Dr Shuai Li

Associate Professor in Robotics and Autonomous Systems, Mechanical Engineering

+44 (0) 1792

shuai.li@swansea.ac.uk

Research Links

https://orcid.org/0000-0001-8316-5289

Google Scholar

Available For Postgraduate Supervision

About

Steven is presently an associate professor within the Faculty of Science and Engineering. His main research interests include AI, machine learning, control algorithms, robotics, nonlinear optimization, and control. He has published over 200 SCI indexed journal papers (including more than 90 on IEEE transactions) on peer reviewed journals. Steven is available for supervising both master and PhD students. PhD graduates from his group are now working in leading universities in Hong Kong, India, China as professors. In case you have interests for taking your further study under the supervision by Steven, please feel free to contact him at shuai.li@swansea.ac.uk

Areas Of Expertise

Robotics
Neural Networks
Nonlinear Optimization and Control
Advanced Algorithms
Manufacturing Automation
High-speed High-Precision Control

Career Highlights

Teaching Interests

EG-M111 Automation & Robotics
EGA366-Kinematics and Programming of Robots
EG150-Signals and Systems
EG353-final year projects

Research

Publications

Research Highlights

Guo, D., Li, S., & Stanimirovic, P. (2020). Analysis and Application of Modified ZNN Design With Robustness Against Harmonic Noise. IEEE Transactions on Industrial Informatics, 16(7), 4627-4638.
https://doi.org/10.1109/tii.2019.2944517, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52457
Chen, D., Li, S., Wu, Q., & Luo, X. (2019). Super-twisting ZNN for coordinated motion control of multiple robot manipulators with external disturbances suppression. Neurocomputing
https://doi.org/10.1016/j.neucom.2019.08.085, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52014
Chen, D., Li, S., Li, W., & Wu, Q. (2019). A Multi-Level Simultaneous Minimization Scheme Applied to Jerk-Bounded Redundant Robot Manipulators. IEEE Transactions on Automation Science and Engineering, 1-12.
https://doi.org/10.1109/TASE.2019.2931810, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa51998
Xu, Z., Zhou, X., & Li, S. (2019). Deep Recurrent Neural Networks Based Obstacle Avoidance Control for Redundant Manipulators. Frontiers in Neurorobotics, 13
https://doi.org/10.3389/fnbot.2019.00047, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52000
Chen, D., Li, S., & Wu, Q. (2019). A Novel Disturbance Rejection Zeroing Neurodynamic Approach for Robust Synchronization of Chaotic Systems. IEEE Access, 7, 121184-121198.
https://doi.org/10.1109/ACCESS.2019.2938016, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52006
Mao, C., Li, S., Chen, Z., Zu, H., Wang, Z., & Wang, Y. (2019). A Novel Algorithm for Robust Calibration of Kinematic Manipulators and its Experimental Validation. IEEE Access, 7, 90487-90496.
https://doi.org/10.1109/access.2019.2926801, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52004
Chen, D., Li, S., Lin, F., & Wu, Q. (2020). New Super-Twisting Zeroing Neural-Dynamics Model for Tracking Control of Parallel Robots: A Finite-Time and Robust Solution. IEEE Transactions on Cybernetics, 1-10.
https://doi.org/10.1109/TCYB.2019.2930662, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52001
Khan, A., Li, S., & Luo, X. (2020). Obstacle Avoidance and Tracking Control of Redundant Robotic Manipulator: An RNN-Based Metaheuristic Approach. IEEE Transactions on Industrial Informatics, 16(7), 4670-4680.
https://doi.org/10.1109/tii.2019.2941916, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa51997
http://dx.doi.org/10.1109/tii.2019.2941916
Zhou, X., Xu, Z., & Li, S. (2019). Collision-Free Compliance Control for Redundant Manipulators: An Optimization Case. Frontiers in Neurorobotics, 13
https://doi.org/10.3389/fnbot.2019.00050, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52009
Chen, D., Li, S., & Liao, L. (2019). A recurrent neural network applied to optimal motion control of mobile robots with physical constraints. Applied Soft Computing, 85, 105880
https://doi.org/10.1016/j.asoc.2019.105880, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52559
Chen, D., Li, S., Wu, Q., & Liao, L. (2020). Simultaneous identification, tracking control and disturbance rejection of uncertain nonlinear dynamics systems: A unified neural approach. Neurocomputing, 381, 282-297.
https://doi.org/10.1016/j.neucom.2019.11.031, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52966
Li, Z., Li, C., Li, S., & Cao, X. (2020). A Fault-Tolerant Method for Motion Planning of Industrial Redundant Manipulator. IEEE Transactions on Industrial Informatics, 16(12), 7469-7478.
https://doi.org/10.1109/tii.2019.2957186, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52973
Zhang, Y., Ling, Y., Li, S., Yang, M., & Tan, N. (2020). Discrete-time zeroing neural network for solving time-varying Sylvester-transpose matrix inequation via exp-aided conversion. Neurocomputing, 386, 126-135.
https://doi.org/10.1016/j.neucom.2019.12.053, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53117
http://dx.doi.org/10.1016/j.neucom.2019.12.053
Mao, C., Li, S., Chen, Z., Zhang, X., & Li, C. (2020). Robust kinematic calibration for improving collaboration accuracy of dual-arm manipulators with experimental validation. Measurement, 155, 107524
https://doi.org/10.1016/j.measurement.2020.107524, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53485
Zhang, Y., Li, S., Xu, B., & Yang, Y. (2020). Analysis and design of a distributed k-winners-take-all model. Automatica, 115, 108868
https://doi.org/10.1016/j.automatica.2020.108868, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53516
