Self-Structured Organizing Single-Input CMAC Control for De-icing Robot Manipulator

ABSTRACT

This paper presents a self-structured organizing single-input control system based on differentiable cerebellar model articulation controller (CMAC) for an n-link robot manipulator to achieve the high-precision position tracking. In the proposed scheme, the single-input CMAC controller is solely used to control the plant, so the input space dimension of CMAC can be simplified and no conventional controller is needed. The structure of single-input CMAC will also be self-organized; that is, the layers of single-input CMAC will grow or prune systematically and their receptive functions can be automatically adjusted. The online tuning laws of single-input CMAC parameters are derived in gradient-descent learning method and the discrete-type Lyapunov function is applied to determine the learning rates of the proposed control system so that the stability of the system can be guaranteed. The simulation results of three-link De-icing robot manipulator are provided to verify the effectiveness of the proposed control methodology.

This paper presents a self-structured organizing single-input control system based on differentiable cerebellar model articulation controller (CMAC) for an n-link robot manipulator to achieve the high-precision position tracking. In the proposed scheme, the single-input CMAC controller is solely used to control the plant, so the input space dimension of CMAC can be simplified and no conventional controller is needed. The structure of single-input CMAC will also be self-organized; that is, the layers of single-input CMAC will grow or prune systematically and their receptive functions can be automatically adjusted. The online tuning laws of single-input CMAC parameters are derived in gradient-descent learning method and the discrete-type Lyapunov function is applied to determine the learning rates of the proposed control system so that the stability of the system can be guaranteed. The simulation results of three-link De-icing robot manipulator are provided to verify the effectiveness of the proposed control methodology.

KEYWORDS

Cerebellar Model Articulation Controller (CMAC), De-Icing Robot Manipulator, Gradient-Descent Method, Self-Organizing, Signed Distance

Cerebellar Model Articulation Controller (CMAC), De-Icing Robot Manipulator, Gradient-Descent Method, Self-Organizing, Signed Distance

Cite this paper

nullT. Ngo, Y. Wang, Y. Chen and Z. Xiao, "Self-Structured Organizing Single-Input CMAC Control for De-icing Robot Manipulator,"*Intelligent Control and Automation*, Vol. 2 No. 3, 2011, pp. 241-250. doi: 10.4236/ica.2011.23029.

nullT. Ngo, Y. Wang, Y. Chen and Z. Xiao, "Self-Structured Organizing Single-Input CMAC Control for De-icing Robot Manipulator,"

References

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[2] W. Z. Gao and R. R. Selmic, “Neural Network Control of a Class of Nonlinear Systems with Actuator Saturation,” American Control Conference, Boston, 2006, pp. 147-156.

[3] Y. Zou, Y. N. Wang and X. Z. Liu, “Neural Network Robust H∞Tracking Control Strategy for robot manipulators,” Applied Mathematical Modelling, Vol. 34, No. 7, 2010, pp. 1823-1838. doi:10.1016/j.apm.2009.09.026

[4] B.-S. Chen, H.-J. Uang and C.-S. Tseng, “Robust Tracking Enhancement of Robot Systems Including Motor Dynamics: A Fuzzy-Based Dynamic Game Approach,” IEEE Transactions on Fuzzy Systems, Vol. 6, No. 4, 1998, pp. 538-552. doi:10.1109/91.728449

[5] H.-X. Li and S.-C. Tong, “A Hybrid Adaptive Fuzzy Control for a Class of Nonlinear MIMO Systems,” IEEE Transactions on Fuzzy Sysemstm, Vol. 11, No. 1, 2003, pp. 24-34. doi:10.1109/TFUZZ.2002.806314

[6] S. Labiod, M. S. Boucherit and T. M. Guerra, “Adaptive Fuzzy Control of a Class of MIMO Nonlinear Systems,” Fuzzy Set and Systems, Vol. 151, No. 1, 2005, pp. 59-77. doi:10.1016/j.fss.2004.10.009

[7] Y. G. Leu, W. Y. Wang, and T. T. Lee, “Observe Based Direct Adaptive Fuzzy Neural Control for Non-Affine Nonlinear Systems,” IEEE Transactions on Neural Networks, Vol. 16, No. 4, 2005, pp. 853-861. doi:10.1109/TNN.2005.849824

[8] R. J. Wai and Z. W. Yang, “Adaptive Fuzzy Neural Network Control Design via a T-S Fuzzy Model for a Robot Manipulator Including Actuator Dynamics,” IEEE Transactions on Systems, Man and Cybernnetics, Vol. 38, No. 5, 2008, pp. 1326-1346. doi:10.1109/TSMCB.2008.925749

