Effect of Adaptation Gain on system Performance for Model Reference Adaptive Control Scheme using MIT Rule
Adaptive control involves modifying the control law
used by the controller to cope with the fact that the parameters of the
system being controlled change drastically due to change in
environmental conditions or in system itself. This technique is based
on the fundamental characteristic of adaptation of living organism.
The adaptive control process is one that continuously and
automatically measures the dynamic behavior of plant, compares it
with the desired output and uses the difference to vary adjustable
system parameters or to generate an actuating signal in such a way so
that optimal performance can be maintained regardless of system
changes. This paper deals with application of model reference
adaptive control scheme in first order system. The rule which is used
for this application is MIT rule. This paper also shows the effect of
adaptation gain on the system performance. Simulation is done in
MATLAB and results are discussed in detail.
[1] Karl J. Astrom, Bjorn Wittenmark, "Adaptive control" , 2nd ed.
Pearson Education Asia, 2001, pp185-225.
[2] Rey-Chue Hwang, Huang-Chu Huang, Wei-Shen Chi, "A New
Fuzzy PID-Like Controller", IEEE international conference on
systems, man, cybernetics, vol. 5, 2000.
[3] K. S. Tang, Kim Fung Man, Guanrong Chen, Sam Kwong, "An
Optimal Fuzzy PID Controller", IEEE Transactions on industrial
electronics, vol. 48, No. 4, August 2001.
[4] K.L. Lo and M.O. Sadegh, "Systematic method for the design of a
full-scale fuzzy PID stability controller for svc to control power
system", IEEE transaction on generation transmission and
distribution Vol. 150, 2003.
[5] E. M. Jafarov, M. N. A. Parlakçı, and Y. Istefanopulos, "A New
Variable Structure PID-Controller Design for Robot Manipulators",
IEEE Transactions on control system technology, VOL. 13, NO. 1,
January 2005.
[6] Tae-Yong Choi, Kap-Ho Seo, Jin-ho ShinÜ, Ju-Jang Lee, "The
Hybrid SOF-PID Controller for a MIMO Nonlinear System",
Proceedings of the 2005 IEEE/ASME, International Conference on
Advanced Intelligent Mechatronics Monterey, California, USA, 24-
28 July, 2005.
[7] Baozhu Jia, Guang Ren and Gang Long, "Design and Stability
Analysis of Fuzzy Switching PID Controller", 6th World Congress
on Intelligent Control and Automation, June 21 - 23, 2006,
Dalian, China.
[8] Ahmed Rubaai, Marcel J. Castro-Sitiriche, Abdul Ofoli, "DSP-Based
Implementation of Fuzzy-PID Controller Using Genetic optimization
for High Performance Motor Drives", IEEE international conference on
industry applications, 2007.
[9] Ahmed Rubaai, Marcel J. Castro-Sitiriche, and Abdul R. Ofoli, "DSP-Based
Laboratory Implementation of Hybrid Fuzzy-PID Controller Using Genetic
Optimization for High-Performance Motor Drives", IEEE Transactions on
industry applications, vol. 44, No. 6, November/December 2008.
[10] Dan Sun, Jun Meng, "A Single Neuron PID Controller Based PMSM DTC
Drive System Fed by Fault Tolerant 4-Switch 3-Phase Inverter", IEEE
international conference on industrial electronics and applications, 2006.
[11] Jianjun Yao , Liquan Wang ,Caidong Wang, Zhonglin Zhang and Peng Jia,
"ANN-based PID Controller for an Electro-hydraulic Servo System", IEEE
International Conference on Automation and Logistics Qingdao, China
September 2008.
[12] Xue-Kui Wang, Xu-Hong Yang, Gang Liu, Hong Qian, "Adaptive Neuro-
Fuzzy inference system PID controller for SG water level of nuclear power
plant", Proceedings of the Eighth International Conference on Machine
Learning and Cybernetics, Baoding, 12-15 July 2009.
[13] K. Benjelloun, H. Mechlih and E.K. boukas, "A modified model reference
adaptive control algorithm for DC servomotor", second IEEE conference on
control applications, September 13-16, 1993 Vancouver, B.C.
[14] M.S.Ehsani, "Adaptive Control of Servo Motor by MRAC Method", IEEE
international conference on vehicle, power and propulsion, 2007.
[15] Mukesh kirar, Pankaj Swarnkar, Shailendra Jain, R.K.Nema, "Comparative
study of conventional and adaptive schemes for DC servomotors",
International conference on Energy Engineering ICEE, Puducherry, India,
Jan 2009.
