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i-manager's Journal on Embedded Systems (JES)

Current Issue Vol. 12 Issue 2

Most Cited

Volume 1 Issue 3 August - October 2012

Article

65nm CMOS LVDS I/O Transmitter Implementation with 600Mbps Data Rate

Alexey Balashov* , Andrey Malkov**

*-** Freescale Semiconductor, Moscow, Russia.

Balashov,A., and Malkov,A., (2013). 65nm CMOS LVDS I/O Transmitter Implementation with 600 Mbps Data Rate. i-manager’s Journal on Embedded Systems, 1(3), 1-6. https://doi.org/10.26634/jes.1.3.1989

Abstract

Low Voltage Differential Signaling (LVDS) technology is an effective solution for the physical layer of high-speed data applications. The advantages of the LVDS interface include high data rates, low noise generation, and low power consumption across the entire speed range. Different approaches of LVDS circuit implementation are considered in this article. The LVDS transmitter circuit implementation in the I/O pad cell for microprocessor product based on 65nm CMOS bulk technology is presented. The designed LVDS transmitter supports a 600 Mbps data transfer rate and supply current no more than 5mA.

References

[1]. ANSI TIA/EIA-644-A, “Electrical Characteristics of Low Voltage Differential Signaling (LVDS) Interface Circuits”.

[2]. IEEE Standard for Low-Voltage Differential Signals (LVDS) for Scalable Coherent Interface (SCI), IEEE Standard 1596.3-1996, Jul. 1996.

[3]. M. Chen, J. Silva-Martinez, M. Nix, and M. E. Robinson, “Low-voltage low-power LVDS drivers,” IEEE J. Solid-State Circuits, Vol. 40, No. 2, pp. 472–479, Feb. 2005.

[4]. G. Mandal and P. Mandal, “Low power LVDS transmitter with low common mode variation for 1 Gb/s-per pin operation,” in Proc. IEEE Int. Symp. Circuits and Systems, Vancouver, Canada, May 2004, pp.1120–1123.

[5]. V. Bratov, J. Binkley, V. Katzman, J. Choma, “Architecture and implementation of Low-Power LVDS Output Buffer for High-Speed Applications”, IEEE Transactions on circuit and systems, Vol.53, No.10, October 2006.

[6]. Gray Hurst, Lewis Meyer, “Analysis and design of analog integrated circuits”, fourth edition, 2001.

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Research Paper

Comparison Of Multi Output Series Resonant Inverter And Cyclo Inverter Induction Heater Systems

S. Jaanaa Rubavathy* , Dr. P. Murugesan**

* Research Scholar, Sathyabama University, Chennai, India.

** Professor, S.A. Engineering College, Chennai, India.

Rubavathy,J.S., and Murugesan.P. (2012). Comparison of Multi Output Series Resonant Inverter and Cyclo Inverter Induction Heater Systems. i-manager’s Journal on Embedded Systems, 1(3), 7-13. https://doi.org/10.26634/jes.1.3.1990

Abstract

In this paper, utility frequency AC to High frequency AC power conversion circuit without DC smoothing capacitor is proposed, which employs asymmetric voltage cancellation control for output power, a generalized control technique for Series resonant inverter and cyclo- inverter for output voltage control. It ensures better efficiency performances than conventional control strategies. The development of two output Series resonant inverter and cyclo-inverter topology for induction heating system ensures reduction of size, weight and number of components. The proposed inverters are a two output extension of a full bridge inverter. It allows the control of two output powers, simultaneously and independently, up to their rated power, by using 3 legs of full bridge Series resonant inverter and cyclo-inverter. One leg for common control and other two legs for independent control. To verify the theoretical predictions, the proposed two output series resonant inverter and cyclo-inverter systems are designed and simulated using MATLAB simulink. The THD and output powers of both the systems are compared.

References

[1]. S.M.W. Ahmed, M.M. Eissa, M. Edress and T.S. Abdel- Hameed (2009). “A Multi-Output High frequency Cycloinverter operation for induction-heating Cooking Appliances- Harmonic Study”, CIEA, IEEE pp 2267-2272.

