[1] 赵大勇, 柴天佑. 再磨过程泵池液位区间与给矿压力模糊切换控制. 自动化学报, 2013, 39(5): 556−564

Zhao Da-Yong, Chai Tian-You. Fuzzy switching control for sump level interval and hydrocyclone pressure in regrinding process. Acta Automatica Sinica, 2013, 39(5): 556−564
[2] 贾瑶, 张立岩, 柴天佑. 矿浆中和过程中基于模型预估模糊自适应控制. 东北大学学报, 2014, 35(5): 617−621 doi: 10.3969/j.issn.1005-3026.2014.05.003

Jia Yao, Zhang Li-Yan, Chai Tian-You. Based on fuzzy adaptive control of model predictive in slurry neutralization process. Journal of Northeastern University Natural Science, 2014, 35(5): 617−621 doi: 10.3969/j.issn.1005-3026.2014.05.003
[3] Zhang Y J, Jia Y, Chai T Y, Wang D H, Dai W, Fu J. Data-driven PID controller and its application to pulp neutralization process. IEEE Transactions on Control Systems Technology, 2018, 26(3): 828−841 doi: 10.1109/TCST.2017.2695981
[4] Xia D Y, Chai T Y, Wang L Y. Fuzzy neural-network friction compensation-based singularity avoidance energy swing-up to nonequilibrium unstable position control of Pendubot. IEEE Transactions on Control Systems Technology, 2014, 22(2): 690−705 doi: 10.1109/TCST.2013.2255290
[5] 魏萃, 柴天佑, 贾瑶, 王良勇. 补偿信号法驱动的Pendubot自适应平衡控制. 自动化学报, 2019, 45(6): 1146−1156

Wei Cui, Chai Tian-You, Jia Yao, Wang Liang-Yong. Compensation signal driven adaptive balance control of the Pendubot. Acta Automatica Sinica, 2019, 45(6): 1146−1156
[6] Chen L, Narendra K S. Nonlinear adaptive control using neural networks and multiple models. Automatica, 2001, 37(8): 1245−1255 doi: 10.1016/S0005-1098(01)00072-3
[7] Fu Y, Chai T Y. Nonlinear multivariable adaptive control using multiple models and neural networks. Automatica, 2007, 43(8): 1101−1110
[8] 柴天佑, 张亚军. 基于未建模动态补偿的非线性自适应切换控制方法. 自动化学报, 2010, 37(7): 773−786

Chai Tian-You, Zhang Ya-Jun. Nonlinear adaptive switching control method based on un-modeled dynamics compensation. Acta Automatica Sinica, 2010, 37(7): 773−786
[9] Wang Y G, Chai T Y, Fu J, Zhang Y J, Fu Y. Adaptive decoupling switching control based on generalized predictive control. IET Control Theory and Application, 2012, 12(6): 1−12
[10] Wang Y G, Chai T Y, Fu J, Sun J, Wang H. Adaptive decoupling switching control of the forced-circulation evaporation system using neural networks. IEEE Transactions on Control Systems Technology, 2013, 21(3): 964−974 doi: 10.1109/TCST.2012.2193883
[11] Hou Z S, Jin S T. Data-driven model-free adaptive control for a class of MIMO nonlinear discrete-time systems. IEEE Transactions on Neural Networks, 2011, 22(12): 2173−2188 doi: 10.1109/TNN.2011.2176141
[12] Zhu Y M, Hou Z S. Data-driven MFAC for a class of discrete-time nonlinear systems with RBFNN. IEEE Transactions on Neural Networks and Learning Systems, 2014, 25(5): 1013−1020
[13] Dai W, Chai T Y, Yang S X. Data-driven optimization control for safety operation of hematite grinding process. IEEE Transactions on Industrial Electronics, 2015, 62(5): 2930−2941 doi: 10.1109/TIE.2014.2362093
[14] Chi R H, Liu Y, Hou Z S, Jin S T. Data-driven terminal iterative learning control with high-order learning law for a class of non-linear discrete-time multiple-input–multiple output systems. IET Control Theory and Applications, 2015, 9(7): 1075−1082
[15] Chai T Y, Zhang Y J, Wang H, Su C Y, Sun J. Data-based virtual un-modeled dynamics driven multivariable nonlinear adaptive switching control. IEEE Transactions on Neural Networks, 2011, 22(12): 2154−2171 doi: 10.1109/TNN.2011.2167685
[16] Spong M W, Block D J. The Pendubot: A mechatronic system for control research and education. In: Proceedings of the 34th IEEE Conference on Decision and Control.New Orleans, LA, USA: IEEE, 1995. 555−556
[17] Zhang M J, Tzyh-Jong T. Hybrid control of the Pendubot. IEEE/ASME Transactions on Mechatronics, 2002, 7(1): 79−86 doi: 10.1109/3516.990890
[18] Xin X, Liu Y N. Reduced-order stable controllers for two- link underactuated planar robots. Automatica, 2013, 49(7): 2176−2183 doi: 10.1016/j.automatica.2013.03.027
[19] Sanchez E N, Flores V. Real-time fuzzy PI+PD control for an underactuated robot. In: Proceedings of the 2002 IEEE Internatinal Symposium on Intelligent Control. Vancouver, BC, Canada: IEEE, 2002. 137−141
[20] 侯俊, 王良勇, 柴天佑, 方正. 基于T-S模糊的欠驱动机械臂的平衡控制. 控制工程, 2012, 19(1): 5−8, 85 doi: 10.3969/j.issn.1671-7848.2012.01.002

