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A robust fractional order fuzzy P + fuzzy I + fuzzy D controller for nonlinear and uncertain system

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Abstract

In this paper, a robust fractional order fuzzy P + fuzzy I + fuzzy D (FOFP + FOFI + FOFD) controller is presented for a nonlinear and uncertain 2-link planar rigid manipulator. It is a nonlinear fuzzy controller with variable gains that makes it selfadjustable or adaptive in nature. The fractional order operators further make it more robust by providing additional degrees of freedom to the design engineer. The integer order counterpart, fuzzy P + fuzzy I + fuzzy D (FP + FI + FD) controller, for a comparative study, was realized by taking the integer value for the fractional order operators in FOFP + FOFI + FOFD controller. The performances of both the fuzzy controllers are evaluated for reference trajectory tracking and disturbance rejection with and without model uncertainty and measurement noise. Genetic algorithm was used to optimize the parameters of controller under study for minimum integral of absolute error. Simulation results demonstrated that FOFP + FOFI + FOFD controller show much better performance as compared to its counterpart FP + FI + FD controller in servo as well as the regulatory problem and in model uncertainty and noisy environment FOFP + FOFI + FOFD controller demonstrated more robust behavior as compared to the FP + FI + FD controller. For the developed controller bounded-input and bounded-output stability conditions are also developed using Small Gain Theorem.

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References

  1. K. J. Astrom, T. Hagglund. PID Controllers, 2nd ed., New York, USA: Instrument Society of America, 1995.

    Google Scholar 

  2. K. J. Åström, T. Hägglund, Advanced PID Controllers, 1st ed., Research Triangle Park, USA: Instrumentation, Systems and Automation Society, 2006.

    Google Scholar 

  3. M. A. Johnson, M. H. Moradi. PID Control, London, UK: Springer-Verlag, 2005.

    Book  Google Scholar 

  4. S. Bennett. Development of the PID controller. IEEE Control System Magazine, vol. 13, no. 6, pp. 58–65, 1993.

    Article  Google Scholar 

  5. K. J. Aström, U. Borisson, L. Ljung, B. Wittenmark. Theory and applications of self-tuning regulators. Automatica, vol. 13, no. 5, pp. 457–476, 1977.

    Article  MATH  Google Scholar 

  6. K. J. Aström. Theory and applications of adaptive control-A survey. Automatica, vol. 19, no. 5, pp. 471–486, 1983.

    Article  Google Scholar 

  7. G. Chen. Conventional and fuzzy PID controllers: An overview. International Journal of Intelligent and Control Systems, vol. 1, no. 2, pp. 235–246, 1996.

    Article  MathSciNet  Google Scholar 

  8. H. Ying. Fuzzy Control and Modeling: Analytical Foundations and Applications, New York, USA: Wiley, 2000.

    Book  Google Scholar 

  9. G. R. Chen. Introduction to Fuzzy Systems, London, UK: Chapman & Hall/CRC Press, 2006.

    Google Scholar 

  10. H. Ying, W. Siler, J. J. Buckley. Fuzzy control theory: A nonlinear case. Automatica, vol. 26, no. 3, pp. 513–520, 1990.

    Article  MathSciNet  MATH  Google Scholar 

  11. H. A. Malki, H. D. Li, G. R. Chen. New design and stability analysis of fuzzy proportional-derivative control systems. IEEE Transactions on Fuzzy Systems, vol. 2, no. 4, pp. 245–254, 1994.

    Article  Google Scholar 

  12. D. Misir, H. A Malki, G. R. Chen. Design and analysis of a fuzzy proportional-integral-derivative controller. Fuzzy Set and System, vol. 79, no. 3, pp. 297–314, 1996.

    Article  MathSciNet  MATH  Google Scholar 

  13. P. Sooraksa, G. R. Chen. Mathematical modeling and fuzzy control of a flexible-link robot arm. Mathematical and Computer Modeling, vol. 27, no. 6, pp. 73–93, 1998.

    Article  MATH  Google Scholar 

  14. J. Carvajal, G. R. Chen, H. Ogmen. Fuzzy PID controller: Design, analysis, performance evaluation, and stability analysis. Information Sciences, vol. 123, no. 3–4, pp. 249–270, 2000.

    Article  MathSciNet  MATH  Google Scholar 

  15. J. L. Lu, H. Ying, Z. G. Sun, P. Y. Wu, G. R. Chen. Real-time ultrasound-guided fuzzy control of tissue coagulation progress during laser heating. Information Sciences, vol. 123, no. 3–4, pp. 271–280, 2000.

