Xiuyan Peng

Harbin Engineering University

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Biao Zhang

Harbin University of Science and Technology

Shuli Jia

Marine Design & Research Institute of China

Lihong Rong

Qingdao Agricultural University

Han Zhou

Shanghai East Hospital

Bo Wang

Harbin Engineering University

Zhao Luo

Harbin Engineering University

Yicong Huang

Harbin Engineering University

Jianxin Lin

Harbin Engineering University

Yao Wu

Wenzhou Medical University

Enhua Chen

Harbin Engineering University

Cooperative Institutions

Harbin Engineering University

Harbin Institute of Technology

Chinese Academy of Sciences

University of Science and Technology of China

Harbin University of Science and Technology

Jilin University

Harbin University

Shanghai Jiao Tong University

Wuhan Ship Development & Design Institute

Northeastern University

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A Reduced-Order Fault Detection Filtering Approach for Continuous-Time Markovian Jump Systems with Polytopic Uncertainties

Complexity (2017)

Lihong Rong Xiuyan Peng Biao Zhang

The fault detection (FD) reduced-order filtering problem is investigated for a family of continuous-time Markovian jump linear systems (MJLSs) with polytopic uncertain transition rates, which also include the totally known and partly unknown transition rates. Then, in accordance with the convexification techniques, a novel sufficient condition for the existence of FD reduced-order filter over MJLSs with deficient transition information is obtained in terms of linear matrix inequality (LMI), which can ensure the error augmented system with the FD reduced-order filter is randomly stable. In addition, a performance index is given to enhance the robustness of the residual system against deficient transition information and external disturbance, such that the error between the fault and the residual is made as small as possible to reinforce the faults sensitivity. Finally, the effectiveness of the proposed method is substantiated with two illustrative examples.

Robustness

Linear matrix inequality

10.1155/2017/4927453

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Citations (14)

Shipboard power system control based on power fluctuation forecasting for photovoltaic penetrated all-electric ships

OCEANS 2022 - Chennai (2022)

Xiuyan Peng Bo Wang Peng Su

With the development of ship electrification and the wide application of renewable energy, the uncertainty of renewable energy output brings a serious challenge to the maintenance of ship power quality. This paper proposes a shipboard power generation system control method to maintain power quality by predicting photovoltaic power fluctuations and generating an additional signal to eliminate the volatility influence. In order to obtain the extra control signal, an adaptive kernel based online sequential extreme learning machine algorithm is designed to predict ship load power fluctuations, which is treated as an additional control signal for shipboard power system. Using an equivalent notional shipboard power system model, the proposed method was verified with various types of sea state scenarios. The test results demonstrate the accuracy of the prediction algorithm and the superiorities of the proposed power generation system control method.

10.1109/oceanschennai45887.2022.9775493

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Citations (1)

T–S Fuzzy-Affine-Model-Based Reliable Output Feedback Control of Nonlinear Systems with Actuator Faults

Circuits Systems and Signal Processing (2017)

Yanling Wei Jianbin Qiu Xiuyan Peng Hak‐Keung Lam

10.1007/s00034-017-0547-0

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Citations (10)

Global well-posedness for nonlinear fourth-order Schrödinger equations

Boundary Value Problems (2016)

Xiuyan Peng Yi Niu Jie Liu Mingyou Zhang Jihong Shen

This paper studies a class of nonlinear fourth-order Schrödinger equations. By constructing a variational problem and the so-called invariant of some sets, we get global existence and nonexistence of the solutions.

10.1186/s13661-016-0534-6

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Control of Ship Course Based on NN-Adaptive Output Feedback

Transactions of Beijing Institute of Technology (2011)

Xiuyan Peng

This paper proposes the NN-adaptive output feedback control method for ship course tracking problem.The stability of the controller is proved by Lyapunov stability theory.The proposed controller only needs the measurable information of course angle,and the unknown disturbances in the complicated sea environment are estimated by neural network.To enhance the robustness of the controller,the structure of controller was designed again by adjusting some parameters and an example with a general cargo ship was shown to verify the effectiveness of the proposed controller.Simulations,with ship course continues changing between 10°and-10°, illustrate that the design controller has strong robustness and good dynamic performance without overshooting.