[2]. Henry W. Koertzen, Jacobus D. Van Wyk & Jan A. Ferreira (1995). “Design of the Half-Bridge, Series Resonant Converter for Induction Cooking”, The 26th Annual Power Electronics Specialists Conference, Vol 2, pp 729-735.

[3]. Mokhtar Kamli, Shigehiro Yamamoto & Minoru Abe (1996, Feb), “A 50 –150 kHz Half-Bridge Inverter for Induction Heating applications”, IEEE Transactions on Industrial Electronics, Vol 43, No 1,pp 163-172.

[4]. Jose M. Burdio, Abelardo Martinez & Jose R. Garcia (1998, Nov), “A synthesis Method for Generating Switched Electronic Converter ”, IEEE Transaction on Power Electronics, Vol 13,No 6 pp 1056- 1068.

[5]. Shengpei Wang, Kiyoshi Izaki, Izuo Hirota, Hidekazu Yamashita, Hideki Omori & Mutsuo Nakaoka (1998,July/Aug), “Induction- Heated Cooking Appkiance using New Quasi-Resonant Zvs-Pwm Inverter with Power Factor Correction”, IEEE Transaction on Industry Applications, Vol 34, No 4, pp 705-712.

[6]. Fernando Monterde, Pablo Hernandez, Jose M. Burdio, Jose R. Garcia, & Abelardo Martinez (2000), “A new ZVS Two-output Series-Resonant Inverter for Induction cookers obtained by a synthesis Method”, The 31st Annual Power Electronics Specialist Conference, Vol 3, pp 1375- 1380.

[7]. Jose M.Burdio, Luis A. Barragan, Fernando Monterde, Denis Nararro & Jesus Acero (2004, March), “Asymmetrical Voltage – Cancellation control for Full-Bridge Series Resonant Inverters”, IEEE Transactions on Power Electronics, Vol 19,No 2,pp 461-469.

[8]. Jose M. Burdio, Fernando Monterde, Jose R. Garcia, Luis A. Barragan & Abelardo Martinez ( 2005, July), “A twooutput Series- Resonant Inverter for Induction-Heating Cooking Appliances” IEEE Transaction on Power Electronics , Vol 20, No 4, pp 815-822.

[9]. S.H. Hosseini, A.Yazdanpanah Goharrizi and E. Karimi (2006),“ A Multi-Output Series Resonant Inverter With Asymmetrical Voltage – Cancellation Control for Induction- Heating Cooking Appliances”, CES / IEEE 5th International Conference on Power Electronics & Motion Control, Vol 3, pp 1-6.

[10]. J. Salmon, A. Knight, & J. Ewanchuk (2008), “Single Phase Multi- Level PWM Inverter Topologies using Coupled Inductors”, IEEE Transaction, pp 802-808.

[12]. Juan Dixon, Javier Pereda, Carlos Castillo, Sebastian Bosch (2010), “Asymmetrical Multilevel Inverter for Traction Drives Using Only One DC Supply”, IEEE Transactions.

[13]. Ruibin mei, Changsheng Li, Xianghua Liu, Bao Li and Bin Han (2011, April), “Modeling of slab induction heating in hot rolling by FEM”, Scientific research Journal.

[14]. Hector Sarnago, Arturo Mediano and Oscar Lucia (2012, August), “High frequency AC-AC power electronic converter applied to domestic induction heating”, IEEE transactions on Power Electronics, Vol 27, No 8.

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Research Paper

A Hybrid Evolutionary Programming – Tabu Search Method with Cooling-Banking Constraints for Hydro Thermal Scheduling in a Large Power System

Nimain Charan Nayak* , C. Christober Asir Rajan**

* Research Scholar, Dept. of EEE, Sathyabama University, Chennai, India.

