Works matching AU Han, Yu-Qun
Results: 35
Adaptive tracking control for a class of stochastic non‐linear systems with input delay: a novel approach based on multi‐dimensional Taylor network.
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- IET Control Theory & Applications (Wiley-Blackwell), 2020, v. 14, n. 15, p. 2147, doi. 10.1049/iet-cta.2020.0336
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Adaptive tracking control for a class of stochastic non‐linear systems with input saturation constraint using multi‐dimensional Taylor network.
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- IET Control Theory & Applications (Wiley-Blackwell), 2020, v. 14, n. 9, p. 1193, doi. 10.1049/iet-cta.2019.0934
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Adaptive multi‐dimensional Taylor network tracking control for SISO uncertain stochastic non‐linear systems.
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- IET Control Theory & Applications (Wiley-Blackwell), 2018, v. 12, n. 4, p. 1107, doi. 10.1049/iet-cta.2017.0538
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Adaptive tracking control for a class of nonlinear systems with intermittent actuator faults under prescribe output tracking performance.
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- Asian Journal of Control, 2024, v. 26, n. 4, p. 2011, doi. 10.1002/asjc.3317
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Multi‐dimensional Taylor network‐based control for a class of nonlinear stochastic systems with full state time‐varying constraints and the finite‐time output constraint.
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- Asian Journal of Control, 2022, v. 24, n. 6, p. 3311, doi. 10.1002/asjc.2720
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Adaptive decentralized control for large‐scale nonlinear systems with finite‐time output constraints by multi‐ dimensional Taylor network.
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- Asian Journal of Control, 2022, v. 24, n. 4, p. 1769, doi. 10.1002/asjc.2571
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Adaptive prescribed performance control for state constrained stochastic nonlinear systems with unknown control direction: a novel network-based approach.
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- Neural Computing & Applications, 2024, v. 36, n. 6, p. 2737, doi. 10.1007/s00521-023-09125-4
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Adaptive decentralized prescribed performance control for a class of large-scale nonlinear systems subject to nonsymmetric input saturations.
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- Neural Computing & Applications, 2022, v. 34, n. 13, p. 11123, doi. 10.1007/s00521-022-07032-8
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Adaptive finite‐time tracking control of nonlinear systems subject to input hysteresis and multiple objective constraints.
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- International Journal of Robust & Nonlinear Control, 2024, v. 34, n. 15, p. 10292, doi. 10.1002/rnc.7517
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Adaptive finite‐time control for a class of stochastic nonlinear systems with input saturation constraints: A new approach based on multidimensional Taylor network.
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- International Journal of Robust & Nonlinear Control, 2024, v. 34, n. 8, p. 5329, doi. 10.1002/rnc.7266
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Switching threshold‐based event‐triggered adaptive asymptotic tracking control for stochastic nonlinear systems with full‐state constraints.
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- International Journal of Robust & Nonlinear Control, 2023, v. 33, n. 13, p. 7908, doi. 10.1002/rnc.6803
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Tracking control for large‐scale switched nonlinear systems subject to asymmetric input saturation and output hysteresis: A new adaptive network‐based approach.
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- International Journal of Robust & Nonlinear Control, 2022, v. 32, n. 14, p. 8052, doi. 10.1002/rnc.6258
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Multi-dimensional Taylor network-based adaptive fixed-time tracking control for a class of nonlinear systems with input delay.
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- International Journal of Control, 2025, v. 98, n. 1, p. 56, doi. 10.1080/00207179.2024.2319752
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Adaptive backstepping-based sampled-data tracking control with prescribed performance for switched nonlinear systems.
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- International Journal of Control, 2024, v. 97, n. 8, p. 1934, doi. 10.1080/00207179.2023.2241921
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A novel network-based controller design for a class of stochastic nonlinear systems with multiple faults and full state constraints.
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- International Journal of Control, 2024, v. 97, n. 4, p. 651, doi. 10.1080/00207179.2022.2163297
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Tracking control for switched nonlinear systems subject to output hysteresis via adaptive multi-dimensional Taylor network approach.
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- International Journal of Control, 2023, v. 96, n. 7, p. 1724, doi. 10.1080/00207179.2022.2067787
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Adaptive tracking control of a class of nonlinear systems with unknown dead-zone output: a multi-dimensional Taylor network (MTN)-based approach.
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- International Journal of Control, 2021, v. 94, n. 11, p. 3161, doi. 10.1080/00207179.2020.1752941
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Observer-based adaptive neural tracking control for a class of stochastic nonlinear systems.