Shi, Y., Jin, L., Li, S., & Qiang, J. (n.d.) Proposing, developing and verification of a novel discrete-time zeroing neural network for solving future augmented Sylvester matrix equation. Journal of the Franklin Institute
https://doi.org/10.1016/j.jfranklin.2020.02.024, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53642
Xu, Z., Li, S., Zhou, X., Zhou, S., & Cheng, T. (2020). Dynamic Neural Networks for Motion-Force Control of Redundant Manipulators: An Optimization Perspective. IEEE Transactions on Industrial Electronics, 68(2), 1-1.
https://doi.org/10.1109/tie.2020.2970635, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53696
Gong, W., Chen, D., & Li, S. (2020). Active Sensing of Robot Arms Based on Zeroing Neural Networks: A Biological-Heuristic Optimization Model. IEEE Access, 8, 25976-25989.
https://doi.org/10.1109/access.2020.2971020, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53713
Jiang, X., Lin, Z., He, T., Ma, X., Ma, S., & Li, S. (2020). Optimal Path Finding With Beetle Antennae Search Algorithm by Using Ant Colony Optimization Initialization and Different Searching Strategies. IEEE Access, 8, 15459-15471.
https://doi.org/10.1109/access.2020.2965579, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53741
Li, X., Xu, Z., Li, S., Wu, H., & Zhou, X. (2020). Cooperative Kinematic Control for Multiple Redundant Manipulators Under Partially Known Information Using Recurrent Neural Network. IEEE Access, 8, 40029-40038.
https://doi.org/10.1109/access.2020.2974248, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53865
Khan, A., Shao, Z., Li, S., Wang, Q., & Guan, N. (2020). Which is the best PID variant for pneumatic soft robots an experimental study. IEEE/CAA Journal of Automatica Sinica, 7(2), 451-460.
https://doi.org/10.1109/jas.2020.1003045, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53870
Khan, A., Cao, X., Li, S., Katsikis, V., & Liao, L. (2020). BAS-ADAM: an ADAM based approach to improve the performance of beetle antennae search optimizer. IEEE/CAA Journal of Automatica Sinica, 7(2), 461-471.
https://doi.org/10.1109/jas.2020.1003048, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53871
Khan, A., Li, S., Chen, D., & Liao, L. (n.d.) Tracking control of redundant mobile manipulator: An RNN based metaheuristic approach. Neurocomputing
https://doi.org/10.1016/j.neucom.2020.02.109, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53900
Zhang, Y., Huang, H., Li, S., Li, J., & He, L. (n.d.) Event-triggered zeroing dynamics for motion control of Stewart platform. Journal of the Franklin Institute
https://doi.org/10.1016/j.jfranklin.2020.02.060, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53923
Liang, J., Xu, Z., Zhou, X., Li, S., & Ye, G. (2020). Recurrent Neural Networks-Based Collision-Free Motion Planning for Dual Manipulators Under Multiple Constraints. IEEE Access, 8, 54225-54236.
https://doi.org/10.1109/access.2020.2981688, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53940
Khan, A., Cao, X., Katsikis, V., Stanimirovic, P., Brajevic, I., Li, S., Kadry, S., & Nam, Y. (2020). Optimal Portfolio Management for Engineering Problems Using Nonconvex Cardinality Constraint: A Computing Perspective. IEEE Access, 8, 57437-57450.
https://doi.org/10.1109/access.2020.2982195, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53954
Khan, A. & Li, S. (2020). Sliding Mode Control With PID Sliding Surface for Active Vibration Damping of Pneumatically Actuated Soft Robots. IEEE Access, 8, 88793-88800.
https://doi.org/10.1109/access.2020.2992997, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa54131
Yan, W., Xu, Z., Zhou, X., Su, Q., Li, S., & Wu, H. (2020). Fast Object Pose Estimation Using Adaptive Threshold for Bin-Picking. IEEE Access, 8, 63055-63064.
https://doi.org/10.1109/access.2020.2983173, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa54162
Li, Z., Zuo, W., & Li, S. (2020). Zeroing dynamics method for motion control of industrial upper-limb exoskeleton system with minimal potential energy modulation. Measurement, 163, 107964
https://doi.org/10.1016/j.measurement.2020.107964, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa54389
Yue, Z., Li, G., Jiang, X., Li, S., Cheng, J., & Ren, P. (2020). A Hardware Descriptive Approach to Beetle Antennae Search. IEEE Access, 8, 89059-89070.
https://doi.org/10.1109/access.2020.2993600, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa54434
Cheng, Z., Pei, H., & Li, S. (2020). Neural-Networks Control for Hover to High-Speed-Level-Flight Transition of Ducted Fan UAV With Provable Stability. IEEE Access, 8, 100135-100151.
https://doi.org/10.1109/access.2020.2997877, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa54501
Katsikis, V., Mourtas, S., Stanimirović, P., Li, S., & Cao, X. (2020). Time-varying minimum-cost portfolio insurance under transaction costs problem via Beetle Antennae Search Algorithm (BAS). Applied Mathematics and Computation, 385, 125453
https://doi.org/10.1016/j.amc.2020.125453, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa54545
Zhang, Y. & Li, S. (2020). Machine Behavior Design And Analysis: A consensus perspective Springer, Singapore.
https://doi.org/10.1007/978-981-15-3231-3, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa54887
Brajević, I., Stanimirović, P., Li, S., & Cao, X. (2020). A Hybrid Firefly and Multi-Strategy Artificial Bee Colony Algorithm. International Journal of Computational Intelligence Systems, 13(1), 810-821.
https://doi.org/10.2991/ijcis.d.200612.001, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa54989
Zhang, H., Li, Z., Jiang, X., Ma, X., Chen, J., Li, S., Luan, Y., Lv, Z., & Ma, S. (2020). Beetle Colony Optimization Algorithm and its Application. IEEE Access, 8, 128416-128425.
https://doi.org/10.1109/access.2020.3008692, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa54990