** Associate Professor, Dept. of EEE, Pondicherry Engineering College, Puducherry, India.

Nayak,N,C., and Rajan,C,A.C., (2012). A Hybrid Evolutionary Programming – Tabu Search Method With Cooling – Banking Constraints For Hydro Thermal Scheduling In A Large Power System. i-manager’s Journal on Embedded Systems, 1(3), 14-25. https://doi.org/10.26634/jes.1.3.1991

Abstract

This Paper proposes a new hybrid algorithm for solving the Unit Commitment problem in Hydrothermal power system using a hybrid Evolutionary Programming — Tabu Search method with cooling-banking constraints. The main objective of this paper is to find the generation scheduling by committing the generating units such that the total operating cost can be minimized by satisfying both the forecasted load demand and various operating constraints of the generating units. It is a Global optimization technique for solving Unit Commitment Problem, operates on a system, which is designed to encode each unit’s operating schedule with regard to its minimum up/down time. In this method, the unit commitment schedule is coded as a string of symbols. An initial population of parent solutions is generated at random. Here the parents are obtained from a pre-defined set of solutions i.e. each and every solution is adjusted to meet the requirements. Then, random recommitment is carried out with respect to the unit’s minimum down time. Tabu Search (TS) is a powerful optimization procedure that has been successfully applied to a number of combinatorial optimization problems. It avoids entrapment at local optimum by maintaining a short term memory of recently obtained solutions. The memory structure assists in forbidding certain moves that deteriorates the quality of the solution by assigning Tabu status to the forbidden solutions. The Tabu status of a solution can be overruled if certain conditions are satisfied expressed in the form of Aspiration Level. Aspiration Level (AL) adds flexibility in Tabu Search by directing the search towards attractive moves. The best population is selected by Evolutionary Strategy. Numerical results are shown comparing the cost solutions and computation time obtained by using the proposed hybrid method than conventional methods like Dynamic Programming, Lagrangian Relaxation.

References

[1]. Ferrero, R.W., Rivera, J.F., & Shahidehpour, S.M. (1998). A Dynamic Programming Two-Stage Algorithm For Long- Term Hydrothermal Scheduling Of Multi reservoir Systems, IEEE Transactions on Power System, vol. 13, n.4, pp.1534- 1540.

[2]. Martinez, L., and Soares, S. (2002). Comparison between Closed-Loop and Partial Open-Loop Feedback Control Policies in Long Term Hydrothermal Scheduling, IEEE Transactions on Power Systems, Vol. 17, No. 2, pp. 330-336.

[3]. Benhamida, F. (2009). A Hybrid Lagrangian Relaxation – Dynamic Programming Solution to the Unit Commitment Problem, Journal of Electrical Engineering, Vol. 9, No. 4, 2009, pp. 31-40.

[4]. Salem Al-Agtash (2001). Hydrothermal Scheduling by Augmented Lagrangian: Consideration of Transmission Constraints and Pumped-Storage Units, IEEE Transactions on Power Systems, Vol. 16, No. 4, 2001, pp. 750-756

[5]. Ngundam, J.M., Kenfack, F., & Tatietse, T.T. (2002). Optimal Scheduling of Large – Scale Hydrothermal Power Systems Using the Lagrangian Relaxation Technique, International Journal of Electrical Power & Energy Systems, Vol. 22, No. 1, 2002, pp.237-245.

[6]. Alberto Borghetti, Antonio Frangioni, Fabrizio Lacalandra, and Carlo Alberto Nucci, (2003). Lagrangian Heuristics Based on Disaggregated Bundle Methods for Hydrothermal Unit Commitment, IEEE Transactions on Power Systems, Vol. 18, No. 1,2003, pp.313-323.

[7]. Ruey-Hsun Liang, Ming-Huei Ke, and Yie-Tone Chen, (2009). Co evolutionary Algorithm Based on Lagrangian Method for Hydrothermal Generation Scheduling, IEEE Transactions on Power Systems, Vol. 24, No. 2, 2009, pp. 499-507.

