Xiaohua Li
Orcid: 0000-0002-9557-2401Affiliations:
- University of Science and Technology Liaoning, School of Electronic and Information Engineering, Anshan, China
- Harbin Institute of Technology, Control Theory and Guidance Technology Center, Harbin, China (former)
- Lakehead University, Department of Electrical Engineering, Thunder Bay, ON, Canada (former)
- Northeastern University, Shenyang, China (PhD 2006)
According to our database1,
Xiaohua Li authored at least 12 papers
between 2017 and 2025.
Collaborative distances:
Collaborative distances:
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Bibliography
2025
Process-Threshold-Based Fuzzy Adaptive Prescribed Performance Event-Triggered Tracking Control for a Manipulator System.
Int. J. Fuzzy Syst., October, 2025
Double-performance-constraint-based prescribed time fault-tolerant asymptotical tracking control of a dual-link manipulator.
J. Frankl. Inst., 2025
2024
Adaptive prescribed finite-time asymptotic tracking control for switched systems with unknown initial conditions and full-state constraints.
Int. J. Syst. Sci., January, 2024
A variable-barrier-function-based prescribed finite-time bounded-H∞ reinforcement learning optimal tracking control strategy without dependence on initial condition.
J. Frankl. Inst., 2024
2023
A prescribed-performance-based adaptive finite-time tracking control scheme circumventing the dependence on the system initial condition.
Appl. Math. Comput., July, 2023
2021
Annular Domain Finite-Time Connective Control for Large-Scale Systems With Expanding Construction.
IEEE Trans. Syst. Man Cybern. Syst., 2021
Decentralised connectively finite-time control for a class of p-normal form nonlinear large-scale systems with expanding construction and its application.
Int. J. Control, 2021
2020
Adaptive Neural Network Prescribed Performance Bounded- $H_{\infty}$ Tracking Control for a Class of Stochastic Nonlinear Systems.
IEEE Trans. Neural Networks Learn. Syst., 2020
2019
Backstepping-based decentralized bounded-<i>H</i><sub>∞</sub> adaptive neural control for a class of large-scale stochastic nonlinear systems.
J. Frankl. Inst., 2019
2018
Backstepping-based decentralized adaptive neural <i>H</i><sub>∞</sub> tracking control for a class of large-scale nonlinear interconnected systems.
J. Frankl. Inst., 2018
2017
Adaptive neural network decentralized stabilization for nonlinear large scale interconnected systems with expanding construction.
J. Frankl. Inst., 2017
Decentralized connective stabilization of complex large-scale systems with expanding construction employing reduced-order observers: Dedicated to Prof. Dragislav D. Siljak, the grandmaster of complex large-scale systems.
Proceedings of the 2017 IEEE International Conference on Systems, Man, and Cybernetics, 2017