A Novel Adjustable Parameters PID Control of Dual-motor Driving Servo System

References

• W. Chen, Y. F. Wu, R. H. Du, and X. B. Wu, “Fault diagnosis and fault tolerant control for the servo system driven by two motors synchronously,” Control Theory Appl., Vol. 31, pp. 27–34, Jan. 2014.
   Google Scholar
• L. P. Zhang, L. Li, B. N. Qi, and J. Song, “High speed stability electromechanical coupling control for dual-motor distributed drive electric vehicle,” Journal of Mechanical Engineering, Vol. 51, pp. 29–40, Aug. 2015. doi: 10.3901/JME.2015.16.029
   Google Scholar
• H. P. Ren, and B. He, “Anti-backlash control of machine tool feed system driven by dual-motors,” Electr. Mach. Control, Vol. 18, pp. 60–6, Mar. 2014.
   Google Scholar
• J. T. Gai, S. D. Huang, G. M. Zhou, Y. Liu, and T. Ma, “Adaptive sliding mode steering control of double motor coupling drive transmission for tracked vehicle,” ACTA ARMAMENTARII, Vol. 36, pp. 405–11, Mar. 2015.
   Google Scholar
• D. X. Sun, F. C. Lan, X. F. He, and J. Q. Chen, “Study on adaptive acceleration slip regulation for dual-motor four-wheel drive electric vehicle,” Automot. Eng., Vol. 38, pp. 600–8, May. 2016.
   Google Scholar
• J. R. Wu, Y. Guo, F. Q. Huang, and Y. F. Wu, “Adaptive control of dual-motor driving servo system based on characteristic model,” Journal of Huazhong University of Science and Technology (Natural Science Edition, Vol. 41, pp. 436–9, Jan. 2013.
   Google Scholar
• Y. C. Wei, C. L. Xia, T. Liu, Q. Geng, and T. N. Shi, “Finite control set model predictive control for dual-motor torque synchronous system,” Trans. China Electrotech. Soc., Vol. 31, pp. 115–22, Oct. 2016.
   Google Scholar
• S. K. Tseng, C. C. Tseng, T. H. Liu, and J. L. Chen, “Wide-range adjustable speed control method for dual-motor drive systems,” IET Electr. Power Appl., Vol. 9, pp. 107–16, Jan. 2015. doi: 10.1049/iet-epa.2013.0291
   Web of Science ®Google Scholar
• P. D. U. Coronado, and H. Ahuett-Garza, “Control strategy for power distribution in dual motor propulsion system for electric vehicles,” Math. Probl. Eng., Vol. 2015, pp. 1–10, Nov. 2015.
   Web of Science ®Google Scholar
• L. R. Ramelan, E. Firmansyah, T. H. Liu, and S. K. Tseng, “An improved maximum efficiency control for dual-motor drive systems,” in 6th International Conference on Information Technology and electrical Engineering, 2014, pp. 1–6.
   Google Scholar
• W. Chen, Y. F. Wu, R. H. Du, and X. B. Wu, “Robust dynamic surface control for the servo system driven by two motors synchronously,” Inf. Control, Vol. 42, pp. 625–31, Oct. 2013.
   Google Scholar
• G. F. Sun, “Dynamic surface control for nonlinear systems and the application to servo systems,” Ph.D. dissertation, School of Automation, Beijing Institute of Technology 2015.
   Google Scholar
• D. W. Li, G. F. Sun, X. M. Ren, and X. H. Lv, “Finite-time adaptive dynamic surface control of dual motor driving systems,” Proceedings of 2013 Chinese Intelligent Automation Conference, Vol. 255, pp. 165–74, Jan. 2013. doi: 10.1007/978-3-642-38460-8_19
   Google Scholar
• M. L. Wang, and X. M. Ren, “Adaptive dynamic surface control for dual-motor driving system withperformance,” Proceedings of 2016 Chinese Intelligent Systems Conference, Vol. 404, pp. 335–44, Jan. 2016. doi: 10.1007/978-981-10-2338-5_33
   Google Scholar
• H. X. Wu, and S. P. Shen, “Basis of theory and applications on PID control,” Control Engineering of China, Vol. 10, pp. 37–42, Jan. 2003.
   Google Scholar
• H. X. Wu, “Research and prospect on the control theory and method in the engineering,” Control Theory Appl., Vol. 31, pp. 1626–31, Dec. 2014.
   Google Scholar
• P. Derugo, and K. Szabat, “Adaptive neuro-fuzzy PID controller for nonlinear drive system,” COMPEL-The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, Vol. 34, pp. 792–807, 2015. doi: 10.1108/COMPEL-10-2014-0257
   Web of Science ®Google Scholar
• K. Nowopolski, B. Wicher, K. Zawirski, and M. Tulodziecki, “Control of electromechanical object with backlash and elasticity within interconnection between motor and load,” 2015 Selected Problems of Electrical Engineering and Electronics (Jan. 2016).
   Google Scholar
• Y.-L. Zhou, and D.-W. Cai, “Energy Saving control system of long Stroke Pumping unit based on RBF neural network,” Proceedings of the 2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics, Vol. 2, 358–61, Aug. 2012.
   Google Scholar
• Y. Z. Zhang, and J. H. Dong, “Modeling fuzzy RBF neural network to predict of mechanical properties of welding joints based on fuzzy C-means cluster,” Journal of Mechanical Engineering, Vol. 50, pp. 58–64, Jun. 2014. doi: 10.3901/JME.2014.12.058
   Google Scholar
• C. C. Cai, S. C. Cheng, Z. X. Deng, B. Jiang, W. G. He, and J. X. Ma, “DC microgrid equivalent modeling based on fuzzy-RBF artificial neural network,” Power Syst. Technol., Vol. 40, pp. 3446–52, Nov. 2016.
   Google Scholar
• Y. F. Yao, H. Cheng, C. X. Rong, M. J. Li, H. B. Cai, and J. Song, “Analysis and prediction of vertical shaft freezing pressure in deep alluvium based on RBF fuzzy neural network model,” Journal of Mining and Safety Engineering, Vol. 33, pp. 70–6, Jan. 2016.
   Google Scholar
• H. X. Zhu, J. Shen, and Z. G. Su, “RBF neural network regression model based on fuzzy observations,” Journal of Southeast University, Vol. 29, pp. 400–6, Jan. 2013.
   Google Scholar
• Y. F. Wang, Z. M. Li, Z. T. Yuan, and W. H. Wan, “Intelligent control of the grinding and classification system based on fuzzy RBF neural network,” Journal of Chongqing University, Vol. 33, pp. 124–8, Mar. 2010.
   Google Scholar
• H. B. Zhao, and C. G. Wang, “Fuzzy sliding mode adaptive control of dual-motor driving servo system,” in IEEE International Conference on Mechatronics, Robotics and Automation, May 2018., pp. 52–5.
   Google Scholar
• H. B. Zhao, “Backstepping adaptive control of dual-motor driving servo system with backlash nonlinearity,” Proceedings of the 2013 International Conference on Intelligent Control and Information Processing, 655–60, Jun. 2013.
   Google Scholar