Robustness

Lyapunov stability

Course (navigation)

Source

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Citations (6)

Particle filtering for nonlinear cyber–physical systems under Round-Robin protocol: Handling complex sensor issues and non-Gaussian noise

Journal of the Franklin Institute (2025)

Beiyuan Li Juan Li Peng Lou Xiuyan Peng Ziyang Wang

Cyber-physical system

Gaussian Noise

Particle (ecology)

10.1016/j.jfranklin.2025.107507

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Application of analytic hierarchy process in evaluating education equipment efficiency factors

Xiaodi Wang Xiuyan Peng

This paper expounds the concept of education equipment efficiency, and analyses the influence factors through four aspects as follows: its own condition, operating rules, undertaken tasks and operator. The evaluation model on education equipment efficiency factors is constructed and its quantitative index weight is given based on AHP (analytic hierarchy process). This paper presents problems that we should pay attention to in evaluating, and gives some remedy measures to avoiding subjectivity influence on drawing index weight. It is proved by example that analytic hierarchy process is suitable resonable in evaluating education equipment effectiveness factors.

Operator (biology)

Analytic network process

10.1109/icbmei.2011.5916883

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Citations (3)

On-line adaptive neural networks for ship motion control

2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (2007)

Xiuyan Peng Xuejing Yang Xiren Zhao

An online neural-net control system, in which learning and control are independently carried out, is proposed for the problem of ship motion control, including roll, yaw and sway stabilization at the same time. Disturbance models, including roll moment, yaw moment and sway force induced by sea wave and wind, are presented by the experimental data in tank. With the three disturbance models as inputs, a recurrent neural network is proposed to approach the forward model of the real ship, and the real time recurrent learning algorithm is described to train the forward model. Then neural-net controller is presented to reduce the roll, yaw and sway synthetically. This paper proposes the adaptation process of control system and applies it to the ship HD702. The approaching accuracy of forward model network and the synthetic control effect of the three motions are investigated.

Yaw

10.1109/iros.2007.4399088

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Citations (2)

The ship motion prediction approach based on BP neural network to identify Volterra series kernels

2022 34th Chinese Control and Decision Conference (CCDC) (2014)

Xiuyan Peng Zhiguo Men Xingmei Wang Shuli Jia

Ship motion prediction plays a prominent role in the whole ship motion process. This paper presents a new approach for ship motion prediction. In order to obtain more effective prediction result, the paper studied the BP neural network and Volterra series model, and the chaos characteristics of ship motion time series. A novel method of single-output three-layer BP neural network to identify Volterra series kernels is proposed. Multi-step prediction for the roll motion time series of ship at 135° with the method is accomplished. The simulation analysis demonstrate that the ship motion prediction approach based on BP neural network to identify Volterra series kernels has higher precision, longer prediction time, effectiveness and adaptability, and it can predict the ship motion exactly.

Volterra series

Adaptability

10.1109/ccdc.2014.6852560

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Citations (2)

The Rudder Roll Damping Control System with Input Constraints Based on T-S Fuzzy Models

Journal of Information and Computational Science (2013)

Xiuyan Peng

In this paper, the Takagi-Sugeno (T-S) fuzzy model of Rudder-roll Damping (RRD) control system was established. Parallel Distributed Compensation (PDC) principle was introduced to the design of the fuzzy controller. The solving of the controller is in terms of the Linear Matrix Inequalities (LMIs). The globally asymptotical stability of the closed-loop system was derived by Lyapunov stability theory. Simulation results verified the effectiveness of the proposed design method.

Rudder

10.12733/jics20103107

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Citations (0)