H
Huijun Gao
Researcher at Harbin Institute of Technology
Publications - 722
Citations - 50296
Huijun Gao is an academic researcher from Harbin Institute of Technology. The author has contributed to research in topics: Linear matrix inequality & Control theory. The author has an hindex of 121, co-authored 685 publications receiving 44399 citations. Previous affiliations of Huijun Gao include Brunel University London & Xidian University.
Papers
More filters
Journal ArticleDOI
Fault Detection for Nonlinear Process With Deterministic Disturbances: A Just-In-Time Learning Based Data Driven Method
TL;DR: The proposed JITL-DD fault detection method provides a data-driven fault detection solution for nonlinear processes with deterministic disturbances, and owns inherent online adaptation and high accuracy of fault detection.
Journal ArticleDOI
$H_{\bm \infty}$ Fuzzy Control for Systems With Repeated Scalar Nonlinearities and Random Packet Losses
TL;DR: Sufficient conditions are obtained for the existence of admissible controllers, and the cone complementarity linearization procedure is employed to cast the controller design problem into a sequential minimization one subject to linear matrix inequalities, which can be readily solved by using standard numerical software.
Journal ArticleDOI
Transient-Performance-Guaranteed Robust Adaptive Control and Its Application to Precision Motion Control Systems
TL;DR: A novel model reference adaptive control with external filter is proposed to not only stabilize the error system but also guarantee its transient performance to solve the adaptive tracking-control problem for a class of nonlinear systems with uncertain parameters, disturbance, and unmodeled dynamics.
Journal ArticleDOI
Adaptive Fault-Tolerant Control for Nonlinear System With Unknown Control Directions Based on Fuzzy Approximation
TL;DR: A fuzzy adaptive failure compensation control strategy is developed that guarantees the semi-global boundedness for all signals and takes advantage of the adaptive fuzzy control method and backstepping technology.
Journal ArticleDOI
Neural networks letter: Novel stability of cellular neural networks with interval time-varying delay
TL;DR: A new criterion of asymptotic stability is derived in terms of a linear matrix inequality (LMI), which can be efficiently solved via standard numerical software and proves to be less conservative than most of the existing results.