Cheng, Y., Li, C., Li, S., & Li, Z. (2020). Motion Planning of Redundant Manipulator With Variable Joint Velocity Limit Based on Beetle Antennae Search Algorithm. IEEE Access, 8, 138788-138799.
https://doi.org/10.1109/access.2020.3012564, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55086
http://dx.doi.org/10.1109/access.2020.3012564
Zhou, X., Xu, Z., Li, S., Wu, H., Cheng, T., & Lv, X. (2020). AI based Robot Safe Learning and Control Springer Singapore.
https://doi.org/10.1007/978-981-15-5503-9, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55087
http://dx.doi.org/10.1007/978-981-15-5503-9
Khan, A., Li, S., & Zhou, X. (2021). Dynamic manipulation of pneumatically controlled soft finger for home automation. Measurement, 170, 108680
https://doi.org/10.1016/j.measurement.2020.108680, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55602
Kadry, S., Zhang, Y., & Li, S. (2020). Advanced microprocessor optimization methods for the Internet of Things. Transactions on Emerging Telecommunications Technologies, 31(12)
https://doi.org/10.1002/ett.4187, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55844
Li, Z., Li, S., & Luo, X. (2021). An overview of calibration technology of industrial robots. IEEE/CAA Journal of Automatica Sinica, 8(1), 23-36.
https://doi.org/10.1109/jas.2020.1003381, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55880
Mao, C., Chen, Z., Li, S., & Zhang, X. (2020). Separable Nonlinear Least Squares Algorithm for Robust Kinematic Calibration of Serial Robots. Journal of Intelligent & Robotic Systems, 101(1)
https://doi.org/10.1007/s10846-020-01268-z, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55908
Li, Z. & Li, S. (2021). A Sparse Optimization-Based Control Method for Manipulator With Simultaneous Potential Energy Minimization. IEEE Transactions on Circuits and Systems II: Express Briefs, 68(6), 2062-2066.
https://doi.org/10.1109/tcsii.2020.3045427, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56011
Zhang, Y., Li, S., & Weng, J. (2022). Learning and Near-Optimal Control of Underactuated Surface Vessels With Periodic Disturbances. IEEE Transactions on Cybernetics, 52(8), 7453-7463.
https://doi.org/10.1109/tcyb.2020.3041368, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56084
Li, Z. & Li, S. (2021). Saturated PI Control for Nonlinear System With Provable Convergence: An Optimization Perspective. IEEE Transactions on Circuits and Systems II: Express Briefs, 68(2), 742-746.
https://doi.org/10.1109/tcsii.2020.3007879, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56220
Khan, A., Li, S., & Cao, X. (2021). Tracking control of redundant manipulator under active remote center-of-motion constraints: an RNN-based metaheuristic approach. Science China Information Sciences, 64(3)
https://doi.org/10.1007/s11432-019-2735-6, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56354
Li, X., Li, S., Xu, Z., & Zhou, X. (2021). A Vary-Parameter Convergence-Accelerated Recurrent Neural Network for Online Solving Dynamic Matrix Pseudoinverse and its Robot Application. Neural Processing Letters, 53(2), 1287-1304.
https://doi.org/10.1007/s11063-021-10440-x, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56362
Khan, A., Li, S., & Zhou, X. (2021). Trajectory Optimization of 5-Link Biped Robot Using Beetle Antennae Search. IEEE Transactions on Circuits and Systems II: Express Briefs, 68(10), 3276-3280.
https://doi.org/10.1109/tcsii.2021.3062639, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56468
Zhang, Y., Li, S., & Liao, L. (2021). Input Delay Estimation for Input-Affine Dynamical Systems Based on Taylor Expansion. IEEE Transactions on Circuits and Systems II: Express Briefs, 68(4), 1298-1302.
https://doi.org/10.1109/tcsii.2020.3025136, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56698
Liao, B., Ma, C., Liao, M., Li, S., & Huang, Z. (2020). Toward deep neural networks: Mirror extreme learning machines for pattern classification. Filomat, 34(15), 4985-4996.
https://doi.org/10.2298/fil2015985l, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56705
Chen, D., Li, S., & Wu, Q. (2021). A Novel Supertwisting Zeroing Neural Network With Application to Mobile Robot Manipulators. IEEE Transactions on Neural Networks and Learning Systems, 32(4), 1776-1787.
https://doi.org/10.1109/tnnls.2020.2991088, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56719
Xu, Z., Zhou, X., Wu, H., Li, X., & Li, S. (2021). Motion Planning of Manipulators for Simultaneous Obstacle Avoidance and Target Tracking: An RNN Approach with Guaranteed Performance. IEEE Transactions on Industrial Electronics, 1-1.
https://doi.org/10.1109/tie.2021.3073305, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56810
Li, X., Xu, Z., Li, S., Su, Z., & Zhou, X. (2021). Simultaneous Obstacle Avoidance and Target Tracking of Multiple Wheeled Mobile Robots With Certified Safety. IEEE Transactions on Cybernetics, 0, 1-15.
https://doi.org/10.1109/tcyb.2021.3070385, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56945
Khan, A., Cao, X., Xu, B., & Li, S. (2022). A Model-Free Approach for Online Optimization of Nonlinear Systems. IEEE Transactions on Circuits and Systems II: Express Briefs, 69(1), 109-113.
https://doi.org/10.1109/tcsii.2021.3079125, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56946
He, Y., Li, X., Xu, Z., Zhou, X., & Li, S. (2021). Collaboration of multiple SCARA robots with guaranteed safety using recurrent neural networks. Neurocomputing, 456, 1-10.
https://doi.org/10.1016/j.neucom.2021.05.049, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56979
Chen, D., Cao, X., & Li, S. (2021). A multi-constrained zeroing neural network for time-dependent nonlinear optimization with application to mobile robot tracking control. Neurocomputing, 460, 331-344.
https://doi.org/10.1016/j.neucom.2021.06.089, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57250
