Harbin Engineering University

About: Harbin Engineering University is a education organization based out in Harbin, Heilongjiang, China. It is known for research contribution in the topics: Control theory & Computer science. The organization has 31149 authors who have published 27940 publications receiving 276787 citations. The organization is also known as: HEU.

Dissipativity-Based Reliable Control for Fuzzy Markov Jump Systems With Actuator Faults

Abstract: This paper is concerned with the problem of reliable dissipative control for Takagi-Sugeno fuzzy systems with Markov jumping parameters. Considering the influence of actuator faults, a sufficient condition is developed to ensure that the resultant closed-loop system is stochastically stable and strictly ( $\boldsymbol {\mathcal {Q}}, \boldsymbol {\mathcal {S}},\boldsymbol {\mathcal {R}}$ )-dissipative based on a relaxed approach in which mode-dependent and fuzzy-basis-dependent Lyapunov functions are employed. Then a reliable dissipative control for fuzzy Markov jump systems is designed, with sufficient condition proposed for the existence of guaranteed stability and dissipativity controller. The effectiveness and potential of the obtained design method is verified by two simulation examples.

Observer-Based Fuzzy Adaptive Output-Feedback Control of Stochastic Nonlinear Multiple Time-Delay Systems

Abstract: This paper is concerned with the observer-based fuzzy output-feedback control for stochastic nonlinear multiple time-delay systems. On the basis of the consistent form of virtual input signals and increasing characteristics of the system upper bound functions, a variable splitting technique is employed to surmount the difficulty occurred in the nonlower-triangular form. In the controller design procedure, a state observer is first designed, and then an adaptive fuzzy output-feedback control method is presented by combining backstepping design together with fuzzy systems’ universal approximation capability. The proposed adaptive controller guarantees the semi-global boundedness of closed-loop system trajectories in terms of fourth-moment. Two simulation examples are displayed to demonstrate the feasibility of the suggested controller.

An Intrusion Detection Model Based on Feature Reduction and Convolutional Neural Networks

Abstract: With the popularity and development of network technology and the Internet, intrusion detection systems (IDSs), which can identify attacks, have been developed. Traditional intrusion detection algorithms typically employ mining association rules to identify intrusion behaviors. However, they fail to fully extract the characteristic information of user behaviors and encounter various problems, such as high false alarm rate (FAR), poor generalization capability, and poor timeliness. In this paper, we propose a network intrusion detection model based on a convolutional neural network-IDS (CNN-IDS). Redundant and irrelevant features in the network traffic data are first removed using different dimensionality reduction methods. Features of the dimensionality reduction data are automatically extracted using the CNN, and more effective information for identifying intrusion is extracted by supervised learning. To reduce the computational cost, we convert the original traffic vector format into an image format and use a standard KDD-CUP99 dataset to evaluate the performance of the proposed CNN model. The experimental results indicate that the AC, FAR, and timeliness of the CNN-IDS model are higher than those of traditional algorithms. Therefore, the model we propose has not only research significance but also practical value.

Two-dimensional net-like SnO2/ZnO heteronanostructures for high-performance H2S gas sensor

Abstract: H2S gas in the environment, even at a concentration as low as 20 ppb, is very harmful to the health of human beings. Therefore, the design and fabrication of sensors for detecting trace H2S gas in the environment are highly desirable. However, it remains a challenge to develop gas sensors that can detect H2S at ppb concentration levels and at a relatively low temperature. Herein we developed a facile method to fabricate porous two-dimensional net-like SnO2/ZnO heteronanostructures. Both the SnO2 and ZnO nanoparticles were significantly smaller in the net-like heteronanostructures than in net-like SnO2 and ZnO homonanostructures. Heterojunctions formed at the interfaces between SnO2 and ZnO—and, as a result, the net-like SnO2/ZnO heteronanostructures—exhibited better H2S-sensing properties, including higher sensor response, better selectivity and long-term stability, than did the net-like SnO2 and ZnO homonanostructures, and other types of metal oxide-based nanocomposites. Importantly, the SnO2/ZnO heteronanostructures could detect 10 ppb H2S even at a working temperature of 100 °C. Therefore, the net-like SnO2/ZnO heteronanostructures have very promising applications in high-performance H2S sensors. In addition, the fabrication method presented here is facile, repeatable and operable, and may thus be extended to synthesize other types of metal oxide-based heteronanostructures for applications in various fields.