[16] H. D. Patino and Derong Liu, "Neural network-based model reference
adaptive control system", IEEE transaction on systems, man, and
cybernatics-part B: cybernatics, vol.30, No. 1, February 2000.
[17] Qian Sang and Gang Tao, "Gain margins of model reference adaptive
control systems", 7th world congress on intelligent control and automation,
June 25-27, 2008, Chongqing, china.
[18] Pin-Yan Tsai, Hung Chu huang, Yu-Ju-Chen, Rey-Chue Hwang, "The
model reference control by auto tuning PID-like Fuzzy controller",
International conference on control applications Taipei, Taiwan, September
2-4, 2004.
[19] Maurizio cirrincione, Marcello Pucci, "An MRAS-based sensorless high
performance induction motor drive with a predictive adaptive model", IEEE
transaction on industrial electronics, vol. 52, No. 2, April 2005.
[20] Kuo-Ming Chang, "Model reference adaptive control for uncertain systems
with sector-like bounded nonlinear inputs", International conference on
control and automation, June 27-29, 2005, Budapest, Hungary.
[21] Lei zuo, Jean-Jacques E. slotine, Samir a. Nayfeh, "Model reaching
adaptive control for vibration Isolation", IEEE transaction on control
systems technology, vol. 13, No. 4, July 2005.
[22] Shen Qingbo, Ding Yuanming, "A model reference adaptive controller
design for discrete Hammerstein systems", 26th Chinese control conference,
July 26-31, 2007, Zhangjiajie, hunan, China.
[23] M.T. Benchouia, A.Ghamri, M.E.H. Benbouzid, a. Golea, S.E. Zouzou,
"Fuzzy model reference adaptive control of power converter for unity
power factor and harmonics minimization", International conference on
electrical machine and system ,October 8-11, 2007, Seoul, Korea.
[24] T.John Koo, "Stable Model Reference Adaptive Fuzzy Control of a Class of
Nonlinear Systems" IEEE Transactions on fuzzy systems, Vol. 9, No. 4, August
2001.
[25] Yuan-Rui Chen Jie Wu, Norbert C. Cheung, "Lyapunov-s Stability Theory-
Based Model Reference Adaptive Control for Permanent Magnet Linear
Motor Drives", 1st IEEE international conference on power electronics
system and applications, 2004.
[26] Kuo-Kai Shyu, Ming-Ji Yang, Yen-Mo Chen, and Yi-Fei Lin, "Model
reference adaptive control design for a shunt active-power-filter system",
IEEE Transactions on industrial electronics, vol. 55, No. 1, January 2008.
[27] Ding Yuan, Timothy Chang, "Model reference input shaper design with
applications to a high speed robotic workcell with variable loads", IEEE
transaction on industrial electronics, vol. 55, No. 2, February 2008.
[28] M-arcio Stefanello, Jo˜ao Marcos Kanieski , Rafael Cardoso and Hilton
Ab'ılio Gr¨undling, "Design of a Robust Model Reference Adaptive
Control for a Shunt Active Power Filter", 34th IEEE international
conference on industrial electronics 2008.
[29] HongZhe Jin and JangMyung Lee, "An RMRAC current regulator for
permanent-magnetbsynchronous motor based on statistical model
interpretation", IEEE transaction on industrial electronics, vol. 56, No. 1,
January 2009.
[30] Francisco Jurado, Jose Ramon Saenz, "Adaptive control of a fuel
cell-microturbine hybrid power plant", IEEE transactions on energy
conversion, vol. 18, No. 2, June 2003.
[31] Bin Wu and Om P. Malik, "Multivariable adaptive control of
synchronous machines in a multimachine power system", IEEE
transactions on power system, vol. 21, No. 4, November 2006.
[32] Teresa Orlowska-Kowalska, Krzysztof, "Control of the drive system
with stiff and elastic coupling using adptive neuro-fuzzy approach"
IEEE transaction on industrial electronics, vol. 54, No. 1, February
2007.
[33] Zhenhua Jiang, Lijun Gao, Roger A. Dougal, "Adaptive control
strategy for active power sharing in hybrid fual cell/battery power
sources", IEEE transactions on energy conversion, vol. 22, No. 2,
June 2007.
[34] Daniel salomonsson, Lennart soder, Ambra sannino, "An adaptive
control system for a DC microgrid for Data Centers", IEEE
transaction on industry applications, vol. 44, No. 6,
November/December 2008.
[1] Karl J. Astrom, Bjorn Wittenmark, "Adaptive control" , 2nd ed.
Pearson Education Asia, 2001, pp185-225.
