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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Kim, Ho Joong Lombaerts, Thomas Looye, Gertjan Department of Aerospace Engineering San José State University Santa Clara County San JoseCA95121 United States Aerospace Engineering Department Charles W. Davidson College of Engineering United States KBR NASA Ames Research Center Intelligent Systems Division Mail Stop 269-1 Moffett FieldCA94083 United States Institute of System Dynamics and Control German Aerospace Center DLR Weßling82234 Germany

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This paper describes the design and evaluation of an autoflight controller under maximized crosswind landing scenarios using Nonlinear Dynamic Inversion (NDI) and Incremental Nonlinear Dynamic Inversion (INDI) control methods. The simulation model is representative of a nonlinear, 6 DOF twin-engined civilian transport aircraft in landing configuration starting 300 meters above the runway. The designed flight controller is of cascaded control structure based upon the time scale separation principle. While only INDI based design is evaluated, each control loop implements both NDI and INDI based design, accompanied with feed forward path control for select loops. The controller is evaluated through multiple Monte Carlo statistical analyses, each set containing 2000 landings, which are performed under widely distributed environmental and system parameters. The designed INDI method based controller as discussed in this paper satisfies all safe landing criteria for crosswind landings of up to 30 knots. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Aircraft landing

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An interpretation framework for autonomous vehicles decision-making via SHAP and RF 6

An interpretation framework for autonomous vehicles decision...

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6th CAA International Conference on Vehicular control and Intelligence, CVCI 2022

作者： Cui, Zhihao Li, Meng Huang, Yanjun Wang, Yulei Chen, Hong Clean Energy Automotive Engineering Center School of Automotive Studies Tongji University Shanghai China Tongji University Department of Control Science and Engineering Shanghai China Clean Energy Automotive Engineering Center Shanghai Research Institute for Intelligent Autonomous Systems School of Automotive Studies Tongji University Shanghai China Shanghai Research Institute for Autonomous Systems Tongji University Department of Control Science and Engineering Shanghai China Clean Energy Automotive Engineering Center Shanghai Research Institute for Autonomous Systems Tongji University Department of Control Science and Engineering Shanghai China

ISBN: (数字)9781665453745

ISBN: (纸本)9781665453745

Decision-making for autonomous vehicles is critical to achieving safe and efficient autonomous driving. In recent years, deep reinforcement learning (DRL) techniques have emerged as the most promising way to enable intelligent decision-making. However, DRL with 'black box' nature is not widely understood by humans, thus hindering their social acceptance. In this paper, we combine SHapley Additive exPlanation (SHAP) and random forest (RF) techniques to bring transparency to decision-making obtained by DRL. Specifically, we first implement decision-making of autonomous vehicles following in discrete action space based on DRL algorithm with the goal of safety and efficiency. Then we use the SHAP technique to simplify the feature space, which shows that relative distance, longitudinal speed of the ego vehicle, and longitudinal speed of the proceeding vehicle have a critical impact on vehicle following task. Finally, we collect the state-action pairs generated by the DRL model and perform feature filtering, and fit the decision model with an interpretable RF model. The simulation results show that the RF model achieves the behavioral explanation of autonomous vehicle following. © 2022 IEEE.

关键词： Autonomous vehicles

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Design of Lowpass Filter and Wavelet Analysis for Electroretinogram in Dogs 38

Design of Lowpass Filter and Wavelet Analysis for Electroret...

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38th IEEE Region 10 Conference, TENCON 2023

作者： Tuntrik, Tunyawat Tuntivanich, Nalinee Banjerdpongchai, David Chulalongkorn University Center of Excellence in Intelligent Control Automation of Process Systems Faculty of Engineering Dept. of Electrical Engineering 254 Phayathai Road Pathumwan Bangkok10330 Thailand Faculty of Veterinary Science Dept. of Veterinary Surgery 254 Phayathai Road Pathumwan Bangkok10330 Thailand

ISBN: (纸本)9798350302196

In frequency domain, wavelet coefficient is one of the characteristics of ERG signal which is hidden in frequency-domain. This paper aims to develop a tool for analyzing the constituent frequencies and time of interest in the dog's ERG signal using wavelet analysis. We design a lowpass filter to reduce noise during the measurement of ERG response. ERG dataset was obtained for the light intensity series and their constituent frequencies are analyzed by using the continuous wavelet transform (CWT). The results show that, in time-domain, as light intensity increases, both amplitudes of a-wave and b-wave are higher. We can visualize the noise interference in the ERG signals. Then a lowpass filter is designed to attenuate the noise effect. The filtered signals have lower a-, and b-waves' amplitude which affect the important characteristics in time domain. Therefore, we choose to filter signal from 26ms onward, the main components are recovered, and the filtered signal becomes smoother. In frequency-domain, the peak magnitude of wavelet coefficients is increased as light intensity increases. © 2023 IEEE.

