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Hypersonic Re-entry Vehicle Fault-Tolerant control Against Actuator Failure via Integral Sliding Mode

Journal of Beijing Institute of Technology (English Edition) 2021年第ZK期30卷 111-120页

作者： Guo, Fuhui Lu, Pingli School of Automation Beijing Institute of Technology Beijing100081 China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

A fault-tolerant control (FTC) scheme is proposed based on integral sliding mode(ISM) for attitude control of hypersonic re-entry vehicle (HRV) under partial loss of actuator effectiveness. First, the inner/outer loop mathematical model of HRV in the present of actuator failure is given with specific analysis on torque. Then prescribed performance approach is introduced to the ISM controller design by error transformation. Specifically, the transformation error rather than tracking error is chosen as the sliding variable to establish the sliding mode surface and reaching law. As a result, the attitude tracking error of HRV is limited into the expected range. Meanwhile, the transient process and the steady state behavior are both considered. Considering that the unknown fault information of actuator can cause adverse effect on HRV, an extended state observer(ESO) is adopted to estimate the unknown actuator failure. Thus the observer result is served as compensation for the loss of the controlled system performance. Simulation results show that the proposed scheme can fulfil the tracking task with prescribed performance. © 2020 Journal of Beijing Institute of Technology

关键词： Actuators

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A Resilient Data-Driven controller Against DoS Attacks 41

A Resilient Data-Driven Controller Against DoS Attacks

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第41届中国控制会议

作者： Wenjie Liu Jian Sun Gang Wang Jie Chen Key Lab of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing Institute of Technology Chongqing Innovation Center Department of Control Science and Engineering Tongji University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper is concerned with the stabilization problem of linear time-invariant systems under Denial-of-Service(DoS)***,system matrices are unknown,and only some input-output trajectories collected from off-line experiments are ***,in the model-based case,it has been proven that systems equipped with a predictor-based state feedback controller achieve resilience against DoS ***,this is difficult or even impossible to be implemented in the absence of a system model,thus leading to resilient control challenging in the data-based *** maintain resilience against DoS attacks in the data-based case,a data-driven model predictive control(MPC) scheme is proposed such that future system input-output trajectories can be obtained by solving a data-dependent optimal *** this scheme,a data-driven resilient control strategy is developed such that the system achieves the same level of resilience of the DoS attacks as the model-based ***,a numerical example is given to validate the effectiveness of the proposed method.

关键词： Denial-of-service attack data-driven control model predictive control input-to-state stability

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Phase of Multivariable systems: A Revisit via H2T-Dissipativity 62

Phase of Multivariable Systems: A Revisit via H2T-Dissipativ...

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62nd IEEE Conference on decision and control, CDC 2023

作者： Wang, Dan Chen, Wei Johansson, Karl H. Kth Royal Institute of Technology Division of Decision and Control Systems Stockholm Sweden Peking University State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science Beijing China

ISBN: (纸本)9798350301243

A new notion of phase of multi-input multi-output (MIMO) systems was recently defined and studied, leading to new understandings in various fronts including a formulation of small phase theorem, a performance criterion named H∞ phase sector, and a sectored real lemma, etc. In this paper, we define a new notion of H2T-dissipativity and show the connection between the phase of a multivariable linear time-invariant (LTI) system and the H2T-dissipativity. The H2T-dissipativity, roughly speaking, is dissipativity restricted to the time-domain H2 space which consists of L2 signals with only positive frequency components. In addition, by exploiting the newly defined H2T- dissipativity, we also study the phase of a feedback system and provide a physical interpretation of the sectored real lemma. © 2023 IEEE.

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Gait Planning and Motion control Based on Vrep Simulation for Quadruped Robot 5

Gait Planning and Motion Control Based on Vrep Simulation fo...

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5th World Robot Conference Symposium on Advanced Robotics and Automation, WRC SARA 2023

作者： Zhou, Linqi Chen, Zhihua Liu, Jun Liu, Zhi Chen, Yumeng Zhang, Liting Nanchang Hangkong University Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Moe Key Lab of Nondestructive Testing Technology Nanchang330063 China Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing100081 China

ISBN: (纸本)9798350307320

Gait planning of quadruped robots plays an important role in achieving less walking, including dynamic and static gait. In this article, a static and dynamic gait control method based on center of gravity stability margin is proposed. Firstly, the robot model and kinematics modeling are introduced. Secondly, the robot's foot static and dynamic gait were planned and the foot trajectory was designed. Finally, two types of gait of the robot were simulated using Vrep simulation software, and the differences in stability and speed between the coordinated gait with speed and stability in the static and dynamic gait of a 12 degree of freedom robot were analyzed, verifying the effectiveness of the gait control method proposed in this paper. © 2023 IEEE.

关键词： Robot programming

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Data-Driven Discovery of Nonlinear Dynamical systems from Noisy and Sparse Observations

Data-Driven Discovery of Nonlinear Dynamical Systems from No...

