[1]       Linlin Li, Fault Detection and Fault-Tolerant Control for Nonlinear Systems, Springer, 2016.

[2]       Linlin Li, Steven X. Ding, and Xin Peng*, Optimal observer-based fault detection and estimation approaches for T-S fuzzy systems, IEEE Transactions on Fuzzy Systems, 2022, 30(2): 579-590.

[3]       Changsheng Hua, Linlin Li* and Steven X. Ding, Reinforcement Learning-aided Performance-driven Fault-tolerant Control of Feedback Control Systems, IEEE Transactions on Automatic Control, 2022, 67(9): 3013-3020.

[4]       Steven X. Ding, Linlin Li, Dong Zhao, Chris Louen, Application of the unified control and detection framework to detecting stealthy integrity cyber-attacks on feedback control systems, Automatica, 2022, 142: 110352

[5]       Linlin Li^*, and Steven X. Ding, Gap metric techniques and their application to fault detection performance analysis and fault isolation schemes, Automatica, Regular paper, 2020, 118: 109029.

[6]       Linlin Li, Hao Luo, Steven X. Ding, Ying Yang, and Kaixiang Peng, Performance-based fault detection and fault-tolerant control for automatic control systems, Automatica, 2019, 99: 308-316

[7]       Linlin Li^*, and Steven X. Ding, Optimal detection schemes for multiplicative faults in uncertain systems with application to rolling mill processes, IEEE Transactions on Control Systems Technology, 2020, 28(6): 2432-2444.

[8]       Linlin Li, Steven X. Ding, Hao Luo^*, Ying Yang, and Kaixiang Peng, Performance-based fault-tolerant control approaches for industrial processes with multiplicative faults, IEEE Transactions on Industrial Informatics, 2020, 16(7): 4759-4768.

[9]       Linlin Li^*, and Steven X. Ding, Performance supervised fault detection schemes for industrial feedback control systems and their data-driven implementation, IEEE Transactions on Industrial Informatics, 2020, 16(4): 2849-2858.

[10]    Linlin Li, Steven X. Ding, Jianbin Qiu, Kaixiang Peng, and Ying Yang*, An optimal fault detection approach for piecewise affine systems via diagnostic observers, Automatica, 2017, 85: 256-263

[11]    Linlin Li, Steven X. Ding, Jianbin Qiu, Ying Yang*, and Yong Zhang, Weighted fuzzy observer-based fault detection approach for discrete-time nonlinear systems via piecewise-fuzzy Lyapunov functions, IEEE Transactions on Fuzzy Systems, 2016, 24(6): 1320-1333.

[12]    Linlin Li*, Steven X. Ding, Jianbin Qiu, and Ying Yang, Real-time fault detection approach for nonlinear systems and its asynchronous T-S fuzzy observer-based implementation, IEEE Transactions on Cybernetics, 2017, 47(2): 283-294.

[13]    Linlin Li, Steven X. Ding, Jianbin Qiu, Ying Yang*, and Dongmei Xu, Fuzzy observer-based fault detection design approach for nonlinear processes, IEEE Transactions on Systems, Man, Cybernetics: Systems, 2017, 47(8): 1941-1952.

[14]    Linlin Li, Mohammod Chadli, Steven X. Ding, Jianbin Qiu, and Ying Yang*, Diagnostic observer design for T-S fuzzy systems: Application to real-time weighted fault detection approach, IEEE Transactions on Fuzzy Systems, 2018, 26(2): 805-816.

[15]    Linlin Li, Steven X. Ding, Ying Yang*, Kaixiang Peng, and Jianbin Qiu, A fault detection approach for nonlinear systems based on data-driven realizations of fuzzy Kernel representations, IEEE Transactions on Fuzzy Systems, 2018, 26(4): 1800-1812.

[16]   Linlin Li, Steven X. Ding, Xin Peng*. Distributed Data-Driven Optimal Fault Detection for Large-Scale Systems using Average Consensus Algorithm, Journal of Process Control, 2020, 96: 94-103.

[17]    Steven X. Ding, Linlin Li*, and Minjia Krueger, Application of randomized algorithms to assessment and design of observer-based fault detection systems, Automatica, 2019, 107: 175-182

[18]    Ying Yang*, Linlin Li, and Steven X. Ding, A control-theoretic study on Runge-Kutta methods with application to real-time fault-tolerant control of nonlinear systems, IEEE Transactions on Industrial Electronics, 2015, 62(6): 3914-3922

[19]    Ting Xue, Maiying Zhong^*, Linlin Li, and Steven X. Ding, An optimal data-driven approach to distribution independent fault detection, IEEE Transations on Industrial Informatics, 2020, 16(11): 6826-6836