[8]. Gary, W. Chang, Mohamed Aganagic, James G. Waight, José Medina, Tony Burton, Steve Reeves, and Christoforidis, M. (2001). Experiences With Mixed Integer Linear Programming Based Approaches on Short-Term Hydro Scheduling, IEEE Transactions on Power Systems, Vol. 16, No. 4, 2001, pp.743-749.

[9]. Alberto Borghetti, Claudia D'Ambrosio, Andrea Lodi, and Silvano Martello, (2008). An MILP Approach for Short- Term Hydro Scheduling and Unit Commitment with Head- Dependent Reservoir, IEEE Transactions on Power Systems, Vol. 23. No. 3, pp. 1115-1124.

[10]. Costas G. Baslis, Stylianos E. Papadakis, and Anastasios G. Bakirtzis, (2009). Simulation of Optimal Medium-Term Hydro-Thermal System Operation by Grid Computing, IEEE Transactions on Power Systems, Vol. 24, No. 3, pp. 1208-1217.

[11]. Baptistella, L.F.B., and Gerome, J.C. (1980). Decomposition approach to problem of unit commitment schedule for hydrothermal systems, IEE Proc. Generation, Transmission and Distribution, Vol. 127, No. 6, pp. 250-258.

[12]. Mohan, M.R., Kuppusamy, K., Abdullah Khan, M. (1992). Optimal Short-term Hydro-Thermal Scheduling using Decomposition Approach and Linear Programming Method, International Journal of Electrical Power and Energy Systems, Vol. 14, No. 1, 1992, pp.39-44.

[13]. Wilfredo S. Sifuentes, Alberto Vargas, (2007). Hydrothermal Scheduling Using Benders Decomposition: Accelerating Techniques, IEEE Transactions on Power Systems, Vol. 22, No. 3, pp. 1351-1359.

[14]. Tiago Norbiato dos Santos and Andre Luiz Diniz, (2009). A New Multi period Stage Definition for the Multistage Benders Decomposition Approach Applied to Hydrothermal Scheduling, IEEE Transactions on Power Systems, Vol. 24, No. 3, pp.1383-1392.

[15]. Srinivasa Rao, C., Siva Nagaraju, S., Sangameswara Raju, P. (2009). Automatic generation control of TCPS based hydrothermal system under open market scenario: A fuzzy logic approach, International Journal of Electrical Power and Energy Systems, Vol. 31, No. 1, pp. 315–322.

[16]. Vo Ngoc Dieu, Weerakorn Ongsakul, (2008). Enhanced merit order and augmented Lagrange Hopfield network for hydrothermal scheduling, International Journal of Electrical Power and Energy Systems, vol. 30, n. 1, pp. 93–101.

[17]. Kirkpatrick S, Gelatt CD, Jr., Vecehi MP, (1983). Optimisation by Simulated Annealing, Science, Vol. 220, No. 1, 1983, pp. 4598.

[18]. Shokri Z. Selim and Alsultan, K. (1991). A Simulated Annealing Algorithm for the Clustering Problem, Pattern Recognition, Vol. 24, No. 10, 1991, pp 1003-1008.

[19]. Zhuang, F., and Galiana, F.D. (1990) Unit Commitment by Simulated Annealing, IEEE Trans. on Power Systems, Vol. 5, No. 1, 1990, pp.311-318.

[20]. Mantawy, A.H., Youssef, L. Abdel-Magid, Shokri Z. Selim, (1998). A Simulated Annealing Algorithm for Unit Commitment, IEEE Trans. on Power Systems, Vol. 13, No. 1, 1998, pp. 197-204.

[21]. Mantawy, A.H., Youssef L. Abdel-Magid, Shokri Z. Selim, (1998). A Unit Commitment By Tabu Search, IEE Proc. Generation, Transmission and Distribution, Vol. 145, No. 1, 1998, pp.56-64.

[22]. Whei-Min Lin, Fu-Sheng Cheng, Ming-Tong Tsay, (2002). An Improved Tabu Search for Economic Dispatch With Multiple Minima, IEEE Transactions on Power Systems, Vol. 17, No. 1, 2002, pp.108-112.