Li, Z. & Li, S. (2022). An L₁-Norm Based Optimization Method for Sparse Redundancy Resolution of Robotic Manipulators. IEEE Transactions on Circuits and Systems II: Express Briefs, 69(2), 469-473.
https://doi.org/10.1109/tcsii.2021.3088942, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57319
Khan, A., Li, S., & Li, Z. (2021). Obstacle avoidance and model-free tracking control for home automation using bio-inspired approach. Advanced Control for Applications, 4(1)
https://doi.org/10.1002/adc2.63, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57438
Khan, A., Khan, A., Li, S., Bakhsh, S., Mehmood, A., & Zaib, J. (2021). Optimally configured Gated Recurrent Unit using Hyperband for the long-term forecasting of photovoltaic plant. Renewable Energy Focus, 39, 49-58.
https://doi.org/10.1016/j.ref.2021.07.002, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57493
Wu, H., Yan, W., Xu, Z., Li, S., & Zhou, X. (2021). Learning robot anomaly recovery skills from multiple time-driven demonstrations. Neurocomputing, 464, 522-532.
https://doi.org/10.1016/j.neucom.2021.08.036, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57655
Li, Z. & Li, S. (2021). Neural Network Model-Based Control for Manipulator: An Autoencoder Perspective. IEEE Transactions on Neural Networks and Learning Systems, 1-15.
https://doi.org/10.1109/tnnls.2021.3109953, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57895
Shi, Y., Zhao, W., Li, S., Li, B., & Sun, X. (2021). Novel Discrete-Time Recurrent Neural Network for Robot Manipulator: A Direct Discretization Technical Route. IEEE Transactions on Neural Networks and Learning Systems, 1-10.
https://doi.org/10.1109/tnnls.2021.3108050, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58131
Katsikis, V., Mourtas, S., Stanimirović, P., Li, S., & Cao, X. (2022). Time-varying mean–variance portfolio selection problem solving via LVI-PDNN. Computers & Operations Research, 138, 105582
https://doi.org/10.1016/j.cor.2021.105582, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58177
Khan, A. & Li, S. (2022). Smart surgical control under RCM constraint using bio-inspired network. Neurocomputing, 470, 121-129.
https://doi.org/10.1016/j.neucom.2021.10.116, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58593
Jiang, K., Li, X., Xu, Z., Zhou, X., & Li, S. (2021). Robust Formation Tracking of Multiple Wheeled Mobile Robots Under External Disturbance. In Intelligent Robotics and Applications (pp. 659-668). Springer International Publishing.
https://doi.org/10.1007/978-3-030-89092-6_60, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58599
Yan, W., Xu, C., Wu, H., Li, S., & Zhou, X. (2021). Real Time Volume Measurement of Logistics Cartons Through 3D Point Cloud Segmentation. In Intelligent Robotics and Applications (pp. 324-335). Springer International Publishing.
https://doi.org/10.1007/978-3-030-89134-3_30, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58601
Li, Z. & Li, S. (2021). Kinematic Control of Manipulator with Remote Center of Motion Constraints Synthesised by a Simplified Recurrent Neural Network. Neural Processing Letters, 54
https://doi.org/10.1007/s11063-021-10678-5, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58642
Zhu, Y., Zou, J., Li, S., & Peng, C. (2022). An adaptive sliding mode observer based near-optimal OER tracking control approach for PEMFC under dynamic operation condition. International Journal of Hydrogen Energy, 47(2), 1157-1171.
https://doi.org/10.1016/j.ijhydene.2021.10.067, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58648
Li, Z., Li, C., Li, S., Zhu, S., & Samani, H. (2022). A sparsity-based method for fault-tolerant manipulation of a redundant robot. Robotica, 0, 1-19.
https://doi.org/10.1017/S0263574722000285, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59462
Khan, A., Cao, X., Li, Z., & Li, S. (2022). Evolutionary Computation Based Real-time Robot Arm Path-planning Using Beetle Antennae Search. EAI Endorsed Transactions on AI and Robotics, 1, 1-10.
https://doi.org/10.4108/airo.v1i.6, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59568
Zhang, Y., Li, S., Cattani, C., & Wang, S. (2022). Editorial: Advanced Deep Learning Methods for Biomedical Information Analysis (ADLMBIA). Frontiers in Big Data, 5, 863060
https://doi.org/10.3389/fdata.2022.863060, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59642
Li, Z. & Li, S. (2022). Model-based recurrent neural network for redundancy resolution of manipulator with remote centre of motion constraints. International Journal of Systems Science, 0, 1-14.
https://doi.org/10.1080/00207721.2022.2070790, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60160
Zhang, Y., Li, S., Weng, J., & Liao, B. (2022). GNN Model for Time-Varying Matrix Inversion With Robust Finite-Time Convergence. IEEE Transactions on Neural Networks and Learning Systems, 1-11.
https://doi.org/10.1109/tnnls.2022.3175899, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60201
Zhang, Y., Li, S., & Weng, J. (2022). Distributed k-Winners-Take-All Network: An Optimization Perspective. IEEE Transactions on Cybernetics, 1-13.
https://doi.org/10.1109/tcyb.2022.3170236, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60207
Chen, D. & Li, S. (2022). DCT-Net: A Neurodynamic Approach with Definable Convergence Property for Real-Time Synchronization of Chaotic Systems. Neural Processing Letters, 0
https://doi.org/10.1007/s11063-022-10911-9, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60254
Francis, A., Li, S., Griffiths, C., & Sienz, J. (2022). Gas source localization and mapping with mobile robots: A review. Journal of Field Robotics, 0
https://doi.org/10.1002/rob.22109, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60541
http://dx.doi.org/10.1002/rob.22109

