Demo Data from VLDB 2026 / reviewers in the wild / expert
Hanfeng Li
dblp:242/9840
· DBLP profile ↗
6ranked-venue papers
3as first author
5since 2021 · last 2024
0000-0003-1485-7796ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 4 · 2 first-author · 4 since 2021Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Theoretical computer science
1 paper |
Mathematical optimization · 100% |
Topics — the 1 heaviest of 1, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Mathematical optimization
control theory |
0.4 | 1 | 2019 | Quantized control for the class of feedforward nonlinear systems · Sci. China Inf. Sci. 2019 |
Methods — techniques the papers use, named apart from their topics
quantized control · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Event-triggered impulsive tracking control for uncertain strict-feedback nonlinear systems via the neural-network-based backstepping technique
Weihao Pan, Debao Fan, Hanfeng Li, Xianfu Zhang |
Neurocomputing | 3 |
| 2024 | Global Regulation of Feedforward Nonlinear Systems: A Logic-Based Switching Gain ApproachabstractIn this article, we investigate the global regulation problem for a class of feedforward nonlinear systems. Notably, the systems under consideration allow unknown input-output-dependent nonlinear growth rates, which has not been considered in existing works. A novel logic-based switching (LBS) gain approach is proposed to counteract the system uncertainties and nonlinearities. The key idea of the proposed approach is that whenever the Lyapunov function does not decrease as desired, the switching mechanism is activated so that a new gain is adopted. Furthermore, a tanh-type speed-regulation function is embedded into the switching mechanism for the first time to improve the convergence speed and transient performance. Then, a switching adaptive output feedback (SAOF) controller, which is of concise form and low complexity, is proposed based on the developed switching mechanism. It is shown that the objective of global regulation is achieved with faster convergence speed and better transient performance under the proposed controller. Moreover, it is also shown that the proposed control approach can be extended with the enhanced switching mechanism to deal with feedforward nonlinear systems with external disturbances. Finally, numerical examples are presented to demonstrate the effectiveness and advantages of our approach in comparison with the existing approaches. Debao Fan, Xianfu Zhang, Gang Feng 0001, Hanfeng Li |
IEEE Trans. Cybern. | 4 |
| 2023 | Decentralized output-feedback control of triangular large-scale nonlinear impulsive systems with time-varying delays: a gain scaling approach
Debao Fan, Xianfu Zhang, Weihao Pan, Hanfeng Li |
Sci. China Inf. Sci. | 4 |
| 2022 | A Dynamic Gain Approach to Consensus Control of Nonlinear Multiagent Systems With Time DelaysabstractThis article proposes a dynamic gain approach for investigating the leader-follower consensus problem of nonlinear multiagent systems with both distributed delays and discrete delays. It is assumed that each agent is in the strict-feedback form and satisfies the Lipschitz condition with an unknown constant. A novel dynamic gain observer is first constructed for each follower by only utilizing the output information of the follower and its neighbors. By introducing an observer, a distributed output-feedback control protocol is designed for each follower agent under a directed communication topology. It is proved by the Lyapunov-Razumikhin theorem that the consensus of the multiagent system is achieved with the proposed consensus protocol. Different from the existing results, the dynamic gain is constructed for each follower to propose the consensus protocol, without resorting to the celebrated backstepping technique. Moreover, the time-varying gain is designed in a uniform framework. The effectiveness of the proposed approaches is illustrated by a simulation example. Hanfeng Li, Chenghui Zhang, Shuai Liu 0001, Xianfu Zhang |
IEEE Trans. Cybern. | 1 |
| 2021 | Event-Triggered Output Feedback Control of Switched Nonlinear Systems With Input SaturationabstractThis article is concerned with the event-triggered output feedback control problem for a class of switched nonlinear strict-feedback systems subject to asymmetric input saturation. The nonlinear terms are assumed to be bounded by a continuous function of the output multiplied by unmeasured states. The hyperbolic tangent function is employed to process the error caused by the event-triggered scheme, and an indicator function of the saturation degree is used to analyze the influence generated by the asymmetric input saturation. By adopting the common Lyapunov function method and the dynamic gain control design approach, a new design procedure based on a reduced-order observer is proposed to construct an output feedback controller. It is proved by the Lyapunov analysis that the proposed event-triggered control scheme can ensure that all the signals of the closed-loop system are globally bounded. Furthermore, the output can be converged to a bounded region around the origin, and this region can be tuned to be small by adjusting the design parameters. Different from typical existing results on the switched nonlinear strict-feedback systems, the celebrated backstepping method is not employed in this article. The continuous stirred tank reactor is finally used to demonstrate the effectiveness of the proposed control scheme. Hanfeng Li, Xianfu Zhang, Gang Feng 0001 |
IEEE Trans. Cybern. | 1 |
| 2019 | Quantized control for the class of feedforward nonlinear systems
Hanfeng Li, Qingrong Liu, Xianfu Zhang, Xiandong Chen |
Sci. China Inf. Sci. | 1 |