    Article  Google Scholar 

  16. K. S. Tang, K. F. Man, G. Chen. Solar plant control using genetic fuzzy PID controller. In Proceedings of the 26th IEEE Annual Conference of the Industrial Electronics Society, IEEE, Nagoya, Japan, vol. 3, pp. 1686–1691, 2000.

    Google Scholar 

  17. K. S. Tang, K. F. Man, G. Chen, S. Kwong. An optimal fuzzy PID controller. IEEE Transactions on Industrial Electronics, vol. 48, no. 4, pp. 757–765, 2001.

    Article  Google Scholar 

  18. J. H. Kim, S. J. Oh. A fuzzy PID controller for nonlinear and uncertain system. Soft Computing, vol. 4, no. 2, pp. 123–129, 2000.

    Article  MathSciNet  Google Scholar 

  19. J. L. Lu, G. R. Chen, H. Ying. Predictive fuzzy PID control: Theory, design and simulation. Information Science, vol. 137, no. 1–4, pp.157–187, 2001.

    Article  MathSciNet  MATH  Google Scholar 

  20. K. S. Tang, K. F Man, G. R. Chen, S. Kwang. A GAoptimized fuzzy PD+ I controller for nonlinear systems. In Proceedings of the 27th Annual IEEE Conference of the Industrial Electronics Society, IECON’01, IEEE, Denver, USA, vol. 1, pp. 718–723, 2001.

    Google Scholar 

  21. M. P. V. S. Veeraiah, S. Majhi, C. Mahanta. Fuzzy proportional integral-proportional derivative (PI-PD) controller. In Proceedings of the American Control Conference, IEEE, Boston, USA, pp. 4028–4033, 2004.

    Google Scholar 

  22. V. Kumar, A. P. Mittal. Parallel fuzzy P + Fuzzy I + fuzzy D controller: Design and performance evaluation. International Journal of Automation and Computing, vol. 7, no. 4, pp. 463–471, 2010.

    Article  Google Scholar 

  23. V. Kumar, B. C. Nakra, A. P. Mittal. Some Investigations on fuzzy P + Fuzzy I + fuzzy D controller for non-stationary process. International Journal of Automation and Computing, vol. 9, no. 5, pp. 449–458, 2012.

    Article  Google Scholar 

  24. V. Kumar, A. P. Mittal, R. Singh. Stability analysis of parallel fuzzy P + fuzzy I + fuzzy D control systems. International Journal of Automation and Computing, vol. 10, no. 2, pp. 91–98, 2013.

    Article  Google Scholar 

  25. V. Kumar, K. P. S. Rana, A. Kumar. Design, performance, and stability analysis of a formula-based fuzzy PI controller. International Journal of Innovative Computing, Information and Control, vol. 7, no. 7(B), pp. 4291–4308, 2011.

    Google Scholar 

  26. V. Kumar, B. C. Nakra, A. P. Mittal. A review of classical and fuzzy PID controllers. International Journal of Intelligent Control Systems, vol. 16, no. 3, pp. 170–181, 2011.

    Google Scholar 

  27. C. A. Monje, Y. Chen, B. M. Vinagre, D. Xue, V. Feliu. Fractional-order Systems and Controls: Fundamentals and Applications, London, UK: Springer-Verlag, 2010.

    Book  MATH  Google Scholar 

  28. D. Valério, J. S. D. Costa. An Introduction to Fractional Control, London, UK: IET, 2013.

    MATH  Google Scholar 

  29. R. Sharma, K. P. S. Rana, V. Kumar. Performance analysis of fractional order fuzzy PID controllers applied to a robotic manipulator. Expert Systems with Applications, vol. 41, no. 9, pp. 4274–4289, 2014.

    Article  Google Scholar 

  30. H. Delavari, R. Ghaderi, A. Ranjbar, S. H. HosseinNia, S. Momani. Adaptive fractional PID controller for robotic manipulator. In Proceedings of the 4th IFAC Workshop on Fractional Differentiation and Its Applications, IEEE, Badajoz, Spain, pp. 1–7, 2010.

    Google Scholar 

  31. I. Pan, S. Das. Chaotic multi-objective optimization based design of fractional order PID controller in AVR system. International Journal of Electrical Power & Energy Systems, vol. 43, no. 1, pp. 393–407, 2012.

    Article  Google Scholar 

  32. S. Das, I. Pan, S. Das, A. Gupta. A novel fractional order fuzzy PID controller and its optimal time domain tuning based on integral performance indices. Engineering Applications of Artificial Intelligence, vol. 25, no. 2, pp. 430–442, 2012.