All Research

Journal Articles

Zhang, Y., Li, S., & Weng, J. (2022). Learning and Near-Optimal Control of Underactuated Surface Vessels With Periodic Disturbances. IEEE Transactions on Cybernetics, 52(8), 7453-7463.
https://doi.org/10.1109/tcyb.2020.3041368, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56084
Francis, A., Li, S., Griffiths, C., & Sienz, J. (2022). Gas source localization and mapping with mobile robots: A review. Journal of Field Robotics, 0
https://doi.org/10.1002/rob.22109, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60541
http://dx.doi.org/10.1002/rob.22109
Chen, D. & Li, S. (2022). DCT-Net: A Neurodynamic Approach with Definable Convergence Property for Real-Time Synchronization of Chaotic Systems. Neural Processing Letters, 0
https://doi.org/10.1007/s11063-022-10911-9, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60254
Li, Z. & Li, S. (2022). Model-based recurrent neural network for redundancy resolution of manipulator with remote centre of motion constraints. International Journal of Systems Science, 0, 1-14.
https://doi.org/10.1080/00207721.2022.2070790, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60160
Zhang, Y., Li, S., Weng, J., & Liao, B. (2022). GNN Model for Time-Varying Matrix Inversion With Robust Finite-Time Convergence. IEEE Transactions on Neural Networks and Learning Systems, 1-11.
https://doi.org/10.1109/tnnls.2022.3175899, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60201
Zhang, Y., Li, S., & Weng, J. (2022). Distributed k-Winners-Take-All Network: An Optimization Perspective. IEEE Transactions on Cybernetics, 1-13.
https://doi.org/10.1109/tcyb.2022.3170236, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60207
Li, Z., Li, C., Li, S., Zhu, S., & Samani, H. (2022). A sparsity-based method for fault-tolerant manipulation of a redundant robot. Robotica, 0, 1-19.
https://doi.org/10.1017/S0263574722000285, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59462
Zhang, Y., Li, S., Cattani, C., & Wang, S. (2022). Editorial: Advanced Deep Learning Methods for Biomedical Information Analysis (ADLMBIA). Frontiers in Big Data, 5, 863060
https://doi.org/10.3389/fdata.2022.863060, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59642
Li, Z. & Li, S. (2022). An L₁-Norm Based Optimization Method for Sparse Redundancy Resolution of Robotic Manipulators. IEEE Transactions on Circuits and Systems II: Express Briefs, 69(2), 469-473.
https://doi.org/10.1109/tcsii.2021.3088942, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57319
Katsikis, V., Mourtas, S., Stanimirović, P., Li, S., & Cao, X. (2022). Time-varying mean–variance portfolio selection problem solving via LVI-PDNN. Computers & Operations Research, 138, 105582
https://doi.org/10.1016/j.cor.2021.105582, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58177
Khan, A. & Li, S. (2022). Smart surgical control under RCM constraint using bio-inspired network. Neurocomputing, 470, 121-129.
https://doi.org/10.1016/j.neucom.2021.10.116, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58593
Khan, A., Cao, X., Li, Z., & Li, S. (2022). Evolutionary Computation Based Real-time Robot Arm Path-planning Using Beetle Antennae Search. EAI Endorsed Transactions on AI and Robotics, 1, 1-10.
https://doi.org/10.4108/airo.v1i.6, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59568
Zhu, Y., Zou, J., Li, S., & Peng, C. (2022). An adaptive sliding mode observer based near-optimal OER tracking control approach for PEMFC under dynamic operation condition. International Journal of Hydrogen Energy, 47(2), 1157-1171.
https://doi.org/10.1016/j.ijhydene.2021.10.067, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58648
Khan, A., Cao, X., Xu, B., & Li, S. (2022). A Model-Free Approach for Online Optimization of Nonlinear Systems. IEEE Transactions on Circuits and Systems II: Express Briefs, 69(1), 109-113.
https://doi.org/10.1109/tcsii.2021.3079125, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56946
Khan, A., Khan, A., Li, S., Bakhsh, S., Mehmood, A., & Zaib, J. (2021). Optimally configured Gated Recurrent Unit using Hyperband for the long-term forecasting of photovoltaic plant. Renewable Energy Focus, 39, 49-58.
https://doi.org/10.1016/j.ref.2021.07.002, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57493
Wu, H., Yan, W., Xu, Z., Li, S., & Zhou, X. (2021). Learning robot anomaly recovery skills from multiple time-driven demonstrations. Neurocomputing, 464, 522-532.
https://doi.org/10.1016/j.neucom.2021.08.036, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57655
Li, Z. & Li, S. (2021). Kinematic Control of Manipulator with Remote Center of Motion Constraints Synthesised by a Simplified Recurrent Neural Network. Neural Processing Letters, 54
https://doi.org/10.1007/s11063-021-10678-5, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58642
Chen, D., Cao, X., & Li, S. (2021). A multi-constrained zeroing neural network for time-dependent nonlinear optimization with application to mobile robot tracking control. Neurocomputing, 460, 331-344.
https://doi.org/10.1016/j.neucom.2021.06.089, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57250
He, Y., Li, X., Xu, Z., Zhou, X., & Li, S. (2021). Collaboration of multiple SCARA robots with guaranteed safety using recurrent neural networks. Neurocomputing, 456, 1-10.
https://doi.org/10.1016/j.neucom.2021.05.049, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56979
Khan, A., Li, S., & Zhou, X. (2021). Trajectory Optimization of 5-Link Biped Robot Using Beetle Antennae Search. IEEE Transactions on Circuits and Systems II: Express Briefs, 68(10), 3276-3280.
https://doi.org/10.1109/tcsii.2021.3062639, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56468
Shi, Y., Zhao, W., Li, S., Li, B., & Sun, X. (2021). Novel Discrete-Time Recurrent Neural Network for Robot Manipulator: A Direct Discretization Technical Route. IEEE Transactions on Neural Networks and Learning Systems, 1-10.
https://doi.org/10.1109/tnnls.2021.3108050, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58131
Li, Z. & Li, S. (2021). Neural Network Model-Based Control for Manipulator: An Autoencoder Perspective. IEEE Transactions on Neural Networks and Learning Systems, 1-15.
https://doi.org/10.1109/tnnls.2021.3109953, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57895
Li, Z. & Li, S. (2021). A Sparse Optimization-Based Control Method for Manipulator With Simultaneous Potential Energy Minimization. IEEE Transactions on Circuits and Systems II: Express Briefs, 68(6), 2062-2066.
https://doi.org/10.1109/tcsii.2020.3045427, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56011
Li, X., Xu, Z., Li, S., Su, Z., & Zhou, X. (2021). Simultaneous Obstacle Avoidance and Target Tracking of Multiple Wheeled Mobile Robots With Certified Safety. IEEE Transactions on Cybernetics, 0, 1-15.
https://doi.org/10.1109/tcyb.2021.3070385, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56945
