S
Shuai Yuan
Researcher at Harbin Institute of Technology
Publications - 34
Citations - 826
Shuai Yuan is an academic researcher from Harbin Institute of Technology. The author has contributed to research in topics: Adaptive control & Linear system. The author has an hindex of 11, co-authored 30 publications receiving 525 citations. Previous affiliations of Shuai Yuan include Qantas & Delft University of Technology.
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An Adaptive Switched Control Approach to Heterogeneous Platooning With Intervehicle Communication Losses
TL;DR: This paper proposes a novel CACC strategy that overcomes the homogeneity assumption and that is able to adapt its action and achieve string stability even for uncertain heterogeneous platoons, and forms an extended average dwell-time framework and designs an adaptive switched control strategy.
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Adaptive Asymptotic Tracking Control of Uncertain Time-Driven Switched Linear Systems
TL;DR: A time-varying positive definite Lyapunov function is used to develop a novel piecewise continuous model-reference adaptive law and a dwell-time switching law for adaptive asymptotic tracking control of uncertain switched linear systems.
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A novel Lyapunov function for a non-weighted L2 gain of asynchronously switched linear systems
TL;DR: Stability criteria based on the novel Lyapunov function are developed to guarantee global asymptotic stability in the noiseless case and can be used to guarantee a finite non-weighted L 2 gain for asynchronously switched systems, for which LyAPunov functions proposed in literature are inconclusive.
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An Adaptive Learning-Based Approach for Nearly Optimal Dynamic Charging of Electric Vehicle Fleets
TL;DR: An approximate dynamic programming feedback-based optimization method with continuous state space and action space, where the feedback action guarantees uniformity with respect to initial operating conditions, while price variations in the electricity and available solar energy are handled automatically in the optimization.
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Dual estimation: Constructing building energy models from data sampled at low rate
TL;DR: In this article, dual estimation schemes based on Extended Kalman Filtering (EKF) and Unscented Kalman Filter (UKF) were developed for constructing building energy models from data, where an implicit discretization (Euler backward method) was adopted to discretize the continuous-time heat transfer dynamics.