[23]. Xaiomin Bai and Shahidehpur, S.M. (1996). Hydro- Thermal Scheduling by Tabu Search and Decomposition, IEEE Transactions on Power Systems, Vol. 11, No. 2, 1996, pp.968-974.

[24]. Rudolf, A., and Bayrleithner, R. (1999). A Genetic Algorithm for Solving the Unit Commitment Problem of a Hydro Thermal Power System, IEEE Transactions on Power Systems, Vol. 14, No. 4, pp. 1460-1468.

[25]. Yong-Gang Wu, Chun-Ying Ho, (2000). A Diploid Genetic Approach to Short-Term Scheduling of Hydro- Thermal System, IEEE Transactions on Power Systems, Vol. 15, No. 4, 2000, pp. 1268-1274.

[26]. Esteban Gil, Julian Bustos, and Hugh Rudnick, Short- Term Hydrothermal Generation Scheduling Model Using a Genetic Algorithm, IEEE Transactions on Power Systems, vol. 18, n. 4, 2003, pp.1256-1264.

[27]. Mariappane, E., & Thyagarajah, K. (2009). A Genetic Algorithm Approach to Price-Based Unit Commitment, Journal of Electrical Engineering, Vol. 9, No. 4, 2009, pp. 41-46.

[28]. R. Lal Raja Singh, & C. Christober Asir Rajan, (2011). A Hybrid Particle Swarm Optimization Employing Genetic Algorithm for Unit Commitment Problem, International Review of Electrical Engineering, Vol. 6. No. 7, pp. 3211- 3217.

[29]. Werner, T.G., & Verstege, F. (1999). An Evolution Strategy for Short-Term Operation Planning of Hydrothermal Power Systems, IEEE Transactions on Power Systems, Vol. 14, No. 4, pp. 1362-1368.

[30]. Cau TDH and Kaye, R.J. (2002). Evolutionary Optimization Method for multi storage hydrothermal scheduling, IEE Proc. – Gener. Transm. Distrib., Vol. 149, No. 2, pp. 152-156.

[31]. Nidul Sinha, Chakrabarti, R., and Chattopadhyay, P.K. (2003). Fast Evolutionary Programming Techniques for Short-Term Hydrothermal Scheduling, IEEE Transactions on Power Systems, Vol. 18, No. 1, 2003, pp. 214-220.

[32]. Shyh-Jier Huang, (2002). Enhancement of Hydroelectric Generation Scheduling Using Ant Colony System Based Optimization Approaches, IEEE Transactions on Energy Conversion, Vol. 16, No. 3, pp. 296-301.

[33]. T. Venkatesan, & M.Y. Sanavullah, Implementation of Modified SFLA for the Thermal Unit Commitment Problem, International Review on Modelling and Simulations, Vol. 5. No. 1, 2012, pp. 450-457.

[34]. Christober Asir Rajan, C. (2010). HybridizingEvolutionary Programming, Simulated Annealing, Tabu Search Method to Solve the Unit Commitment Problem, Journal of Electrical Engineering, Vol. 10, No. 1, 2010, pp. 34-41.

[35]. Nimain Charan Nayak, C. Christober Asir Rajan, (2011). Thermal Unit Commitment Scheduling Problem in Utility System by Simulated Annealing Embedded Evolutionary Programming Method, International Review on Modelling and Simulations, Vol. 4. No. 6, pp. 3188-3194.

[36]. M.S. Javadi, A. Meskarbashi, R. Azami, Gh. Hematipour, A. Javadinasab, (2011). Security Constrained Unit Commitment in Iran's Electricity Market, International Review on Modelling and Simulations, Vol. 4. No. 6, 2011, pp. 3104-3112.

[37]. M.S. Javadi, A. Meskarbashi, R. Azami, Gh. Hematipour, A. Javadinasab, (2011). Emission Controlled Security Constrained Unit Commitment Considering Hydro- Thermal Generation Units, International Review on Modelling and Simulations, Vol. 4. No. 6, 2011, pp. 3243- 3250.