Xu, Z., Zhou, X., Wu, H., Li, X., & Li, S. (2021). Motion Planning of Manipulators for Simultaneous Obstacle Avoidance and Target Tracking: An RNN Approach with Guaranteed Performance. IEEE Transactions on Industrial Electronics, 1-1.
https://doi.org/10.1109/tie.2021.3073305, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56810
Chen, D., Li, S., & Wu, Q. (2021). A Novel Supertwisting Zeroing Neural Network With Application to Mobile Robot Manipulators. IEEE Transactions on Neural Networks and Learning Systems, 32(4), 1776-1787.
https://doi.org/10.1109/tnnls.2020.2991088, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56719
Zhang, Y., Li, S., & Liao, L. (2021). Input Delay Estimation for Input-Affine Dynamical Systems Based on Taylor Expansion. IEEE Transactions on Circuits and Systems II: Express Briefs, 68(4), 1298-1302.
https://doi.org/10.1109/tcsii.2020.3025136, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56698
Li, X., Li, S., Xu, Z., & Zhou, X. (2021). A Vary-Parameter Convergence-Accelerated Recurrent Neural Network for Online Solving Dynamic Matrix Pseudoinverse and its Robot Application. Neural Processing Letters, 53(2), 1287-1304.
https://doi.org/10.1007/s11063-021-10440-x, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56362
Khan, A., Li, S., & Cao, X. (2021). Tracking control of redundant manipulator under active remote center-of-motion constraints: an RNN-based metaheuristic approach. Science China Information Sciences, 64(3)
https://doi.org/10.1007/s11432-019-2735-6, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56354
Li, Z. & Li, S. (2021). Saturated PI Control for Nonlinear System With Provable Convergence: An Optimization Perspective. IEEE Transactions on Circuits and Systems II: Express Briefs, 68(2), 742-746.
https://doi.org/10.1109/tcsii.2020.3007879, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56220
Khan, A., Li, S., & Li, Z. (2021). Obstacle avoidance and model-free tracking control for home automation using bio-inspired approach. Advanced Control for Applications, 4(1)
https://doi.org/10.1002/adc2.63, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57438
Li, Z., Li, S., & Luo, X. (2021). An overview of calibration technology of industrial robots. IEEE/CAA Journal of Automatica Sinica, 8(1), 23-36.
https://doi.org/10.1109/jas.2020.1003381, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55880
Khan, A., Li, S., & Zhou, X. (2021). Dynamic manipulation of pneumatically controlled soft finger for home automation. Measurement, 170, 108680
https://doi.org/10.1016/j.measurement.2020.108680, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55602
Kadry, S., Zhang, Y., & Li, S. (2020). Advanced microprocessor optimization methods for the Internet of Things. Transactions on Emerging Telecommunications Technologies, 31(12)
https://doi.org/10.1002/ett.4187, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55844
Mao, C., Chen, Z., Li, S., & Zhang, X. (2020). Separable Nonlinear Least Squares Algorithm for Robust Kinematic Calibration of Serial Robots. Journal of Intelligent & Robotic Systems, 101(1)
https://doi.org/10.1007/s10846-020-01268-z, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55908
Li, Z., Li, C., Li, S., & Cao, X. (2020). A Fault-Tolerant Method for Motion Planning of Industrial Redundant Manipulator. IEEE Transactions on Industrial Informatics, 16(12), 7469-7478.
https://doi.org/10.1109/tii.2019.2957186, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52973
Katsikis, V., Mourtas, S., Stanimirović, P., Li, S., & Cao, X. (2020). Time-varying minimum-cost portfolio insurance under transaction costs problem via Beetle Antennae Search Algorithm (BAS). Applied Mathematics and Computation, 385, 125453
https://doi.org/10.1016/j.amc.2020.125453, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa54545
Li, Z., Zuo, W., & Li, S. (2020). Zeroing dynamics method for motion control of industrial upper-limb exoskeleton system with minimal potential energy modulation. Measurement, 163, 107964
https://doi.org/10.1016/j.measurement.2020.107964, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa54389
Cheng, Y., Li, C., Li, S., & Li, Z. (2020). Motion Planning of Redundant Manipulator With Variable Joint Velocity Limit Based on Beetle Antennae Search Algorithm. IEEE Access, 8, 138788-138799.
https://doi.org/10.1109/access.2020.3012564, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55086
http://dx.doi.org/10.1109/access.2020.3012564
Zhang, H., Li, Z., Jiang, X., Ma, X., Chen, J., Li, S., Luan, Y., Lv, Z., & Ma, S. (2020). Beetle Colony Optimization Algorithm and its Application. IEEE Access, 8, 128416-128425.
https://doi.org/10.1109/access.2020.3008692, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa54990
Khan, A., Li, S., & Luo, X. (2020). Obstacle Avoidance and Tracking Control of Redundant Robotic Manipulator: An RNN-Based Metaheuristic Approach. IEEE Transactions on Industrial Informatics, 16(7), 4670-4680.
https://doi.org/10.1109/tii.2019.2941916, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa51997
http://dx.doi.org/10.1109/tii.2019.2941916
Guo, D., Li, S., & Stanimirovic, P. (2020). Analysis and Application of Modified ZNN Design With Robustness Against Harmonic Noise. IEEE Transactions on Industrial Informatics, 16(7), 4627-4638.
https://doi.org/10.1109/tii.2019.2944517, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52457
Brajević, I., Stanimirović, P., Li, S., & Cao, X. (2020). A Hybrid Firefly and Multi-Strategy Artificial Bee Colony Algorithm. International Journal of Computational Intelligence Systems, 13(1), 810-821.
https://doi.org/10.2991/ijcis.d.200612.001, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa54989
Cheng, Z., Pei, H., & Li, S. (2020). Neural-Networks Control for Hover to High-Speed-Level-Flight Transition of Ducted Fan UAV With Provable Stability. IEEE Access, 8, 100135-100151.
https://doi.org/10.1109/access.2020.2997877, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa54501
Chen, D., Li, S., Lin, F., & Wu, Q. (2020). New Super-Twisting Zeroing Neural-Dynamics Model for Tracking Control of Parallel Robots: A Finite-Time and Robust Solution. IEEE Transactions on Cybernetics, 1-10.
https://doi.org/10.1109/TCYB.2019.2930662, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52001
Yue, Z., Li, G., Jiang, X., Li, S., Cheng, J., & Ren, P. (2020). A Hardware Descriptive Approach to Beetle Antennae Search. IEEE Access, 8, 89059-89070.
https://doi.org/10.1109/access.2020.2993600, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa54434
Khan, A. & Li, S. (2020). Sliding Mode Control With PID Sliding Surface for Active Vibration Damping of Pneumatically Actuated Soft Robots. IEEE Access, 8, 88793-88800.
https://doi.org/10.1109/access.2020.2992997, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa54131
Zhang, Y., Li, S., Xu, B., & Yang, Y. (2020). Analysis and design of a distributed k-winners-take-all model. Automatica, 115, 108868