[2] Rey-Chue Hwang, Huang-Chu Huang, Wei-Shen Chi, "A New
Fuzzy PID-Like Controller", IEEE international conference on
systems, man, cybernetics, vol. 5, 2000.
[3] K. S. Tang, Kim Fung Man, Guanrong Chen, Sam Kwong, "An
Optimal Fuzzy PID Controller", IEEE Transactions on industrial
electronics, vol. 48, No. 4, August 2001.
[4] K.L. Lo and M.O. Sadegh, "Systematic method for the design of a
full-scale fuzzy PID stability controller for svc to control power
system", IEEE transaction on generation transmission and
distribution Vol. 150, 2003.
[5] E. M. Jafarov, M. N. A. Parlakçı, and Y. Istefanopulos, "A New
Variable Structure PID-Controller Design for Robot Manipulators",
IEEE Transactions on control system technology, VOL. 13, NO. 1,
January 2005.
[6] Tae-Yong Choi, Kap-Ho Seo, Jin-ho ShinÜ, Ju-Jang Lee, "The
Hybrid SOF-PID Controller for a MIMO Nonlinear System",
Proceedings of the 2005 IEEE/ASME, International Conference on
Advanced Intelligent Mechatronics Monterey, California, USA, 24-
28 July, 2005.
[7] Baozhu Jia, Guang Ren and Gang Long, "Design and Stability
Analysis of Fuzzy Switching PID Controller", 6th World Congress
on Intelligent Control and Automation, June 21 - 23, 2006,
Dalian, China.
[8] Ahmed Rubaai, Marcel J. Castro-Sitiriche, Abdul Ofoli, "DSP-Based
Implementation of Fuzzy-PID Controller Using Genetic optimization
for High Performance Motor Drives", IEEE international conference on
industry applications, 2007.
[9] Ahmed Rubaai, Marcel J. Castro-Sitiriche, and Abdul R. Ofoli, "DSP-Based
Laboratory Implementation of Hybrid Fuzzy-PID Controller Using Genetic
Optimization for High-Performance Motor Drives", IEEE Transactions on
industry applications, vol. 44, No. 6, November/December 2008.
[10] Dan Sun, Jun Meng, "A Single Neuron PID Controller Based PMSM DTC
Drive System Fed by Fault Tolerant 4-Switch 3-Phase Inverter", IEEE
international conference on industrial electronics and applications, 2006.
[11] Jianjun Yao , Liquan Wang ,Caidong Wang, Zhonglin Zhang and Peng Jia,
"ANN-based PID Controller for an Electro-hydraulic Servo System", IEEE
International Conference on Automation and Logistics Qingdao, China
September 2008.
[12] Xue-Kui Wang, Xu-Hong Yang, Gang Liu, Hong Qian, "Adaptive Neuro-
Fuzzy inference system PID controller for SG water level of nuclear power
plant", Proceedings of the Eighth International Conference on Machine
Learning and Cybernetics, Baoding, 12-15 July 2009.
[13] K. Benjelloun, H. Mechlih and E.K. boukas, "A modified model reference
adaptive control algorithm for DC servomotor", second IEEE conference on
control applications, September 13-16, 1993 Vancouver, B.C.
[14] M.S.Ehsani, "Adaptive Control of Servo Motor by MRAC Method", IEEE
international conference on vehicle, power and propulsion, 2007.
[15] Mukesh kirar, Pankaj Swarnkar, Shailendra Jain, R.K.Nema, "Comparative
study of conventional and adaptive schemes for DC servomotors",
International conference on Energy Engineering ICEE, Puducherry, India,
Jan 2009.
[16] H. D. Patino and Derong Liu, "Neural network-based model reference
adaptive control system", IEEE transaction on systems, man, and
cybernatics-part B: cybernatics, vol.30, No. 1, February 2000.
[17] Qian Sang and Gang Tao, "Gain margins of model reference adaptive
control systems", 7th world congress on intelligent control and automation,
June 25-27, 2008, Chongqing, china.
[18] Pin-Yan Tsai, Hung Chu huang, Yu-Ju-Chen, Rey-Chue Hwang, "The
model reference control by auto tuning PID-like Fuzzy controller",
International conference on control applications Taipei, Taiwan, September
2-4, 2004.
[19] Maurizio cirrincione, Marcello Pucci, "An MRAS-based sensorless high
performance induction motor drive with a predictive adaptive model", IEEE
transaction on industrial electronics, vol. 52, No. 2, April 2005.
