G
Guanyu Lai
Researcher at Guangdong University of Technology
Publications - 50
Citations - 1613
Guanyu Lai is an academic researcher from Guangdong University of Technology. The author has contributed to research in topics: Nonlinear system & Adaptive control. The author has an hindex of 19, co-authored 38 publications receiving 1043 citations. Previous affiliations of Guanyu Lai include Nanyang Technological University & University of Virginia.
Papers
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Adaptive Neural Control for a Class of Nonlinear Time-Varying Delay Systems With Unknown Hysteresis
TL;DR: This paper investigates the fusion of unknown direction hysteresis model with adaptive neural control techniques in face of time-delayed continuous time nonlinear systems without strict-feedback form and proposes two neural-network-based adaptive control algorithms.
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Adaptive Neural Output Feedback Control of Output-Constrained Nonlinear Systems With Unknown Output Nonlinearity
TL;DR: This paper addresses the problem of adaptive neural output-feedback control for a class of special nonlinear systems with the hysteretic output mechanism and the unmeasured states with the Lyapunov function technique.
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Adaptive Fuzzy Tracking Control of Nonlinear Time-Delay Systems With Dead-Zone Output Mechanism Based on a Novel Smooth Model
TL;DR: A new optimized algorithm is developed to guarantee the prescribed convergence of tracking error and the boundedness of all the signals in the closed-loop systems by using the proposed output dead-zone model based on Lyapunov synthesis.
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Fuzzy Adaptive Inverse Compensation Method to Tracking Control of Uncertain Nonlinear Systems With Generalized Actuator Dead Zone
TL;DR: This paper solves the problem of adaptive fuzzy inverse compensation control for an uncertain nonlinear system whose actuator is subjected to generalized dead-zone nonlinearity by defining a continuous connection function and combining with the mean-value theorem.
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Adaptive Consensus Tracking Control of Uncertain Nonlinear Multiagent Systems With Predefined Accuracy
TL;DR: It is proved that the proposed controller achieves a perfect asymptotic consensus performance and a tunable $L_{2}$ transient performance of synchronization errors, whereas most existing results can only ensure the stability.