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2024 International Conference on New Trends in Computational Intelligence, NTCI 2024

作者： Zhu, Wei Pei, Chao Liang, Yulan Chen, Zhang Li, Jingsui School of Science Chongqing University of Posts and Telecommunications Chongqing China Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing China College of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (纸本)9798331517021

Sparse Identification of Nonlinear Dynamics (SINDy) is a data-driven algorithm for interpretability mod-eling. SINDy has a strong ability to learn dynamical systems from time series data. Sparse Identification of Nonlinear Dynamics (SINDy) can extract equations from data, but its performance will degrade when data has noise or sparse. In order to deal with this case, the idea of Monte Carlo Markov Chain (MCMC) is introduced, which is used to optimally select models. The SINDy with MCMC (MCMC-SINDy) can comprehensively discover model structures by employing random samples in data space. Simulation results show that MCMC-SINDy is more robust than SINDy with 1 % -15 % levels of noise or sparse 0.5. These results are promising for the discovery of governing equations for complex systems in neuroscience, power grids, epidemiology, finance or ecology, where governing equations have remained elusive. mportantly, compared to existing machine learning methods, the accuracy of modeling using MCMC SINDy is higher. © 2024 IEEE.

关键词： Markov chains

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CFSeRec:A Contrastive Framework for Sequential Recommendation

CFSeRec:A Contrastive Framework for Sequential Recommendatio...

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第42届中国控制会议

作者： Tong Wang Yaping Dai Shuai Shao School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

In sequential recommender systems,the main problems are the long-tailed distribution of data and noise interference.A Contrastive Framework for Sequential Recommendation(CFSeRec) is proposed to solve these two problems *** shuffling and adversarial attack data augmentation methods are used in the framework to improve the quality and quantity of training data,so that the long-tailed problem is *** the application of projection head method,the sequence representation becomes more general and robust,rather than just adapted to the task of contrastive ***,the impact of noise on sequence recommender systems is effectively *** on four public datasets show that CFSeRec achieves state-of-the-art performance in the metrics of hit ratio and normalized discounted cumulative gain,when comparing to the seven previous frameworks.

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Interpretable Fourier Neural Ordinary Differential Equations

Interpretable Fourier Neural Ordinary Differential Equations

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Fully Actuated System Theory and Applications (CFASTA), Conference on

作者： Hanlin Bian Wei Zhu Zhang Chen Jingsui Li Chao Pei Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

Numerous interacting elements can form complex systems. However, describing complex systems is extremely challenging and lacks interpretability. The construction of models still heavily relies on scientists’ understanding of complex systems. This paper explores the use of neural ordinary differential equations in the field of complex system modeling. The proposed Fourier neural ordinary differential equations offer interpretability and a relatively simple structure. By building upon interpretable modeling, the scale is significantly reduced. It is possible to deduce the system’s expression from the model’s parameters. Finally, a real-world system is provided to illustrate the effectiveness of the proposed model, demonstrating its commendable robustness.

关键词： Training Atmospheric modeling Fitting Time series analysis Ordinary differential equations Predictive models Mathematical models

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Two Degree of Freedom Active Disturbance Rejection control Strategy for Time Delay systems

Two Degree of Freedom Active Disturbance Rejection Control S...

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第42届中国控制会议

作者： Xiyuan Shan Tao Cai School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

This paper is concerned with the controller design and the theoretical analysis for time-delay systems,a two degree of freedom(feedforward and feedback) control method is proposed,which combines advantages of the Smith predictor and the active disturbance rejection control(ADRC).The feedforward part of controller is used to track the set point,the feedback part of controller(ADRC) is used to suppress interferences and the Smith predictor is used to correct time *** proposed control design is easy to tune parameters and has been proved to effectively control systems with large time *** bounded input bounded output(BIBO) stability of closed-loop system is ***,numerical simulations show the effectiveness and practicality of the proposed design.

关键词： Time-delay Active Disturbance Rejection control(ADRC) Smith Predictor(SP)

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Comprehensive Gear Shift Schedule Design for 2-AMT Electric Vehicles Based on Sparrow Search Algorithm

Comprehensive Gear Shift Schedule Design for 2-AMT Electric ...

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第42届中国控制会议

作者： Tianyi Wang Liling Ma Junzheng Wang State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

With the aim of 2-AMT electric vehicles,a comprehensive shift schedule that considers both power and economy is ***,the objective function of the comprehensive shift schedule is constructed,which is the weighted sum of vehicle acceleration time and vehicle power consumption per unit ***,Sparrow Search Algorithm is used to solve the objective function and obtain the comprehensive shift ***,AVL Cruise simulation software is used to simulate vehicle dynamics and economy under an *** results show that the comprehensive shift schedule is similar to the optimal power shift schedule in terms of dynamic performance,and the economy is optimized by 3%.The feasibility of the comprehensive shift schedule is verified.

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Research on Urban Air Quality Prediction Method Based on the Fusion of Wide-area Spatiotemporal Distribution Data 26

Research on Urban Air Quality Prediction Method Based on the...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Tao, Zixing Cao, Weihua Gan, Chao Wuhan China School of Future Technology School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

ISBN: (纸本)9798331521950

Air quality data exhibit nonlinearity, sensitivity to environmental factors, and long-term dependencies. Numerous factors influence air quality, making accurate predictions based on a single-dimensional dataset impractical. This study proposes a method for urban air quality prediction that integrates wide-area spatiotemporal data, designed to address the unique characteristics of air quality datasets. First, relevant wide-area spatiotemporal data are selected, and their correlations with air quality are systematically analyzed. Second, a Long Short-Term Memory (LSTM) network-based Transformer model is utilized to capture the long-term dependencies in the air quality sequences. Finally, the model successfully generates hourly multi-step predictions for six air pollutants. The experimental results show that the proposed method outperforms the method that relies on air quality data alone for multi-step air quality prediction. © 2025 IEEE.

关键词： Air quality

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