关键词： Wavelet transforms

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Design of Supervisory Model Predictive control for HVAC systems and Two Zones with Consideration of Energy Efficiency and Thermal Comfort

Design of Supervisory Model Predictive Control for HVAC Syst...

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International Conference on control, Automation and systems ( ICCAS)

作者： Panithan Srisurapanon David Banjerdpongchai Department of Electrical Engineering Center of Excellence in Intelligent Control Automation for Process Systems Faculty of Engineering Chulalongkorn University Pathumwan Bangkok Thailand

This paper presents the design of supervisory model predictive control for HVAC systems and two zones. The supervisory control (SC) is designed to find the optimal reference temperature of each zone. The design criteria consist of the total operating cost (TOC) and the thermal comfort cost (TCC). Then, the model predictive control (MPC) is designed to track the optimal reference signals. When SC and MPC are designed for two zones simultaneously, they are referred to centralized SC and centralized MPC. On the other hand, when SC and MPC are designed for two zones separately, they referred to decentralized SC and decentralized MPC. We then compare the results between the decentralized control and the centralized control. The trade-off curve shows that the performance of centralized control is better than that of decentralized control. In particular, centralized MPC improves the performance in tracking reference signals. Furthermore, TOC of centralized control is lower than that of decentralized control. It can be concluded that the centralized control is appropriate for two zones in terms of the tracking of reference and the electrical charge.

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Preassigned-Time Synchronization of Memristive Chaotic Circuit via Intermittent control

Preassigned-Time Synchronization of Memristive Chaotic Circu...

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2023 International Conference on Neuromorphic Computing, ICNC 2023

作者： Wang, Qiming Wang, Leimin Wu, Genping China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Wuhan Second Ship Design and Research Institute Wuhan430064 China

ISBN: (纸本)9798350316889

In this paper, the preassigned-time synchronization (PTS) problem for a fifth-order memristive chaotic circuit (MCC) is investigated by designing a time-dependent intermittent controller. First, the dynamic characteristics of the MCC, especially the existence and occurrence of chaos, are investigated by simulation experiments. Besides, the stability of the equilibrium points is discussed by using Routh-Hurwitz criterion. Then, a time-dependent intermittent controller is designed and the PTS of MCC is realized via the presented controller. Finally, the effectiveness of theoretical results is verified by means of numerical simulations. © 2023 IEEE.

关键词： controllers

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Dynamics Modeling Method of Offshore Drilling Experimental System Based on Double-Layer Stewart Parallel Mechanism 42

Dynamics Modeling Method of Offshore Drilling Experimental S...

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42nd Chinese control Conference, CCC 2023

作者： Wang, Chenxuan Ma, Zhejiaqi Lu, Chengda Du, Sheng Wu, Min School of Future Technology China University of Geosciences Wuhan430074 China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China

ISBN: (纸本)9789887581543

Establishing the dynamics model of the offshore drilling experimental system can better complete the offshore drilling test in the laboratory environment and reduce the cost of testing. A dynamical modeling method for the offshore drilling experimental system built on the double-layer Stewart parallel mechanism is proposed. Firstly, the kinematic and dynamical characteristics of the double-layer Stewart parallel mechanism are combined with the Lagrange method and the virtual work method to establish the dynamics model of the mechanism. Then a parameter identification scheme is designed using a nonlinear gray system estimation method based on the trust-domain reflection algorithm, and the model parameters are identified. The model is downscaled to improve the feasibility of the identification scheme and the accuracy of the identified parameters. The actual experimental system data verify this model's correctness and the model parameters' accuracy. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Dynamics

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Trust Recognition in Human-Robot Cooperation Using EEG

arXiv

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arXiv 2024年

作者： Xu, Caiyue Zhang, Changming Zhou, Yanmin Wang, Zhipeng Lu, Ping He, Bin The Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai201804 China National Key Laboratory of Autonomous Intelligent Unmanned Systems Shanghai201210 China Frontiers Science Center for Intelligent Autonomous Systems Shanghai201210 China

Collaboration between humans and robots is becoming increasingly crucial in our daily life. In order to accomplish efficient cooperation, trust recognition is vital, empowering robots to predict human behaviors and make trust-aware decisions. Consequently, there is an urgent need for a generalized approach to recognize human-robot trust. This study addresses this need by introducing an EEG-based method for trust recognition during human-robot cooperation. A human-robot cooperation game scenario is used to stimulate various human trust levels when working with robots. To enhance recognition performance, the study proposes an EEG Vision Transformer model coupled with a 3-D spatial representation to capture the spatial information of EEG, taking into account the topological relationship among electrodes. To validate this approach, a public EEG-based human trust dataset called EEGTrust is constructed. Experimental results indicate the effectiveness of the proposed approach, achieving an accuracy of 74.99% in slice-wise cross-validation and 62.00% in trial-wise cross-validation. This outperforms baseline models in both recognition accuracy and generalization. Furthermore, an ablation study demonstrates a significant improvement in trust recognition performance of the spatial representation. The source code and EEGTrust dataset are available at https://***/CaiyueXu/EEGTrust. © 2024, CC BY-NC-SA.