[38]. Chitra Selvi, S., Kumudini Devi, R.P., Christober Asir Rajan, C. (2009). A Hybrid Approaches for the Profit Based Unit Commitment Problem in the Deregulated Markets, Journal of Electrical Engineering, Vol. 9, No. 3, pp. 35-41.

[39]. S. Ganesan, & S. Subramanian, (2012). Reliability Constrained Thermal Unit Commitment Solution Using a Hybrid Approach, International Review on Modelling and Simulations, Vol. 5. No. 1, 2012, pp. 434-441.

[40]. Ahmed Bensalem, Abdelmalik Bouhentala, & Salah Eddine Zouzou, (2006). Optimal Hydropower Generation Management, Journal of Electrical Engineering, Vol. 6, No. 2, 2006, pp. 21-26.

[41]. Allen J. Wood and Wollenberg BF, Power Generation, Operation and Control, John Wiley & Sons, 1984.

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Research Paper

Optimization of Energy Efficient Subcarrier and Power Allocation in Multi User OFDMA Systems

M. Vadivel* , H. Ranganathan**

* Research Scholar, Sathyabama University, Chennai, India.

** Principal, Rajiv Gandhi College of Engineering, Chennai, India.

Vadivel.M., and Ranganathan.H. (2012). Optimization of Energy Efficient Subcarrier and Power Allocation in Multi User OFDMA Systems. i-manager’s Journal on Embedded Systems, 1(3), 26-31. https://doi.org/10.26634/jes.1.3.1992

Abstract

To utilize the energy efficiently which is available in battery of all the mobile stations is an important scenario in wireless communication systems. Better spectral efficiency can be achieved in a wireless communication by finding the energy required per bit. In this paper, we are analyzing the energy efficient resource allocation methods for a Multi User (MU) Orthogonal Frequency Division Multiple Access (OFDMA) system. We are proposing the better energy efficient optimization algorithm to maximize the energy efficiency by assuming the factors CSI, user selection, subcarrier selection, data rate selection and power allocation. The proposed optimization algorithm minimize the total transmit power consumption with the required number of bits. Simulation results show that the proposed optimization algorithm provides better performance which is very close to optimal performance with low transmit power consumption and low complexity.

References

[1]. Jungsup Song and Dong Hoi Kim, “Subcarrier and Bit Allocation Scheme for the MA Problem based on the Ant Colony Optimization to Minimize Power Consumption in OFDMA Systems”, International Journal of Innovative Computing, Information and – Control Volume 7, Number 8, August 2011, pp. 4755 – 4764.

[2]. Fourat Haider, Cheng-Xiang Wang, Harald Haas, Erol Hepsaydir and Xiaohu Ge, “Energy-Efficient Subcarrierand- Bit Allocation in Multi-User OFDMA Systems”.

[3]. Zukang Shen, Jeffrey G. Andrews, and Brian L. Evans, “Adaptive Resource Allocation in Multiuser OFDM Systems with Proportional Rate Constraints”, IEEE Trans. on Wireless Communications, July 2005.

[4]. Samip Malla, Birendra Ghimire, Mark C. Reedz and Harald Haasy, “Energy Efficient Resource Allocation in OFDMA Networks Using Ant-Colony Optimization”.

[5]. Guopeng Zhang, Peng Liu and Enjie Ding, “Energy Efficient resource allocation in non-cooperative multi- cell OFDMA systems”, Journal of Systems Engineering and Electronics Vol. 22, No. 1, February 2011, pp.175–182.

[6]. Derrick Wing Kwan Ng and Robert Schober, “Energy Efficient Resource Allocation in Multi-Cell OFDMA Systems with Limited Backhaul Capacity”.

[7]. Akbari A. “Energy-efficient resource allocation in wireless OFDMA systems” Personal Indoor and Mobile Radio Communications (PIMRC), IEEE International Symposium, 2010, pp. 1731 - 1735.

