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Qinghui Wu
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2020 – today
- 2022
- [j13]Xiao Xiao, Yifan Wu, Qinghui Wu, Hongliang Ren
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Concurrently bendable and rotatable continuum tubular robot for omnidirectional multi-core transurethral prostate biopsy. Medical Biol. Eng. Comput. 60(1): 229-238 (2022) - 2020
- [j12]Xinjun Wang, Qinghui Wu, Xinghui Yin:
Adaptive finite-time prescribed performance control of switched nonlinear systems with unknown actuator dead-zone. Int. J. Syst. Sci. 51(1): 133-145 (2020) - [j11]Yun Hol Chan
Pre-Clinical Proof-of-Concept Study of a Bladder Irrigation Feedback System for Gross Haematuria in a Lab Setup. Multimodal Technol. Interact. 4(3): 59 (2020)
2010 – 2019
- 2019
- [j10]Wenyun Gao, Xinjun Wang
Neural Networks-Based Adaptive Tracking Control for a Class of High-Order Stochastic Nonlinear Time-Delay Systems. IEEE Access 7: 63992-64004 (2019) - [j9]Xinjun Wang
Neural network based adaptive dynamic surface control of nonaffine nonlinear systems with time delay and input hysteresis nonlinearities. Neurocomputing 333: 53-63 (2019) - 2018
- [j8]Hongjing Liang
Distributed-observer-based output synchronization for heterogeneous double-integral networks. Appl. Math. Comput. 337: 535-544 (2018) - [j7]Xinjun Wang
Disturbance observer based adaptive neural control of uncertain MIMO nonlinear systems with unmodeled dynamics. Neurocomputing 313: 247-258 (2018) - 2017
- [c6]Shuo Ding, Qinghui Wu, Xiaoheng Chang, Fang Zhang:
Prediction of Laboratory Equipment Demand Based on Grey Relation Analysis and Elman Neural Network. ISCID (1) 2017: 408-411 - 2016
- [j6]Lei Liu, Yunfei Yin, Jiahui Wang, Qinghui Wu:
Stability analysis of discrete-time switched nonlinear systems via T-S fuzzy model approach. Neurocomputing 173: 1967-1971 (2016) - [j5]Qinghui Wu, Xinjun Wang, Qinghuan Shen:
Research on dynamic modeling and simulation of axial-flow pumping system based on RBF neural network. Neurocomputing 186: 200-206 (2016) - [j4]Qinghui Wu, Qinghuan Shen, Xinjun Wang, Youlin Yang:
Estimation of centrifugal pump operational state with dual neural network architecture based model. Neurocomputing 216: 102-108 (2016) - 2012
- [j3]Qinghui Wu:
Sliding-mode control of induction motor based on inverse decoupling. Int. J. Autom. Control. 6(2): 193-206 (2012) - 2011
- [j2]Shuo Ding, Qinghui Wu:
Research on inverse model based on ANN and analytic method for induction motor. Int. J. Autom. Control. 5(4): 356-370 (2011) - [c5]Qinghui Wu, Shuo Ding, Youlin Yang, Lin Li, Zongze Cui:
Research on Modeling for YiLiuShi NeutraLization Reaction Process. ICDMA 2011: 984-987 - 2010
- [j1]Qinghui Wu:
Neural network inverse decoupling control of stator flux and torque for induction motor drives. Int. J. Autom. Control. 4(2): 147-157 (2010)
2000 – 2009
- 2009
- [c4]Qinghui Wu, Shuxian Lun
Research on Neural Network Based Inverse Model of Induction Motor Drives. BMEI 2009: 1-5 - 2006
- [c3]Qinghui Wu, Cheng Shao:
Novel hybrid sliding-mode controller for direct torque control induction motor drives. ACC 2006: 1-5 - 2004
- [c2]Qinghui Wu, Yi Liu, Dianjun Zhang, Yonghui Zhang:
Adaptive Control for Induction Servo Motor Based on Wavelet Neural Networks. ISNN (2) 2004: 156-162 - [c1]Yonghui Zhang, Cheng Shao, Qinghui Wu:
RBF Neural Networks-Based Software Sensor for Aluminum Powder Granularity Distribution Measurement. ISNN (2) 2004: 860-865
Coauthor Index
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