https://doi.org/10.1016/j.automatica.2020.108868, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53516
Yan, W., Xu, Z., Zhou, X., Su, Q., Li, S., & Wu, H. (2020). Fast Object Pose Estimation Using Adaptive Threshold for Bin-Picking. IEEE Access, 8, 63055-63064.
https://doi.org/10.1109/access.2020.2983173, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa54162
Zhang, Y., Ling, Y., Li, S., Yang, M., & Tan, N. (2020). Discrete-time zeroing neural network for solving time-varying Sylvester-transpose matrix inequation via exp-aided conversion. Neurocomputing, 386, 126-135.
https://doi.org/10.1016/j.neucom.2019.12.053, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53117
http://dx.doi.org/10.1016/j.neucom.2019.12.053
Mao, C., Li, S., Chen, Z., Zhang, X., & Li, C. (2020). Robust kinematic calibration for improving collaboration accuracy of dual-arm manipulators with experimental validation. Measurement, 155, 107524
https://doi.org/10.1016/j.measurement.2020.107524, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53485
Khan, A., Cao, X., Katsikis, V., Stanimirovic, P., Brajevic, I., Li, S., Kadry, S., & Nam, Y. (2020). Optimal Portfolio Management for Engineering Problems Using Nonconvex Cardinality Constraint: A Computing Perspective. IEEE Access, 8, 57437-57450.
https://doi.org/10.1109/access.2020.2982195, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53954
Liang, J., Xu, Z., Zhou, X., Li, S., & Ye, G. (2020). Recurrent Neural Networks-Based Collision-Free Motion Planning for Dual Manipulators Under Multiple Constraints. IEEE Access, 8, 54225-54236.
https://doi.org/10.1109/access.2020.2981688, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53940
Chen, D., Li, S., Wu, Q., & Liao, L. (2020). Simultaneous identification, tracking control and disturbance rejection of uncertain nonlinear dynamics systems: A unified neural approach. Neurocomputing, 381, 282-297.
https://doi.org/10.1016/j.neucom.2019.11.031, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52966
Khan, A., Shao, Z., Li, S., Wang, Q., & Guan, N. (2020). Which is the best PID variant for pneumatic soft robots an experimental study. IEEE/CAA Journal of Automatica Sinica, 7(2), 451-460.
https://doi.org/10.1109/jas.2020.1003045, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53870
Khan, A., Cao, X., Li, S., Katsikis, V., & Liao, L. (2020). BAS-ADAM: an ADAM based approach to improve the performance of beetle antennae search optimizer. IEEE/CAA Journal of Automatica Sinica, 7(2), 461-471.
https://doi.org/10.1109/jas.2020.1003048, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53871
Li, X., Xu, Z., Li, S., Wu, H., & Zhou, X. (2020). Cooperative Kinematic Control for Multiple Redundant Manipulators Under Partially Known Information Using Recurrent Neural Network. IEEE Access, 8, 40029-40038.
https://doi.org/10.1109/access.2020.2974248, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53865
Xu, Z., Li, S., Zhou, X., Zhou, S., & Cheng, T. (2020). Dynamic Neural Networks for Motion-Force Control of Redundant Manipulators: An Optimization Perspective. IEEE Transactions on Industrial Electronics, 68(2), 1-1.
https://doi.org/10.1109/tie.2020.2970635, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53696
Gong, W., Chen, D., & Li, S. (2020). Active Sensing of Robot Arms Based on Zeroing Neural Networks: A Biological-Heuristic Optimization Model. IEEE Access, 8, 25976-25989.
https://doi.org/10.1109/access.2020.2971020, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53713
Jiang, X., Lin, Z., He, T., Ma, X., Ma, S., & Li, S. (2020). Optimal Path Finding With Beetle Antennae Search Algorithm by Using Ant Colony Optimization Initialization and Different Searching Strategies. IEEE Access, 8, 15459-15471.
https://doi.org/10.1109/access.2020.2965579, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53741
Liao, B., Ma, C., Liao, M., Li, S., & Huang, Z. (2020). Toward deep neural networks: Mirror extreme learning machines for pattern classification. Filomat, 34(15), 4985-4996.
https://doi.org/10.2298/fil2015985l, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56705
Zhou, X., Xu, Z., & Li, S. (2019). Collision-Free Compliance Control for Redundant Manipulators: An Optimization Case. Frontiers in Neurorobotics, 13
https://doi.org/10.3389/fnbot.2019.00050, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52009
Chen, D., Li, S., Wu, Q., & Luo, X. (2019). Super-twisting ZNN for coordinated motion control of multiple robot manipulators with external disturbances suppression. Neurocomputing
https://doi.org/10.1016/j.neucom.2019.08.085, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52014
Chen, D., Li, S., & Wu, Q. (2019). A Novel Disturbance Rejection Zeroing Neurodynamic Approach for Robust Synchronization of Chaotic Systems. IEEE Access, 7, 121184-121198.
https://doi.org/10.1109/ACCESS.2019.2938016, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52006
Chen, D., Li, S., Li, W., & Wu, Q. (2019). A Multi-Level Simultaneous Minimization Scheme Applied to Jerk-Bounded Redundant Robot Manipulators. IEEE Transactions on Automation Science and Engineering, 1-12.
https://doi.org/10.1109/TASE.2019.2931810, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa51998
Chen, D., Li, S., & Liao, L. (2019). A recurrent neural network applied to optimal motion control of mobile robots with physical constraints. Applied Soft Computing, 85, 105880
https://doi.org/10.1016/j.asoc.2019.105880, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52559
Mao, C., Li, S., Chen, Z., Zu, H., Wang, Z., & Wang, Y. (2019). A Novel Algorithm for Robust Calibration of Kinematic Manipulators and its Experimental Validation. IEEE Access, 7, 90487-90496.
https://doi.org/10.1109/access.2019.2926801, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52004
Xu, Z., Zhou, X., & Li, S. (2019). Deep Recurrent Neural Networks Based Obstacle Avoidance Control for Redundant Manipulators. Frontiers in Neurorobotics, 13
https://doi.org/10.3389/fnbot.2019.00047, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52000
Khan, A., Li, S., Chen, D., & Liao, L. (n.d.) Tracking control of redundant mobile manipulator: An RNN based metaheuristic approach. Neurocomputing
https://doi.org/10.1016/j.neucom.2020.02.109, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53900
Zhang, Y., Huang, H., Li, S., Li, J., & He, L. (n.d.) Event-triggered zeroing dynamics for motion control of Stewart platform. Journal of the Franklin Institute
https://doi.org/10.1016/j.jfranklin.2020.02.060, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53923
Shi, Y., Jin, L., Li, S., & Qiang, J. (n.d.) Proposing, developing and verification of a novel discrete-time zeroing neural network for solving future augmented Sylvester matrix equation. Journal of the Franklin Institute
https://doi.org/10.1016/j.jfranklin.2020.02.024, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53642