[8]. Derrick Wing Kwan Ng and Robert Schober, “Energy Efficient Resource Allocation in OFDMA Systems with Large Numbers of Base Station Antennas”.

[9]. Fatma Irem Sokmen, Tolga Girici, “Energy-Efficient Resource Allocation in Cooperative OFDMA Systems.”

[10]. Derrick Wing Kwan Ng, Ernest S. Lo and Robert Schober, “Energy Efficient Resource Allocation for Secure OFDMA Systems” IEEE Transactions On Vehicular Technology, Vol. 61, No. 6, July 2012, pp.2572-2585.

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Research Paper

A Comparative Study of P, I, P-I and I-P Controllers for Speed Control of Brushless DC motor using Powersim (PSIM) software

G. Prasad* , G Tulasi Ram Das**

* Department of Electrical and Electronics Engineering, GIT, GITAM University, Visakhapatnam, 530045, Andhra Pradesh, India.

Department of Electrical Engineering, College of Engineering, Osmania University, Hyderabad, Andhra Pradesh, India.

* Hon'ble Vice-Chancellor, JNTUK, Kakinada, Andhra Pradesh, India.

Prasad.G., Prasad.P.V.N., and Das,T,R.G. (2012). A Comparative Study Of P, I, P-I And I-P Controllers for Speed Control of Brushless DC Motor using Powersim (PSIM) Software. i-manager’s Journal on Embedded Systems, 1(3), 32-39. https://doi.org/10.26634/jes.1.3.1993

Abstract

This paper presents a comparative study of various controllers for the speed control of BLDC Motor. The most commonly used controller for the speed control of motor is Proportional-Integral (P-I) controller. However, the P-I controller has some disadvantages such as: the high starting overshoot, sensitivity to controller gains and sluggish response due to sudden disturbance. So, the relatively new Integral-Proportional (I-P) controller is proposed to overcome the disadvantages of the P-I controller and the performance these controllers are compared with P, I, P-I and I-P controllers. Simulation results are presented and analyzed for all the controllers. It is observed that I-P controllers give better responses than the traditional P-I for the speed control of BLDC motor drives.

References

[1]. P. Yedamale, & Brushless, D.C. (BLDC) (2009). Motor Fundamentals. Chandler, AZ: Microchip Technology, Inc., last access; March 15,

[2]. M. Cunkas and Omer Aydogudu, (2010). Realization of Fuzzy Logic Controlled Brushless DC motor drives using MATLAB/SIMULINK, Mathematical and Computational Applications, Vol. 15, No. 2, pp. 218-229.

[3]. B.K. Lee and M. Ehsani (2003). Advanced Simulation Model for Brushless DC Motor Drives, Electric Power Components and Systems 31, 841–868.

[4]. B.K. Lee and M.A. Ehsani, (2001). Simplified functional model for 3-phase voltage-source inverter using switching function concept, IEEE Trans. on Industrial Electronics 48, 309–321.

[5]. C. Subba Rami Reddy and M. Surya Kalavathi, (2011). Performance evaluation of hybrid fuzzy logic controller for brushless dc motor drive, International Journal of Engineering Science and Technology (IJEST), ISSN : 0975- 5462, Vol. 3, No. 6 June.

[6]. P. Pillay and R. Krishnan, (1989). Modeling, simulation, and analysis of permanent-magnet motor drives, part II: the brushless DC motor drive, IEEE Trans. on Industry Applications 25, 274–279.

[7]. B.K. Lee and M.A. Ehsani, (2001). Simplified functional model for 3-phase voltage-source inverter using switching function concept, IEEE Trans. on Industrial Electronics 48, 309–321.

[8]. E.P. Wiechmann, P.D. Ziogas, and V.R. Stefanovic, (1985). Generalized functional model for three phase PWM inverter/rectifier converters, Proc. of the IEEE IndustryApplication Society Annual Meeting IAS'85, pp. 984–993.