    Article  Google Scholar 

  33. S. Das, I. Pan, S. Das. Performance comparison of optimal fractional order hybrid fuzzy PID controllers for handling oscillatory fractional order processes with dead time. ISA Transactions, vol. 52, no. 4, pp. 550–566, 2013.

    Article  Google Scholar 

  34. H. Delavari, R. Ghaderi, N. A. Ranjbar, S. Momani. Fuzzy fractional order sliding mode controller for nonlinear systems. Communication in Nonlinear Science and Numerical Simulation, vol. 15, no. 4, pp. 963–978, 2010.

    Article  MathSciNet  MATH  Google Scholar 

  35. J. J. Craig. Introduction to Robotics and Control: Mechanics and Control, London, UK: Pearson Education, 2005.

    Google Scholar 

  36. C. A. Monje, B. M. Vinagre, V. Feliu, Y. Q. Chen. Tuning and auto-tuning of fractional order controllers for industrial application. Control Engineering Practice, vol. 16, no. 7, pp. 798–812, 2008.

    Article  Google Scholar 

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Acknowledgements

The authors would like to thank their institute for providing excellent experimental facilities in the Advanced Process Control Lab (APCL) and Virtual Instrumentation and Control Technology (VICT), Centre for research.

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Correspondence to Vineet Kumar.

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Recommended by Associate Editor Jyh-Horng Chou

Vineet Kumar received the M. Sc. degree in physics with electronics from Govind Ballabh Pant University of Agriculture & Technology, India, M.Tech. degree in instrumentation from Regional Engineering College, Kurukshetra, India and Ph.D. degree from Delhi University, India. He has served industry from 1996 to 2000. Since July 2000, he has been associated with the Netaji Subhas Institute of Technology (NSIT), Delhi University, India. Currently, he holds the post of associate professor in the Instrumentation and Control Engineering Division, NSIT, India.

His research interests include process dynamics and control, intelligent control techniques and their applications, digital signal processing, and robotics.

K. P. S. Rana received the M. Sc. degree in physics (electronics major) from Meerut University, India in 1989 and M.Tech. degree in instrumentation from Indian Institute of Technology (IIT) India in 1991 and Ph. D. degree in “intelligent methods for complex vibration measurement and control” from Guru Gobind Singh Indraprastha University, India in 2011. He has served Indian Space Research Organization (ISRO) from 1993–2002 as Scientist “SD” in Sensors Division at Bangalore, India. Since August 2000, he has been with Netaji Subhas Institute of Technology (NSIT), Delhi University, India at the Department of Instrumentation and Control Engineering where he has served as assistant professor from August 2000 to December 2005, and since January 2006 he has been serving as associate professor.

His research and teaching interests include PC based measurement, real time systems, intelligent instrumentation and control, sensor linearization, digital signal processing.

Jitendra Kumar received the B.Tech. degree in electronics and instrumentation engineering from West Bengal University of Technology, India and M.Tech. degree in process control from Netaji Subhas Institute of Technology, Delhi University, India in year 2010 and 2013 respectively. He served as a lecturer at GLA University, Mathura, India. Currently, he is a Ph.D. candidate and also serving as a teaching-cum-research-fellow in the Division of Instrumentation and Control Engineering at Netaji Subhas Institute of Technology, Delhi University, India.

His research interests include the areas of conventional adaptive control, intelligent adaptive control, and different optimization techniques.

Puneet Mishra received the B. Tech. degree in electronics and instrumentation engineering from Uttar Pradesh Technical University, India and the M. Sc. degree in control and instrumentation engineering from Delhi College of Engineering, Delhi University, India in year 2009 and 2011 respectively. He was an assistant professor at GLA University, India. Currently, he is a Ph. D. candidate and also serving at the Division of Instrumentation and Control Engineering at Netaji Subhas Institute of Technology, India as a teaching-cum-research-fellow.

His research interests include intelligent adaptive control, fractional order modeling and control, and bio-inspired optimization techniques.

Sreejith S Nair received the B.Tech. degree in electronics and communication from Cochin University, Kerala in 2008. He received the M.Tech. degree in signal processing from Guru Gobind Singh Indraprastha University, India in 2011. He is currently a Ph. D. degree candidate at Netaji Subhas Institute of technology, India.

His research interests include discretetime signal processing, statistical signal processing, image processing, microwave filter design and fractional control.

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Kumar, V., Rana, K.P.S., Kumar, J. et al. A robust fractional order fuzzy P + fuzzy I + fuzzy D controller for nonlinear and uncertain system. Int. J. Autom. Comput. 14, 474–488 (2017). https://doi.org/10.1007/s11633-016-0981-7

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