[9] C.-S. Chen, “Dynamic Structure Neural Fuzzy Networks for Robust Adaptive Control of Robot Manipulators,” IEEE Transactions on Industrial Electronics, Vol. 55, No. 9, 2008, pp. 3402-3414. doi:10.1109/TIE.2008.926778

[10] B. J. Choi, S. W. Kwak and B. K. Kim, “Design of Single-Input Fuzzy Logic Controller and Its Properties,” Fuzzy Sets and Systems, Vol. 106, No. 3, 1999, pp. 299-308. doi:10.1016/S0165-0114(97)00283-2

[11] B. J. Choi, S. W. Kwak and B. K. Kim, “Design and Stability Analysis of Single-Input Fuzzy Logic Controller,” IEEE Transactions on Systems, Man and Cybernnetics, Vol. 30, No. 2, 2000, pp. 303-309. doi:10.1109/3477.836378

[12] K. Ishaque, S. S. Abdullah, S. M. Ayob and Z. Salam, “Single Input Fuzzy Logic Controller for Unmanned Underwater Vehicle,” Journal of Intelligent and Robotic Systems, Vol. 59, No. 3, 2010, pp. 87-100. doi:10.1007/s10846-010-9395-x

[13] J. S. Albus, “A New Approach to Manipulator Control: The Cerebellar Model Articulation Controller,” Journal of Dynamic Systems Measurement and Control, Vol. 97, No. 3, 1975, pp. 220-227. doi:10.1115/1.3426922

[14] H. Shiraishi, S. L. Ipri and D. D. Cho, “CMAC Neural Network Controller for Fuel-Injection Systems,” IEEE Transactions on Control Systems Technology, Vol. 3, No. 1, 1995, pp. 32-38. doi:10.1115/1.3426922

[15] S. Jagannathan, S. Commuri and F. L. Lewis, “Feedback Linearization Using CMAC Neural Networks,” Automatica, Vol. 34, No. 3, 1998, pp. 547-557. doi:10.1016/S0005-1098(97)00206-9

[16] C. T. Chiang and C. S. Lin, “CMAC with General Basis Functions,” Journal of Neural Networks, Vol. 9, No. 7, 1996, pp. 1199-1211. doi:10.1016/S0005-1098(97)00206-9

[17] Y. H. Kim and F. L. Lewis, “Optimal Design of CMAC Neural-Network Controller for Robot Manipulators,” IEEE Transactions on Systems, Man and Cybernnetics, Vol. 30, No. 1, 2000, pp. 22-31. doi:10.1109/5326.827451

[18] C. M. Lin and Y. F. Peng, “Adaptive CMAC-Based Supervisory Control for Uncertain Nonlinear Systems,” IEEE Transactions on Systems, Man and Cybernnetics, Vol. 34, No. 2, 2004, pp. 1248–1260. doi:10.1109/TSMCB.2003.822281

[19] S. F. Su, T. Tao and T. H. Hung, “Credit Assigned CMAC and Its Application to Online Learning Robust Controllers,” IEEE Transactions on Systems, Man and Cybernnetics, Vol. 33, No. 2, 2003, pp. 202-213. doi:10.1109/TSMCB.2003.810447

[20] H.-C. Lu, C.-Y. Chuang and M.-F. Yeh, “Design of Hybrid Adaptive CMAC with Supervisory Controller for a Class of Nonlinear System,” Neurocomputing, Vol. 72, No. 7-9, 2009, pp. 1920-1933. doi:10.1016/j.neucom.2008.07.004

[21] Y. F. Peng and C. M. Lin, “Intelligent Hybrid Control for Uncertain Nonlinear Systems Using a Recurrent Cerebellar Model Articulation Controller,” IEEE Proceedings Control Theory and Applications, Vol. 151, No. 5, 2004. pp. 589-600. doi:10.1049/ip-cta:20040903

[22] J. Hu and F. Pratt, “Self-Organizing CMAC Neural Networks and Adaptive Dynamic Control,” IEEE International Symposium on Intelligent Control/Intelligent Systems and Semiotics, Cambridge, 1999, pp. 259-265.

