” International Journal of Electrical and Electronics Engineering 4:7 Applied Mechanics and Materials (Vol. 48 - 49).

[5]. B. A. Carreras, V. E. Lynch, D. E. Newman and I. Dobson, (2003). "Blackout Mitigation Assessment in Power Transmission Systems", Hawaii International Conference on System Science.

[6]. Xiaomeng Li and Ganesh K. Venayagamoorthy, (2005). "A Neural Network Based Wide Area Monitor for a Power System", IEEE Power Engineering Society General Meeting, Vol. 2, pp: 1455-1460.

[7]. Hari Arief Dharmawan and Sam A. M. Ali (2012). “A Compact Remote Monitoring System for a Three-Phase 10- kVA Energy-Efficient Switchable Distribution Transformer” IEEE transactions on instrumentation and measurement, Vol. 61, No. 3.

[8]. Daponte, M. Di Penta and G.Mercurio, (2004). "TRANSIENTMETER: A Distributed Measurement System for Power Quality Monitoring", IEEE Transactions on Power Delivery, Vol. 19, Issue. 2, pp: 456-463.

[9]. G. Pudlo, S. Tenbohlen, M. Linders and G. Krost, (2002). "Integration of Power Transformer Monitoring and Overload Calculation into the Power System Control Surface", IEEE/PES Transmission and Distribution Conference and Exhibition, Vol. 1, pp: 470-474 Asia Pacific.

[10]. T. Ananthapadmanabha, A. D. Kulkarni, Madhvaraja, and A. P. Suma, (2011). ''Automatic meter reading (AMR) based distribution security monitoring and distribution-supervisory control and data acquisition (DSCADA) control'' Journal of Electrical and Electronics Engineering Research Vol. 3(6), pp. 108-120.

[11]. LabVIEW User Manuals.

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Research Paper

Fuzzy Logic Controller-An Advanced & Efficient Technique for Controlling Drives

R. Suman*

Department of Electrical & Electronics Engineering, Regional Centre, Anna University, Coimbatore, India.

Suman, R. (2013). Fuzzy Logic Controller-An Advanced & Efficient Technique for Controlling Drives. i-manager’s Journal on Instrumentation and Control Engineering, 1(4), 18-26. https://doi.org/10.26634/jic.1.4.2602

Abstract

The basic idea is to design a fuzzy logic hysteresis comparator-based direct torque control scheme of an induction motor under varying dynamic conditions[1]. The major problem that is usually associated with DTC drive is the high torque ripple. To overcome this problem a torque hysteresis band with variable amplitude is proposed based on fuzzy logic[4]. The fuzzy logic controller is used to adjust the bandwidth of the torque hysteresis controller in order to reduce the torque and flux ripples and, to improve motor dynamic response[3],[4]. Based on the slopes of motor-estimated torque and stator current, an FLC is designed to select the optimum bandwidth of the torque hysteresis controller. In order to test the performance of the proposed FLC-based DTC scheme for IM drive, a complete simulation model is developed using MATLAB/Simulink.

References

[1]. L. Tang, L. Zhong, M. F. Rahman, and Y. Hu, (2003). “A novel direct torque control for interior permanent-magnet synchronous machine drive with low ripple in torque and flux-a speed-sensorless approach,” IEEE Trans.Ind. Appl., Vol. 39, No. 6, pp. 1748–1756.

[2]. S. Kouro, R. Bernal, H. Miranda, C.A.Silva, and J.Rodriguez, (2007). “High performance torque and flux control for multilevel inverter fed induction motors,” IEEE Trans. Power Electron., Vol. 22, No. 6, pp. 2116–2123.

[3]. D. Casadei and T. Angelo, (2000). “Implementation of a direct torque control algorithm for induction motors based on discrete space vector modulation,” IEEE Trans. Power Electron., Vol. 15, No. 4, pp. 769–777.

[4]. Y.S. Lai and J.-C. Lin, (2003). “New hybrid fuzzy controller for direct torque control induction motor drives,” IEEE Trans. Power Electron., Vol. 18, No. 5, pp. 1211–1219.

[5]. J.-K. Kang and S.-K. Sul, (1999). “New direct torque control of induction motor for minimum torque ripple and constant switching frequency,” IEEE Trans. Ind. Appl., Vol. 35, No. 5, pp. 1076–1082.

[6]. Youb and A. Craciunescu, (2009). “Direct torque control of induction motors with fuzzy minimization torque ripple,” in Proc. WESCO, Vol. 2, pp. 713–717.