Authored Books

Zhou, X., Xu, Z., Li, S., Wu, H., Cheng, T., & Lv, X. (2020). AI based Robot Safe Learning and Control Springer Singapore.
https://doi.org/10.1007/978-981-15-5503-9, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55087
http://dx.doi.org/10.1007/978-981-15-5503-9
Zhang, Y. & Li, S. (2020). Machine Behavior Design And Analysis: A consensus perspective Springer, Singapore.
https://doi.org/10.1007/978-981-15-3231-3, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa54887

Conference Contributions

Jiang, K., Li, X., Xu, Z., Zhou, X., & Li, S. (2021). Robust Formation Tracking of Multiple Wheeled Mobile Robots Under External Disturbance. In Intelligent Robotics and Applications (pp. 659-668). Springer International Publishing.
https://doi.org/10.1007/978-3-030-89092-6_60, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58599
Yan, W., Xu, C., Wu, H., Li, S., & Zhou, X. (2021). Real Time Volume Measurement of Logistics Cartons Through 3D Point Cloud Segmentation. In Intelligent Robotics and Applications (pp. 324-335). Springer International Publishing.
https://doi.org/10.1007/978-3-030-89134-3_30, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58601

Supervision

Model Constrained Neural Network for Robot Arm Control (current)

PhD

Other supervisor: Dr Dunhui Xiao
Robots for Environmental Monitoring and Visualisation (current)

PhD

Other supervisor: Prof Johann Sienz

Taught Modules

EGA366 Kinematics and Programming for Robot

This module first examines the historical development of robotics, both technical and sociological. And then introduces various application of robot technologies focusing on manufacturing, both existing and potential are examined. The core of the module lies in the studies of robot kinematics including trajectory planning and programming. As part of this, industrial standard robot models are analysed and practically experienced through simulation toolkit and commercial software.

Career History

Associate Professor (Reader), Swansea University

2019 - Present