[23] H. C. Lu and C. Y. Chuang, “Robust Parametric CMAC with Self-Generating Design for Uncertain Nonlinear Systems,” Neurocomputing, Vol. 74, No. 4, 2011, pp. 549-562. doi:10.1016/j.neucom.2010.09.001

[24] H. M. Lee, C. M. Chen and Y. F. Lu, “A Self-Organizing HCMAC Neural-Network Classifier,” IEEE Transactions on Neural Networks, Vol. 14, No. 1, 2003, pp. 15-27. doi:10.1109/TNN.2002.806607

[25] C. M. Lin and T. Y. Chen, “Self-Organizing CMAC Control for a Class of MIMO Uncertain Nonlinear Systems,” IEEE Transactions on Neural Networks, Vol. 20, No. 9, 2009, pp. 1377-1384. doi:10.1109/TNN.2009.2013852

[26] M.-F. Yeh, “Single-Input CMAC Control System,” Neurocomputing, Vol. 70, No. 16-18, 2007, pp. 2638-2644. doi:10.1016/j.neucom.2006.05.019

[27] M.-F. Yeh, H.-C. Lu and J.-C. Chang, “Single-Input CMAC Control System with Direct Control Ability,” IEEE Transactions on Systems, Man and Cybernnetics, Vol. 3, No. 1, 2006, pp. 2602-2607. doi:10.1109/ICSMC.2006.385256

[28] M.-F. Yeh and C.-H. Tsai, “Standalone CMAC Control Systems with Online Learning Ability,” IEEE Transactions on Systems, Man and Cybernnetics, Vol. 40, No. 1, 2010, pp. 43-53. doi:10.1109/TSMCB.2009.2030334

[1] A. Vemuri, M. M. Polycarpou and S. A. Diakourtis, “Neural Network Based Fault Detection in Robotic Manipulators,” IEEE Robotics Automation, Vol. 14, No. 2, 1998, pp. 342-348. doi:10.1109/70.681254

[2] W. Z. Gao and R. R. Selmic, “Neural Network Control of a Class of Nonlinear Systems with Actuator Saturation,” American Control Conference, Boston, 2006, pp. 147-156.

[3] Y. Zou, Y. N. Wang and X. Z. Liu, “Neural Network Robust H∞Tracking Control Strategy for robot manipulators,” Applied Mathematical Modelling, Vol. 34, No. 7, 2010, pp. 1823-1838. doi:10.1016/j.apm.2009.09.026

[4] B.-S. Chen, H.-J. Uang and C.-S. Tseng, “Robust Tracking Enhancement of Robot Systems Including Motor Dynamics: A Fuzzy-Based Dynamic Game Approach,” IEEE Transactions on Fuzzy Systems, Vol. 6, No. 4, 1998, pp. 538-552. doi:10.1109/91.728449

[5] H.-X. Li and S.-C. Tong, “A Hybrid Adaptive Fuzzy Control for a Class of Nonlinear MIMO Systems,” IEEE Transactions on Fuzzy Sysemstm, Vol. 11, No. 1, 2003, pp. 24-34. doi:10.1109/TFUZZ.2002.806314

[6] S. Labiod, M. S. Boucherit and T. M. Guerra, “Adaptive Fuzzy Control of a Class of MIMO Nonlinear Systems,” Fuzzy Set and Systems, Vol. 151, No. 1, 2005, pp. 59-77. doi:10.1016/j.fss.2004.10.009

[7] Y. G. Leu, W. Y. Wang, and T. T. Lee, “Observe Based Direct Adaptive Fuzzy Neural Control for Non-Affine Nonlinear Systems,” IEEE Transactions on Neural Networks, Vol. 16, No. 4, 2005, pp. 853-861. doi:10.1109/TNN.2005.849824

[8] R. J. Wai and Z. W. Yang, “Adaptive Fuzzy Neural Network Control Design via a T-S Fuzzy Model for a Robot Manipulator Including Actuator Dynamics,” IEEE Transactions on Systems, Man and Cybernnetics, Vol. 38, No. 5, 2008, pp. 1326-1346. doi:10.1109/TSMCB.2008.925749

[9] C.-S. Chen, “Dynamic Structure Neural Fuzzy Networks for Robust Adaptive Control of Robot Manipulators,” IEEE Transactions on Industrial Electronics, Vol. 55, No. 9, 2008, pp. 3402-3414. doi:10.1109/TIE.2008.926778

[10] B. J. Choi, S. W. Kwak and B. K. Kim, “Design of Single-Input Fuzzy Logic Controller and Its Properties,” Fuzzy Sets and Systems, Vol. 106, No. 3, 1999, pp. 299-308. doi:10.1016/S0165-0114(97)00283-2

[11] B. J. Choi, S. W. Kwak and B. K. Kim, “Design and Stability Analysis of Single-Input Fuzzy Logic Controller,” IEEE Transactions on Systems, Man and Cybernnetics, Vol. 30, No. 2, 2000, pp. 303-309. doi:10.1109/3477.836378

[12] K. Ishaque, S. S. Abdullah, S. M. Ayob and Z. Salam, “Single Input Fuzzy Logic Controller for Unmanned Underwater Vehicle,” Journal of Intelligent and Robotic Systems, Vol. 59, No. 3, 2010, pp. 87-100. doi:10.1007/s10846-010-9395-x