[7]. A. F. Aimer, A. Bendiabdellah, A. Miloudi, and C. Mokhtar, (2009). “Application of fuzzy logic for a ripple reduction strategy in DTC scheme of a PWM inverter fed induction motor drives,” J. Elect. Syst., Special Issue 1, pp. 13–17.

[8]. G. Sheng-wei and C. Yan, (2010). “Research on torque ripple minimization strategy for direct torque control of induction motors,” in Proc. ICCASM, pp. VI-278–VI-281.

[9]. G. M. Gadoue, D. Giaouris, and J.W. Finch, “Artificial intelligence-based speed control of DTC induction motor drives-A comparative study,”Elect. Power Syst. Res., vol. 79, no. 1, pp. 210–219, 2009.

[10]. R. Toufouti, S. Meziane, and H. Benalla, (2006). “Direct torque control for induction motor using fuzzy logic,” ACSE J., Vol. 6, No. 2, pp. 19–26.

[11]. F. Sheidaei, M. Sedighizadeh, S. H. Mohseni-Zonoozi, and Y. Alinejad- Beromi, (2007). “A fuzzy logic direct torque control for induction motor sensorless drive,” in Proc. UPEC, pp. 197–202.

[12]. Y. V. S. Reddy, M. Vijayakumar, and T. Brahmananda Reddy, (2007). “Direct Torque control of induction motor using sophisticated lookup tables based on neural networks,” AIML J., Vol. 7, No. 1, pp. 9–15.

[13]. J.-K. Kang, D.-W. Chung, and S.-K. Sul, (1999). “Direct torque control of induction machine with variable amplitude control of flux and torque hysteresis bands,” in Proc. IEMD, pp. 640–642.

[14]. K.-K. La, M.-H. Shin, and D.-S. Hyun, (2000). “Direct torque control of induction motor with reduction of torque ripple,” in Proc. IEEE IECON, pp. 1087–1092.

[15]. Nik Rumzi Nik Idris and Abdul Halim Mohamed Yatim, (2004). “Direct Torque Control of Induction Machines With Constant Switching Frequency and Reduced Torque Ripple,” IEEE Trans. Ind. Appl., Vol. 51, No. 4, pp. 1076–1082.

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Research Paper

GA Based PID Control of Magnetic Levitation System

S. Kishore* , D. Vasanthi**

*Department of Instrumentation Engineering, Madras Institute of Technology, Chennai, Tamilnadu.

**Department of Instrumentation Engineering, Madras Institute of Technology, Chennai, Tamilnadu.

Kishore, S., and Vasanthi, D. (2013). GA Based PID Control Of Magnetic Levitation System. i-manager’s Journal on Instrumentation and Control Engineering, 1(4), 27-31. https://doi.org/10.26634/jic.1.4.2603

Abstract

The Magnetic levitation system serves as a simple model of devices, which are becoming popular in recent years. Magnetic Levitation System is a nonlinear, unstable system that can be applied in many application area such as in magnetic bearings, high speed trains, vibration isolation tables in semiconductor manufacturing, levitation of wind power generation, levitation of molten metal in induction furnaces, position tracking and levitation of metal slabs during manufacturing. The Magnetic levitation system can be categorized as a repulsive system and this system is based on the source of levitate forces. Since it is highly nonlinear and unstable system, it is very challenging in order to construct the high performance controllers to regulate the position of the levitation ball. This work involves the design of PID controller, Optimized PID controller. The real time implementation on the magnetic levitation kit has been carried out.In the above work, we acquired a high precision control to levitate a steel ball in the desired position.

References

[1]. Marwan K.Abbadi, “Modeling and control of magnetic levitation system”, Department of Electrical and Computer Engineering, Bradley University.

[2]. Scott A.Green, Kevin C. Craig, Robust, (1997). “Digital, non-linear control of magnetic levitation System, dynamic system and control division”.

[3]. Walter barie and Jhon chiasson, (1996). “linear and non-linear stare space controllers for magnetic Levitation system”, International Journal for system science, Vol 27, pp. 1153-1163.

[4]. Zi-Jiang Yang, MichitakaTateshi (2001). “Adaptive robust nonlinear control of a magnetic levitation system”, Iizuku, Fukuoka, 820-8502 Japan. Automatoca 37, pp. 1125-1131.

