Neuro Fuzzy and Self Tunging Fuzzy Controller to Improve Pitch and Yaw Control Systems Resposes of Twin Rotor MIMO System
In this paper, Neuro-Fuzzy based Fuzzy Subtractive
Clustering Method (FSCM) and Self Tuning Fuzzy PD-like
Controller (STFPDC) were used to solve non-linearity and trajectory
problems of pitch AND yaw angles of Twin Rotor MIMO system
(TRMS). The control objective is to make the beams of TRMS reach
a desired position quickly and accurately. The proposed method
could achieve control objectives with simpler controller. To simplify
the complexity of STFPDC, ANFIS based FSCM was used to
simplify the controller and improve the response. The proposed
controllers could achieve satisfactory objectives under different input
signals. Simulation results under MATLAB/Simulink® proved the
improvement of response and superiority of simplified STFPDC on
Fuzzy Logic Controller (FLC).
[1] Manual, Twin Rotor MIMO System Manual. UK Feedback Instruments
Ltd., 1998.
[2] B. U. Islam, N. Ahmed, D. L. Bhatti, and S. Khan, "Controller design
using fuzzy logic for a twin rotor MIMO system," 2003, pp. 264-268.
[3] Ch. Sh. Liu, L. R. Chen, B. Z. Li, Sh. K. Chen, Z. S. Zeng, "
Improvement of the Twin Rotor MIMO System Tracking and Transient
Response Using Fuzzy Control Technology", 2006, pp 1-6.
[4] J. G. Juang. W. K. Liu, Ch. Y. Tsai, "Intelligent Control Scheme for
Twin Rotor MIMO System", Taipei, Taiwan, 2005, pp. 102-107.
[5] F. M. Adebrez, M. S. Alam, M. O. Tokhi, "Hybrid Control Scheme for
Tracking Performance of a Flexible system", Springer Berlin
Heidelberg, 2006, pp. 543-550.
[6] A. Rahideh, M. H. Shaheed, "Hybrid fuzzy-PID-based Control of a Twin
Rotor MIMO System", 2006, pp. 49-54.
[7] J. G. Juang, K. T. Tu, W. K. Liu, "Hybrid Intelligent PID Control for
MIMO System", Springer-Verlag, Berlin Heidelberg, 2006, pp. 654-663.
[8] J. G. Juang, K. T. Tu, W. K. Liu, "Comparison of classical control and
intelligent control for a MIMO system", Applied Mathematics and
Computation, Elsevier Inc., 2008.
[9] J. G. Juang, W. K. Liu, "Fuzzy Compensator Using RGA for TRMS
Control", Springer-Verlag, Berlin Heidelberg, 2006, pp. 120-126.
[10] J. G. Juang, K. T. Tu, W. K. Liu, "Optimal Fuzzy Sweitching Grey
Prediction with RGA for TRMS Control", Taipei, Taiwan, 2006 pp. 681-
686..
[11] H. Zhang and D. Liu, Fuzzy Modeling and Fuzzy Control: Control
Engineering, Brikha├╝ser, Boston, 2006.
[12] S. Chopra, R. Matira, V. Kumar, "Analysis of Fuzzy PI and PD Type
Controllers Using Subtractive Clustering" International Journal of
Computational Cognition, 2006, Vol. 4, No. 2.
[13] S. Chopra, R. Matira, V. Kumar, "Neural Network Tuned Fuzzy
Controller for MIMO System", International Journal of Intelligent
Technology, 2007, Vol. 2, No. 1.
[14] D. Driankov, H. Hellendoorn, M. Reinfrank, "An Introduction
to Fuzzy Control", Springer-Verlag, New York, 1993.
[15] R. K. Mudi and N. R. Pal, "A self tuning PI controller", Journal
of Fuzzy sets and systems, Elsevier Science, 2000.
[16] Getting Started, ANFIS and the ANFIS GUI, MathWorks Inc.,
http://www.mathworks.com, accessed on 24 September 2008.
[17] S. L. Chiu, "Fuzzy models identification based on cluster estimation",
Journal of Intelligent and Fuzzy Systems, John Wiley & Sons, 1994, Vol.
2, pp. 267-278.
[1] Manual, Twin Rotor MIMO System Manual. UK Feedback Instruments
Ltd., 1998.
[2] B. U. Islam, N. Ahmed, D. L. Bhatti, and S. Khan, "Controller design
using fuzzy logic for a twin rotor MIMO system," 2003, pp. 264-268.