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- International Journal of Control, 2021, v. 94, n. 5, p. 1344, doi. 10.1080/00207179.2019.1648876
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Adaptive multi-dimensional Taylor network tracking control for a class of nonlinear systems.
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- International Journal of Control, 2021, v. 94, n. 2, p. 277, doi. 10.1080/00207179.2019.1590649
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Observer-based multi-dimensional Taylor network decentralised adaptive tracking control of large-scale stochastic nonlinear systems.
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- International Journal of Control, 2020, v. 93, n. 7, p. 1605, doi. 10.1080/00207179.2018.1521994
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Event‐triggered adaptive tracking control for stochastic nonlinear systems under predetermined finite‐time performance.
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- International Journal of Adaptive Control & Signal Processing, 2024, v. 38, n. 7, p. 2465, doi. 10.1002/acs.3812
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Adaptive decentralized prescribed performance control for a class of large‐scale stochastic nonlinear systems subject to input saturation and full state constraints.
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- International Journal of Adaptive Control & Signal Processing, 2023, v. 37, n. 9, p. 2451, doi. 10.1002/acs.3647
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Controller design for nonlinear systems subject to both input saturation and asymmetry time‐varying state constraints: A novel network‐based approach.
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- International Journal of Adaptive Control & Signal Processing, 2022, v. 36, n. 12, p. 3124, doi. 10.1002/acs.3503
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Adaptive multi‐dimensional Taylor network tracking control for nonlinear systems with input saturation and full state time‐varying constraints.
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- International Journal of Adaptive Control & Signal Processing, 2022, v. 36, n. 9, p. 2152, doi. 10.1002/acs.3447
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Novel adaptive controller design for a class of switched nonlinear systems subject to input delay using multi‐dimensional Taylor network.
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- International Journal of Adaptive Control & Signal Processing, 2022, v. 36, n. 3, p. 607, doi. 10.1002/acs.3362
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Adaptive multi‐dimensional Taylor network funnel control of a class of nonlinear systems with asymmetric input saturation.
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- International Journal of Adaptive Control & Signal Processing, 2021, v. 35, n. 5, p. 713, doi. 10.1002/acs.3224
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Decentralized adaptive multi‐dimensional Taylor network tracking control for a class of large‐scale stochastic nonlinear systems.
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- International Journal of Adaptive Control & Signal Processing, 2019, v. 33, n. 4, p. 664, doi. 10.1002/acs.2978
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Output‐feedback adaptive tracking control of stochastic nonlinear systems using multi‐dimensional Taylor network.
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- International Journal of Adaptive Control & Signal Processing, 2018, v. 32, n. 3, p. 494, doi. 10.1002/acs.2856
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Iteration learning control for 2D linear discrete systems with randomly varying trail lengths.
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- Transactions of the Institute of Measurement & Control, 2024, v. 46, n. 4, p. 638, doi. 10.1177/01423312231179258
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Event-triggered adaptive multi-dimensional Taylor network tracking control for stochastic nonlinear systems.
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- Transactions of the Institute of Measurement & Control, 2024, v. 46, n. 1, p. 193, doi. 10.1177/01423312231174944
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Adaptive finite-time control for stochastic nonlinear systems using multi-dimensional Taylor network.
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- Transactions of the Institute of Measurement & Control, 2022, v. 44, n. 2, p. 457, doi. 10.1177/01423312211039629
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Adaptive multi-dimensional Taylor network tracking control for a class of switched nonlinear systems with input nonlinearity.
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- Transactions of the Institute of Measurement & Control, 2020, v. 42, n. 13, p. 2482, doi. 10.1177/0142331220916601
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Adaptive decentralized tracking control of a class of large-scale nonlinear systems with unknown dead-zone inputs using neural network.
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- Transactions of the Institute of Measurement & Control, 2019, v. 41, n. 16, p. 4499, doi. 10.1177/0142331219861189
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Predefined-time adaptive consensus control for nonlinear multi-agent systems with input quantization and actuator faults.
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- Nonlinear Dynamics, 2024, v. 112, n. 16, p. 14215, doi. 10.1007/s11071-024-09818-y
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Design of decentralized adaptive control approach for large-scale nonlinear systems subjected to input delays under prescribed performance.
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- Nonlinear Dynamics, 2021, v. 106, n. 1, p. 565, doi. 10.1007/s11071-021-06843-z
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