H
Hao Shen
Researcher at Anhui University of Technology
Publications - 296
Citations - 12245
Hao Shen is an academic researcher from Anhui University of Technology. The author has contributed to research in topics: Computer science & Control theory. The author has an hindex of 54, co-authored 225 publications receiving 8681 citations. Previous affiliations of Hao Shen include Nanjing University of Science and Technology & Yeungnam University.
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Fuzzy-Model-Based $\mathcal{H}_{\infty }$ Pinning Synchronization for Coupled Neural Networks Subject to Reaction-Diffusion
TL;DR: Through the utilization of fuzzy set theory together with Lyapunov stability theory, some sufficient conditions with the ability to ensure the performance level of the resulting synchronization error system are deduced are found.
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Stabilization Criteria for Singular Fuzzy Systems With Random Delay and Mixed Actuator Failures
TL;DR: In this article, the problem of reliable sampled-data control design for uncertain singular fuzzy system with randomly occurring delay and nonlinear actuator failures is studied, where the fault model is composed of two parts in which, linear part stands for the gain missing of actuators that vary with the true control input linearly, while the nonlinear part indicates some bounded nonlinear variation.
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Passivity‐based stochastic sampled‐data control of Markovian jump systems via looped‐functional approach
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Dissolved Oxygen Model Predictive Control for Activated Sludge Process Model Based on the Fuzzy C-means Cluster Algorithm
TL;DR: The aim is to design a predictive controller that is capable of performing the online track of dissolved oxygen attributed to better dynamic response and steadier output in different weather.
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Multiple-interval-dependent robust stability analysis for uncertain stochastic neural networks with mixed-delays
TL;DR: Based on the new technique dealing with matrix cross-product and multiple-interval-dependent Lyapunov-Krasovskii functional, some novel delay-dependent stability criteria with less conservatism and less decision variables for the addressed system are derived in terms of linear matrix inequalities.