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Bao-Lin Zhang
Researcher at Jilin University
Publications - 207
Citations - 3892
Bao-Lin Zhang is an academic researcher from Jilin University. The author has contributed to research in topics: Control theory & Chemical vapor deposition. The author has an hindex of 27, co-authored 199 publications receiving 3094 citations. Previous affiliations of Bao-Lin Zhang include Ocean University of China & Qingdao University of Science and Technology.
Papers
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An Overview and Deep Investigation on Sampled-Data-Based Event-Triggered Control and Filtering for Networked Systems
TL;DR: This paper provides an overview and makes a deep investigation on sampled-data-based event-triggered control and filtering for networked systems, finding that a sampled- Data-based Event-Triggered Scheme can ensure a positive minimum inter-event time and make it possible to jointly design suitable feedback controllers and event- triggered threshold parameters.
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Event-triggered H∞ reliable control for offshore structures in network environments
TL;DR: In this paper, a network-based model of the offshore structure subject to external wave force and actuator faults is presented, and an event-triggering mechanism is proposed such that during the control implementation, only requisite sampled data is transmitted over networks.
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Sliding Mode Control With Mixed Current and Delayed States for Offshore Steel Jacket Platforms
TL;DR: It is shown through simulation results that this scheme is more effective in both improving the control performance and reducing control force of the offshore platform than some existing ones, such as delay-free sliding mode control, nonlinear control, dynamic output feedback control, and delayed dynamicoutput feedback control.
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Recent advances in vibration control of offshore platforms
TL;DR: There are three types of control schemes, namely passive control, semi-active control, and active control, to deal with vibration of offshore platforms as discussed by the authors, i.e., passive control schemes and several semiactive control schemes.
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Neuronal State Estimation for Neural Networks With Two Additive Time-Varying Delay Components
TL;DR: A linear-matrix-inequality-based approach with two tuning parameters is proposed to design desired Luenberger estimators such that the error system is globally asymptotically stable.