[9]. L. Salazar and G. Joos, (1994). PSPICE simulation of three-phase inverters by means of switching functions, IEEE Trans. on Power Electronics, vol. 9, no. 1, pp. 35–42, January.

[10]. P.D. Evans and D. Brown, (1990). Simulation of brushless DC drives, Proc. of the IEE, Vol. 137, No. 5, pp. 299–308, September.

i-manager's Journal on Embedded Systems (JES)

Current Issue Vol. 12 Issue 2

Most Read

Most Cited

Volume 1 Issue 3 August - October 2012

65nm CMOS LVDS I/O Transmitter Implementation with 600Mbps Data Rate

Alexey Balashov* , Andrey Malkov**

*-** Freescale Semiconductor, Moscow, Russia.

Balashov,A., and Malkov,A., (2013). 65nm CMOS LVDS I/O Transmitter Implementation with 600 Mbps Data Rate. i-manager’s Journal on Embedded Systems, 1(3), 1-6. https://doi.org/10.26634/jes.1.3.1989

Abstract

References

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Comparison Of Multi Output Series Resonant Inverter And Cyclo Inverter Induction Heater Systems

S. Jaanaa Rubavathy* , Dr. P. Murugesan**

* Research Scholar, Sathyabama University, Chennai, India. ** Professor, S.A. Engineering College, Chennai, India.

Rubavathy,J.S., and Murugesan.P. (2012). Comparison of Multi Output Series Resonant Inverter and Cyclo Inverter Induction Heater Systems. i-manager’s Journal on Embedded Systems, 1(3), 7-13. https://doi.org/10.26634/jes.1.3.1990

Abstract

References

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A Hybrid Evolutionary Programming – Tabu Search Method with Cooling-Banking Constraints for Hydro Thermal Scheduling in a Large Power System

Nimain Charan Nayak* , C. Christober Asir Rajan**

* Research Scholar, Dept. of EEE, Sathyabama University, Chennai, India. ** Associate Professor, Dept. of EEE, Pondicherry Engineering College, Puducherry, India.

Nayak,N,C., and Rajan,C,A.C., (2012). A Hybrid Evolutionary Programming – Tabu Search Method With Cooling – Banking Constraints For Hydro Thermal Scheduling In A Large Power System. i-manager’s Journal on Embedded Systems, 1(3), 14-25. https://doi.org/10.26634/jes.1.3.1991

Abstract

References

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Optimization of Energy Efficient Subcarrier and Power Allocation in Multi User OFDMA Systems

M. Vadivel* , H. Ranganathan**

* Research Scholar, Sathyabama University, Chennai, India. ** Principal, Rajiv Gandhi College of Engineering, Chennai, India.

Vadivel.M., and Ranganathan.H. (2012). Optimization of Energy Efficient Subcarrier and Power Allocation in Multi User OFDMA Systems. i-manager’s Journal on Embedded Systems, 1(3), 26-31. https://doi.org/10.26634/jes.1.3.1992

Abstract

References

Full Article (HTML)

Pdf

A Comparative Study of P, I, P-I and I-P Controllers for Speed Control of Brushless DC motor using Powersim (PSIM) software

G. Prasad* , G Tulasi Ram Das**

Prasad.G., Prasad.P.V.N., and Das,T,R.G. (2012). A Comparative Study Of P, I, P-I And I-P Controllers for Speed Control of Brushless DC Motor using Powersim (PSIM) Software. i-manager’s Journal on Embedded Systems, 1(3), 32-39. https://doi.org/10.26634/jes.1.3.1993

Abstract

References

Full Article (HTML)

Pdf

* Research Scholar, Sathyabama University, Chennai, India.

** Professor, S.A. Engineering College, Chennai, India.

* Research Scholar, Dept. of EEE, Sathyabama University, Chennai, India.

** Associate Professor, Dept. of EEE, Pondicherry Engineering College, Puducherry, India.

* Research Scholar, Sathyabama University, Chennai, India.

** Principal, Rajiv Gandhi College of Engineering, Chennai, India.