Hou Jun, Wang Liang-Yong, Chai Tian-You, Fang Zheng. Balance control of underactuated manipulator using T-S fuzzy scheme. Control Engineering of China, 2012, 19(1): 5−8, 85 doi: 10.3969/j.issn.1671-7848.2012.01.002
[21] Wang W, Yi J Q, Zhao D B, Liu X J. Adaptive sliding mode controller for an underactuated manipulator. In: Proceedings of the 2004 International Conference on Machine Learning and Cybernetics. Shanghai, China: IEEE, 2004. 882−887
[22] Spall J C, Cristion J A. Model-free control of nonlinear stochastic systems with discrete-time measurements. IEEE Transactions on Automatic Control, 1998, 43(9): 1198−1210 doi: 10.1109/9.718605
[23] Hjalmarsson H, Gevers M, Gunnarsson S, Lequin O. Iterative feedback tuning: Theory and applications. IEEE Control Systems Magazine, 1998, 18(4): 26−41 doi: 10.1109/37.710876
[24] Agnoloni T, Mosca E. Controller falsification based on multiple models. International Journal of Adaptive Control and Signal Processing, 2003, 17(2): 163−177 doi: 10.1002/acs.745
[25] Safonov M G, Tsao T C. The unfalsified control concept and learning. IEEE Transactions on Automatic Control, 1997, 42(6): 843−847 doi: 10.1109/9.587340
[26] Campi M C, Lecchini A, Savaresi S M. Virtual reference feedback tuning: A direct method for the design of feedback controllers. Automatica, 2002, 38(8): 1337−1346 doi: 10.1016/S0005-1098(02)00032-8
[27] Markovsky I, Rapisarda P. Data-driven simulation and control. International Journal of Control, 2008, 81(12): 1946−1959 doi: 10.1080/00207170801942170
[28] Jang J S R. ANFIS: Adaptive-network-based fuzzy inference system. IEEE Transactions on System, Man, Cybernetics, 1993, 23(3): 665−685 doi: 10.1109/21.256541
[29] Zhang Y J, Chai T Y, Wang D H. An alternating identification algorithm for a class of nonlinear dynamical systems. IEEE Transactions on Neural Networks and Learning Systems, 2017, 28(7): 1606−1617 doi: 10.1109/TNNLS.2016.2547968
[30] Eom M, Chwa D. Robust swing-up and balancing control using a nonlinear disturbance observer for the Pendubot system with dynamic friction. IEEE Transactions on Robotics, 2015, 31(2): 331−343 doi: 10.1109/TRO.2015.2402512
[31] Sun N, Fang Y C, Chen H, Lu B, Fu Y M. Slew/Translation positioning and swing suppression for 4-DOF tower cranes with parametric uncertainties: Design and hardware experimentation. IEEE Transactions on Industrial Electronics, 2016, 63(10): 6407−6418
[32] 王永富, 柴天佑. 一种补偿动态摩擦的自适应模糊控制方法. 中国电机工程学报, 2005, 25(2): 139−143

Wang Yong-Fu, Chai Tian-You. Adaptive fuzzy control method for dynamic friction compensation. Proceedings of the CSEE, 2005, 25(2): 139−143