[3] Ch. Sh. Liu, L. R. Chen, B. Z. Li, Sh. K. Chen, Z. S. Zeng, "
Improvement of the Twin Rotor MIMO System Tracking and Transient
Response Using Fuzzy Control Technology", 2006, pp 1-6.
[4] J. G. Juang. W. K. Liu, Ch. Y. Tsai, "Intelligent Control Scheme for
Twin Rotor MIMO System", Taipei, Taiwan, 2005, pp. 102-107.
[5] F. M. Adebrez, M. S. Alam, M. O. Tokhi, "Hybrid Control Scheme for
Tracking Performance of a Flexible system", Springer Berlin
Heidelberg, 2006, pp. 543-550.
[6] A. Rahideh, M. H. Shaheed, "Hybrid fuzzy-PID-based Control of a Twin
Rotor MIMO System", 2006, pp. 49-54.
[7] J. G. Juang, K. T. Tu, W. K. Liu, "Hybrid Intelligent PID Control for
MIMO System", Springer-Verlag, Berlin Heidelberg, 2006, pp. 654-663.
[8] J. G. Juang, K. T. Tu, W. K. Liu, "Comparison of classical control and
intelligent control for a MIMO system", Applied Mathematics and
Computation, Elsevier Inc., 2008.
[9] J. G. Juang, W. K. Liu, "Fuzzy Compensator Using RGA for TRMS
Control", Springer-Verlag, Berlin Heidelberg, 2006, pp. 120-126.
[10] J. G. Juang, K. T. Tu, W. K. Liu, "Optimal Fuzzy Sweitching Grey
Prediction with RGA for TRMS Control", Taipei, Taiwan, 2006 pp. 681-
686..
[11] H. Zhang and D. Liu, Fuzzy Modeling and Fuzzy Control: Control
Engineering, Brikha├╝ser, Boston, 2006.
[12] S. Chopra, R. Matira, V. Kumar, "Analysis of Fuzzy PI and PD Type
Controllers Using Subtractive Clustering" International Journal of
Computational Cognition, 2006, Vol. 4, No. 2.
[13] S. Chopra, R. Matira, V. Kumar, "Neural Network Tuned Fuzzy
Controller for MIMO System", International Journal of Intelligent
Technology, 2007, Vol. 2, No. 1.
[14] D. Driankov, H. Hellendoorn, M. Reinfrank, "An Introduction
to Fuzzy Control", Springer-Verlag, New York, 1993.
[15] R. K. Mudi and N. R. Pal, "A self tuning PI controller", Journal
of Fuzzy sets and systems, Elsevier Science, 2000.
[16] Getting Started, ANFIS and the ANFIS GUI, MathWorks Inc.,
http://www.mathworks.com, accessed on 24 September 2008.
[17] S. L. Chiu, "Fuzzy models identification based on cluster estimation",
Journal of Intelligent and Fuzzy Systems, John Wiley & Sons, 1994, Vol.
2, pp. 267-278.
@article{"International Journal of Mechanical, Industrial and Aerospace Sciences:57129", author = "Thair Sh. Mahmoud and Tang Sai Hong and Mohammed H. Marhaban", title = "Neuro Fuzzy and Self Tunging Fuzzy Controller to Improve Pitch and Yaw Control Systems Resposes of Twin Rotor MIMO System", abstract = "In this paper, Neuro-Fuzzy based Fuzzy Subtractive
Clustering Method (FSCM) and Self Tuning Fuzzy PD-like
Controller (STFPDC) were used to solve non-linearity and trajectory
problems of pitch AND yaw angles of Twin Rotor MIMO system
(TRMS). The control objective is to make the beams of TRMS reach
a desired position quickly and accurately. The proposed method
could achieve control objectives with simpler controller. To simplify
the complexity of STFPDC, ANFIS based FSCM was used to
simplify the controller and improve the response. The proposed
controllers could achieve satisfactory objectives under different input
signals. Simulation results under MATLAB/Simulink® proved the
improvement of response and superiority of simplified STFPDC on
Fuzzy Logic Controller (FLC).", keywords = "Fuzzy Subtractive Clustering Method, Neuro Fuzzy,Self Tuning Fuzzy Controller, and Twin Rotor MIMO System.", volume = "3", number = "2", pages = "185-5", }