[5]. ValerDolga, LiaDolga, (2007). “Fascicle of Management and Technical engineering”, Modeling and Simulation of a Magnetic Levitation system, Vol. 6 ( XVI).

[6]. Ishtiaq Ahmad, Muhammad Akram Aavaid. “Nonlinear Model & Controller Design for Magnetic Levitation System”, Recent advances in signal processing, robotics and automation.

[7]. Karl J.Astrom, Bjorn Wittenmark. “Adaptive control”-, second edition, Pearson publication,.

[8] S. Lei, A. Palazzolo, and A. Kascak,Steven. Barker, Ron Matusiak, Buffalo state college. Session 3649, -”A technology approach to magnetic levitation system”

[9]. Y. J. Cao and Q. H. Wu, (1999). “Teaching Genetic Algorithm Using Mat lab”, International Journal of Electrical Engineering, Vol. 36, pp. 139–153.

[10]. C. Lin and H. Jou., (1993). “Force model identification for magnetic suspension systems via magnetic field measurement”. IEEE Transactions on Instrumentation and Measurement, 42(3): pp. 767–771.

i-manager's Journal on Instrumentation and Control Engineering (JIC)

Current Issue Vol. 11 Issue 2

Most Read

Most Cited

Volume 1 Issue 4 August - October 2013

Implementation of PI, PD and PID Controllers on FPGA for Process Control

Ravi Kumar Koride*

Asst.Professor, Electronics & Instrumentation Engineering Department, Vignan Institute of Technology & Science, Hyderabad, India.

Koride, R.K. (2013). Implementation Of PI, PD And PID Controllers On FPGA For Process Control. i-manager’s Journal on Instrumentation and Control Engineering, 1(4), 1-5. https://doi.org/10.26634/jic.1.4.2599

Abstract

References

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Methods of Placement and Installation of UFM to Extend the Linearity Range of Measurement

Sheikh Rafik Manihar Ahmed*

Control System Engineer, Fluor Daniel India Private Limited, Gurgaon, New Delhi, India.

Ahmed, S.R.M. (2013). Methods of Placement and Installation of UFM To Extend The Linearity Range of Measurement. i-manager’s Journal on Instrumentation and Control Engineering, 1(4), 6-11. https://doi.org/10.26634/jic.1.4.2600

Abstract

References

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A Closed Loop Transformer Monitoring Using Virtual Instrumentation

Saranya Ponnuswamy* , S. Manoharan**

* Assistant Professor, Department of Electronics and Instrumentation Engineering, Karpagam College of Engineering, Coimbatore. ** Professor and Head, Department of Electronics and Instrumentation Engineering, Karpagam College of Engineering, Coimbatore.

Saranya, P., and Manoharan, S. (2013). A Closed Loop Transformer Monitoring Using Virtual Instrumentation. i-manager’s Journal on Instrumentation and Control Engineering, 1(4), 12-17. https://doi.org/10.26634/jic.1.4.2601

Abstract

References

Full Article (HTML)

Pdf

Fuzzy Logic Controller-An Advanced & Efficient Technique for Controlling Drives

R. Suman*

Department of Electrical & Electronics Engineering, Regional Centre, Anna University, Coimbatore, India.

Suman, R. (2013). Fuzzy Logic Controller-An Advanced & Efficient Technique for Controlling Drives. i-manager’s Journal on Instrumentation and Control Engineering, 1(4), 18-26. https://doi.org/10.26634/jic.1.4.2602

Abstract

References

Full Article (HTML)

Pdf

GA Based PID Control of Magnetic Levitation System

S. Kishore* , D. Vasanthi**

*Department of Instrumentation Engineering, Madras Institute of Technology, Chennai, Tamilnadu. **Department of Instrumentation Engineering, Madras Institute of Technology, Chennai, Tamilnadu.

Kishore, S., and Vasanthi, D. (2013). GA Based PID Control Of Magnetic Levitation System. i-manager’s Journal on Instrumentation and Control Engineering, 1(4), 27-31. https://doi.org/10.26634/jic.1.4.2603

Abstract

References

Full Article (HTML)

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* Assistant Professor, Department of Electronics and Instrumentation Engineering, Karpagam College of Engineering, Coimbatore.

** Professor and Head, Department of Electronics and Instrumentation Engineering, Karpagam College of Engineering, Coimbatore.

*Department of Instrumentation Engineering, Madras Institute of Technology, Chennai, Tamilnadu.

**Department of Instrumentation Engineering, Madras Institute of Technology, Chennai, Tamilnadu.