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.
Papers
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Composite anti-disturbance control for uncertain Markovian jump systems with actuator saturation based disturbance observer and adaptive neural network
TL;DR: A novel robust composite control scheme is put forward by virtue of adaptive neural network technique to ensure that all the signals of the closed-loop system are asymptotically bounded in mean square.
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Distributed reference model based containment control of second-order multi-agent systems
TL;DR: It can be proved that the containment control problem in a group of agents governed by second-order sampled-data dynamics with directed network topologies can be solved by the proposed controller with appropriate sample period and control parameters.
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Finite-Time $\mathcal{H}_{\infty }$ State Estimation for PDT-Switched Genetic Regulatory Networks with Randomly Occurring Uncertainties
TL;DR: The persistent dwell-time switching, as a more versatile class of switching signal, is considered in this paper to design an estimator to ensure that the estimation error system is stochastically finite-time bounded and satisfies the H∞ performance.
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Reachable set estimation and aperiodic sampled-data controller design for Markovian jump systems
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ℋ ∞ state estimation for Markov jump neural networks with transition probabilities subject to the persistent dwell-time switching rule*
TL;DR: Using the stochastic analysis method and some advanced matrix transformation techniques, some sufficient conditions are obtained such that the estimation error system is mean-square exponentially stable with an H∞ performance level, from which the specific form of the estimator can be obtained.