[13] J. S. Albus, “A New Approach to Manipulator Control: The Cerebellar Model Articulation Controller,” Journal of Dynamic Systems Measurement and Control, Vol. 97, No. 3, 1975, pp. 220-227. doi:10.1115/1.3426922

[14] H. Shiraishi, S. L. Ipri and D. D. Cho, “CMAC Neural Network Controller for Fuel-Injection Systems,” IEEE Transactions on Control Systems Technology, Vol. 3, No. 1, 1995, pp. 32-38. doi:10.1115/1.3426922

[15] S. Jagannathan, S. Commuri and F. L. Lewis, “Feedback Linearization Using CMAC Neural Networks,” Automatica, Vol. 34, No. 3, 1998, pp. 547-557. doi:10.1016/S0005-1098(97)00206-9

[16] C. T. Chiang and C. S. Lin, “CMAC with General Basis Functions,” Journal of Neural Networks, Vol. 9, No. 7, 1996, pp. 1199-1211. doi:10.1016/S0005-1098(97)00206-9

[17] Y. H. Kim and F. L. Lewis, “Optimal Design of CMAC Neural-Network Controller for Robot Manipulators,” IEEE Transactions on Systems, Man and Cybernnetics, Vol. 30, No. 1, 2000, pp. 22-31. doi:10.1109/5326.827451

[18] C. M. Lin and Y. F. Peng, “Adaptive CMAC-Based Supervisory Control for Uncertain Nonlinear Systems,” IEEE Transactions on Systems, Man and Cybernnetics, Vol. 34, No. 2, 2004, pp. 1248–1260. doi:10.1109/TSMCB.2003.822281

[19] S. F. Su, T. Tao and T. H. Hung, “Credit Assigned CMAC and Its Application to Online Learning Robust Controllers,” IEEE Transactions on Systems, Man and Cybernnetics, Vol. 33, No. 2, 2003, pp. 202-213. doi:10.1109/TSMCB.2003.810447

[20] H.-C. Lu, C.-Y. Chuang and M.-F. Yeh, “Design of Hybrid Adaptive CMAC with Supervisory Controller for a Class of Nonlinear System,” Neurocomputing, Vol. 72, No. 7-9, 2009, pp. 1920-1933. doi:10.1016/j.neucom.2008.07.004

[21] Y. F. Peng and C. M. Lin, “Intelligent Hybrid Control for Uncertain Nonlinear Systems Using a Recurrent Cerebellar Model Articulation Controller,” IEEE Proceedings Control Theory and Applications, Vol. 151, No. 5, 2004. pp. 589-600. doi:10.1049/ip-cta:20040903

[22] J. Hu and F. Pratt, “Self-Organizing CMAC Neural Networks and Adaptive Dynamic Control,” IEEE International Symposium on Intelligent Control/Intelligent Systems and Semiotics, Cambridge, 1999, pp. 259-265.

[23] H. C. Lu and C. Y. Chuang, “Robust Parametric CMAC with Self-Generating Design for Uncertain Nonlinear Systems,” Neurocomputing, Vol. 74, No. 4, 2011, pp. 549-562. doi:10.1016/j.neucom.2010.09.001

[24] H. M. Lee, C. M. Chen and Y. F. Lu, “A Self-Organizing HCMAC Neural-Network Classifier,” IEEE Transactions on Neural Networks, Vol. 14, No. 1, 2003, pp. 15-27. doi:10.1109/TNN.2002.806607

[25] C. M. Lin and T. Y. Chen, “Self-Organizing CMAC Control for a Class of MIMO Uncertain Nonlinear Systems,” IEEE Transactions on Neural Networks, Vol. 20, No. 9, 2009, pp. 1377-1384. doi:10.1109/TNN.2009.2013852

[26] M.-F. Yeh, “Single-Input CMAC Control System,” Neurocomputing, Vol. 70, No. 16-18, 2007, pp. 2638-2644. doi:10.1016/j.neucom.2006.05.019

[27] M.-F. Yeh, H.-C. Lu and J.-C. Chang, “Single-Input CMAC Control System with Direct Control Ability,” IEEE Transactions on Systems, Man and Cybernnetics, Vol. 3, No. 1, 2006, pp. 2602-2607. doi:10.1109/ICSMC.2006.385256

[28] M.-F. Yeh and C.-H. Tsai, “Standalone CMAC Control Systems with Online Learning Ability,” IEEE Transactions on Systems, Man and Cybernnetics, Vol. 40, No. 1, 2010, pp. 43-53. doi:10.1109/TSMCB.2009.2030334