G
Guang-Hong Yang
Researcher at Northeastern University (China)
Publications - 902
Citations - 29810
Guang-Hong Yang is an academic researcher from Northeastern University (China). The author has contributed to research in topics: Control theory & Linear system. The author has an hindex of 72, co-authored 858 publications receiving 22713 citations. Previous affiliations of Guang-Hong Yang include Northeastern University & National University of Singapore.
Papers
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Reliable robust flight tracking control: an LMI approach
TL;DR: A reliable robust tracking controller design method is developed based on the mixed linear quadratic (LQ)//H/sub /spl infin// tracking performance index and multiobjective optimization in terms of linear matrix inequalities.
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Adaptive Fault-Tolerant Tracking Control Against Actuator Faults With Application to Flight Control
Dan Ye,Guang-Hong Yang +1 more
TL;DR: An adaptive fault-tolerant flight controller design method is developed based on the online estimation of an eventual fault and the addition of a new control law to the normal control law in order to reduce the fault effect on the system without the need for a fault detection and isolation (FDI) mechanism.
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Brief Reliable H∞ controller design for linear systems
TL;DR: Proper procedures for designing reliable controllers are presented for the case of sensor failures and actuator failures that can be modeled by a scaling factor and a disturbance.
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Adaptive Backstepping Stabilization of Nonlinear Uncertain Systems With Quantized Input Signal
TL;DR: A stabilization problem for nonlinear uncertain systems via adaptive backstepping approach is considered, and a designed controller together with the quantizer ensures the stability of the closed-loop system in the sense of signal boundedness.
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Leader-Based Optimal Coordination Control for the Consensus Problem of Multiagent Differential Games via Fuzzy Adaptive Dynamic Programming
TL;DR: For the first time, GFHMs are used to approximate the solutions (value functions) of the coupled HJ equations, based on policy iteration algorithm, and the approximation solution is utilized to obtain the optimal coordination control.