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Yongming Li
Researcher at Liaoning University of Technology
Publications - 485
Citations - 14529
Yongming Li is an academic researcher from Liaoning University of Technology. The author has contributed to research in topics: Fuzzy logic & Backstepping. The author has an hindex of 54, co-authored 444 publications receiving 10604 citations. Previous affiliations of Yongming Li include Peking University & Northwestern Polytechnical University.
Papers
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Observer-Based Adaptive Fuzzy Backstepping Control for a Class of Stochastic Nonlinear Strict-Feedback Systems
TL;DR: It is proved that these two control approaches can guarantee that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) in mean square, and the observer errors and the output of the system converge to a small neighborhood of the origin.
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Observer-based fuzzy adaptive control for strict-feedback nonlinear systems
Shaocheng Tong,Yongming Li +1 more
TL;DR: It is proven that the proposed fuzzy adaptive control approach guarantees the semi-global boundedness property for all the signals and the tracking error to a small neighborhood of the origin.
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Fuzzy Approximation-Based Adaptive Backstepping Optimal Control for a Class of Nonlinear Discrete-Time Systems With Dead-Zone
TL;DR: An adaptive fuzzy optimal control design is addressed for a class of unknown nonlinear discrete-time systems that contain unknown functions and nonsymmetric dead-zone and can be proved based on the difference Lyapunov function method.
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Observer-Based Neuro-Adaptive Optimized Control of Strict-Feedback Nonlinear Systems With State Constraints
TL;DR: In this article, an adaptive neural network (NN) output feedback optimized control design for a class of strict-feedback nonlinear systems that contain unknown internal dynamics and the states that are immeasurable and constrained within some predefined compact sets is proposed.
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Fuzzy Adaptive Actuator Failure Compensation Control of Uncertain Stochastic Nonlinear Systems With Unmodeled Dynamics
TL;DR: It is proved that the proposed control approach can guarantee that all the signals of the closed-loop system are bounded in probability in the presence of the actuator failures and the unmodeled dynamics.