关键词： Topology

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Group consensus of multi-agent systems with additive noises

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Science China(Information Sciences) 2022年第10期65卷 242-255页

作者： Chuanjian LI Xiaofeng ZONG School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

This paper is concerned with group consensus of multi-agent systems(MASs) that consist of two groups in additive noise environments. First, a control protocol is proposed based on the state information of each agent's neighbors corrupted by additive noises. Second, some sufficient conditions and necessary conditions are obtained for the following two types of group consensus behaviors.(1) Pure group consensus:agents in both groups have the same behavior(weak consensus or strong consensus);(2) hybrid group consensus: agents in different groups achieve different consensus behaviors. It is revealed that the influence between the two groups should be attenuated such that the MASs can achieve group consensus in additive noise environments, i.e., the affected group must fight against the influence that comes from another ***, some simulation examples are given to illustrate the feasibility of the theoretical results.

关键词： group consensus multi-agent systems additive noises pure group consensus hybrid group consensus

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An Online Education Effect Assessing Method Based on YOLOv8 and Vision Transformer

An Online Education Effect Assessing Method Based on YOLOv8 ...

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2023 China Automation Congress, CAC 2023

作者： Zhang, Bo-Yang Liu, Zhen-Tao Zeng, Xiang-Yu School of Future Technology China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China School of Automation China University of Geosciences Wuhan430074 China

ISBN: (纸本)9798350303759

Due to the rapid growth of online education worldwide, assessing the learning effectiveness of students during online classes has become increasingly challenging for teachers. In this paper, a method of assessing online education effect based on YOLOv8 and Vision Transformer is proposed. Firstly, the drowsiness state of students in an online teaching unconstraint environment is estimated by using YOLOv8, and then the gaze direction of awake students is estimated by using Vision Transformer to assess the students' attention levels during online education. The results from YOLOv8 are determined based on the calculated probabilities of drowsiness or wakefulness. And then gaze estimation method proposed in this paper was compared with state-of-the-art methods on the MPIIFaceGaze and Gaze360 datasets in which the angular errors of gaze estimation are 4.58° and 12.27°, respectively. We conducted experiments and analysis on a self-made dataset, from which the results demonstrate the feasibility of our method in an unconstrained environment. © 2023 IEEE.

关键词： Students

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Explainable Application Intent for Zero-Touch Networking: An Incorporation of Hypergraph and Transformer

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IEEE Transactions on Communications 2025年

作者： Wu, Bing Zou, Sai Liwang, Minghui Ni, Wei Wang, Xianbin Guizhou University College of Big Data and Information Engineering China National Key Laboratory of Autonomous Intelligent Unmanned Systems Department of Control Science and Engineering China Tongji University Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai China Data61 CSIRO Australia Department of Electrical and Computer Engineering Western University Canada

The autonomous interpretation of application intent (APPI) represents the primary step towards achieving closed-loop autonomy in zero-touch networking (ZTN) and also a prerequisite for intent-based networking (IBN). However, understanding APPIs and invoking the corresponding network resources require network professionals with extensive technical expertise to customize network service requests (NSRs), which presents significant challenges for the large-scale deployment of ZTN. This paper investigates an interesting problem of autonomous interpretation of APPIs for ZTN, where a novel mechanism integrating hypergraph and transformer with completeness assurance (HyperTrans-CA) is proposed. In particular, we first involve the Bayesian theory to model APPIs interpretability as maximizing the correct transition probability, where hypergraph is used to describe the complex relationship between application characteristics (e.g., scenario function, and performance) and NSRs, including network devices, virtual network functions (VNFs), and resources. Then, the hypergraph is integrated into the encoder, decoder, and attention mechanisms of Transformer, and a completeness assurance mechanism is designed to improve the prediction accuracy. The convergence of HyperTrans-CA and the corresponding convergence speed of the hypergraph-boosted Transformer in the graph search process are also analyzed. Comprehensive simulations and empirical measurements regarding industrial internet demonstrate that HyperTrans-CA can effectively explain/understand APPIs. Compared to the state-of-the-art Transformer and ChatGPT3.5 models, HyperTrans-CA improves the prediction accuracy of APPIs mapped to VNFs by 23% and 46%, respectively, while raising the prediction accuracy of VNF locations by 8.6 and 17.3 times. © 2025 IEEE.

关键词： Bayesian networks

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