[20] Kuo-Ming Chang, "Model reference adaptive control for uncertain systems
with sector-like bounded nonlinear inputs", International conference on
control and automation, June 27-29, 2005, Budapest, Hungary.
[21] Lei zuo, Jean-Jacques E. slotine, Samir a. Nayfeh, "Model reaching
adaptive control for vibration Isolation", IEEE transaction on control
systems technology, vol. 13, No. 4, July 2005.
[22] Shen Qingbo, Ding Yuanming, "A model reference adaptive controller
design for discrete Hammerstein systems", 26th Chinese control conference,
July 26-31, 2007, Zhangjiajie, hunan, China.
[23] M.T. Benchouia, A.Ghamri, M.E.H. Benbouzid, a. Golea, S.E. Zouzou,
"Fuzzy model reference adaptive control of power converter for unity
power factor and harmonics minimization", International conference on
electrical machine and system ,October 8-11, 2007, Seoul, Korea.
[24] T.John Koo, "Stable Model Reference Adaptive Fuzzy Control of a Class of
Nonlinear Systems" IEEE Transactions on fuzzy systems, Vol. 9, No. 4, August
2001.
[25] Yuan-Rui Chen Jie Wu, Norbert C. Cheung, "Lyapunov-s Stability Theory-
Based Model Reference Adaptive Control for Permanent Magnet Linear
Motor Drives", 1st IEEE international conference on power electronics
system and applications, 2004.
[26] Kuo-Kai Shyu, Ming-Ji Yang, Yen-Mo Chen, and Yi-Fei Lin, "Model
reference adaptive control design for a shunt active-power-filter system",
IEEE Transactions on industrial electronics, vol. 55, No. 1, January 2008.
[27] Ding Yuan, Timothy Chang, "Model reference input shaper design with
applications to a high speed robotic workcell with variable loads", IEEE
transaction on industrial electronics, vol. 55, No. 2, February 2008.
[28] M-arcio Stefanello, Jo˜ao Marcos Kanieski , Rafael Cardoso and Hilton
Ab'ılio Gr¨undling, "Design of a Robust Model Reference Adaptive
Control for a Shunt Active Power Filter", 34th IEEE international
conference on industrial electronics 2008.
[29] HongZhe Jin and JangMyung Lee, "An RMRAC current regulator for
permanent-magnetbsynchronous motor based on statistical model
interpretation", IEEE transaction on industrial electronics, vol. 56, No. 1,
January 2009.
[30] Francisco Jurado, Jose Ramon Saenz, "Adaptive control of a fuel
cell-microturbine hybrid power plant", IEEE transactions on energy
conversion, vol. 18, No. 2, June 2003.
[31] Bin Wu and Om P. Malik, "Multivariable adaptive control of
synchronous machines in a multimachine power system", IEEE
transactions on power system, vol. 21, No. 4, November 2006.
[32] Teresa Orlowska-Kowalska, Krzysztof, "Control of the drive system
with stiff and elastic coupling using adptive neuro-fuzzy approach"
IEEE transaction on industrial electronics, vol. 54, No. 1, February
2007.
[33] Zhenhua Jiang, Lijun Gao, Roger A. Dougal, "Adaptive control
strategy for active power sharing in hybrid fual cell/battery power
sources", IEEE transactions on energy conversion, vol. 22, No. 2,
June 2007.
[34] Daniel salomonsson, Lennart soder, Ambra sannino, "An adaptive
control system for a DC microgrid for Data Centers", IEEE
transaction on industry applications, vol. 44, No. 6,
November/December 2008.
@article{"International Journal of Information, Control and Computer Sciences:58881", author = "Pankaj Swarnkar and Shailendra Jain and R.K Nema", title = "Effect of Adaptation Gain on system Performance for Model Reference Adaptive Control Scheme using MIT Rule", abstract = "Adaptive control involves modifying the control law
used by the controller to cope with the fact that the parameters of the
system being controlled change drastically due to change in
environmental conditions or in system itself. This technique is based
on the fundamental characteristic of adaptation of living organism.
The adaptive control process is one that continuously and
automatically measures the dynamic behavior of plant, compares it
with the desired output and uses the difference to vary adjustable
system parameters or to generate an actuating signal in such a way so
that optimal performance can be maintained regardless of system
changes. This paper deals with application of model reference
adaptive control scheme in first order system. The rule which is used
for this application is MIT rule. This paper also shows the effect of
adaptation gain on the system performance. Simulation is done in
MATLAB and results are discussed in detail.", keywords = "Adaptive control system, Adaptation gain, MIT rule,Model reference adaptive control.", volume = "4", number = "10", pages = "1574-6", }
