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Last updated on February 6, 2025. This conference program is tentative and subject to change
Technical Program for Thursday January 30, 2025
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TAT1 |
Level 18 – Pacific Penthouse |
Control Applications |
Regular Session |
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09:00-09:20, Paper TAT1.1 | |
Employing a Relay-Feedback Oscillator for Resonance Tracking |
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Yu, Shiang-Hwua | National Sun Yat-Sen University |
Keywords: Control Applications, Nonlinear Systems and Control, System Modelling and Identification
Abstract: Many applications require a controller to automatically track the resonant frequency of a given resonator. Unlike conventional relay-feedback schemes that use a single relay or saturated amplifier in a feedback loop with the resonator, the proposed scheme employs a relay-feedback oscillator for resonance tracking. To facilitate design and analysis, linearized models for the frequency dynamics of both schemes have been developed. Interestingly, the relay-feedback scheme, despite its name, is actually an open-loop scheme for resonance tracking. On the other hand, the proposed scheme has an inherent feedback mechanism for resonance tracking, leading to better noise rejection and frequency stability.
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09:20-09:40, Paper TAT1.2 | |
Imbalanced Classification of Ultrahigh Carbon Steel Microstructures with Vision Transformers and Image Synthesis of Minority Class |
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Liu, Xiu | Curtin University |
Aldrich, Chris | Curtin University |
Liu, Ke | Dalian Maritime University |
Keywords: Control Applications, Process Automation, Nonlinear Systems and Control
Abstract: In the previous work, the authors have highlighted the potential of vision transformers, new types of deep learning models, in automatic microstructural classification of ultrahigh carbon steel, compared to convolutional neural networks. However, the scarcity of data associated with some classes or microstructures led to the underperformance of the deep learning models in the identification of these microstructures. In this work, as a follow-on to the previous one, the authors have carried out image synthesis of otherwise scarcely represented microstructures to address this class imbalance problem. Results have demonstrated that this additional data augmentation technique can reasonably alleviate the class imbalance problem and improve the model performance.
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09:40-10:00, Paper TAT1.3 | |
Adding Damping to Energy-Efficient Electro-Hydraulic Drives Using Observed Pressure |
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Padovani, Damiano | Guangdong Technion-Israel Institute of Technology |
Keywords: Motion Control, Estimation, Control Applications
Abstract: The increasing focus on energy efficiency directs the research for hydraulic systems towards electro-hydraulic drives, namely actuators directly coupled to pumps driven by electric motors. This approach removes functional power dissipations while enabling energy recovery. However, these drives have inherently low damping that causes harmful payload oscillations, deteriorating the position control’s accuracy of the actuator. Adding active damping via pressure feedback is essential, but the pressure in both actuator chambers must be measured. Thus, this paper proposes using observed pressure where a virtual pressure sensor implemented via software replaces two physical pressure transducers. Direct pressure feedback is applied by relying on a model-based approach for designing closed-loop position control. This method is validated numerically on a heavy-duty robotic manipulator, showing that observed pressure feedback can reduce payload oscillations and ensure proper position tracking.
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TBT1 |
Level 18 – Pacific Penthouse |
Sensor/data Fusion |
Regular Session |
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10:30-10:50, Paper TBT1.1 | |
Distance-Adaptive High-Precision Sensing for Autonomous Modular Buses |
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Lin, Hongyi | Tsinghua University |
Yiping, Yan | Tsinghua University |
Liu, Yang | Tsinghua University |
Yang, Ying | Shanghai University |
Qu, Xiaobo | Tsinghua University |
Keywords: Sensor/data fusion, Automotive Control
Abstract: To address the challenges faced by current public transportation systems, researchers have proposed the Autonomous Modular Bus (AMB), in which individual bus units can connect or disconnect while in motion, allowing passengers to transfer between units, significantly improving convenience and transportation efficiency. However, the high precision required for docking on public roads presents a major challenge, as existing autonomous driving systems struggle to achieve centimeter-level accuracy and exhibit sensitivity to target distances, particularly in perception modules where errors are pronounced. This paper introduces a novel distance-adaptive high-precision sensing module that fuses data from LiDAR and cameras. By utilizing an ensemble learning approach based on attention mechanisms, the proposed module enhances the perception accuracy of autonomous systems. Experiments conducted on the publicly available nuScenes dataset and a self-collected dataset show improvements over state-of-the-art methods. Additionally, the proposed method demonstrates strong adaptability across different distances, making it suitable for all docking scenarios in AMB applications and laying the groundwork for the practical implementation of AMB systems.
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10:50-11:10, Paper TBT1.2 | |
SIFT Based on MediaPipe to Identify Athletic Posture |
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Wu, Jim-Wei | National Central University |
Keywords: Sensor/data fusion, Signal Processing, Real-time Systems
Abstract: This study investigates potential changes in athletes' posture during exercise, addressing the critical issue of improper posture as a primary factor in exercise-related injuries. Using Google MediaPipe, we preprocess video frames and apply the SIFT algorithm to extract feature points and descriptors from the images, enabling detailed analysis of posture variations throughout exercise. Experimental results reveal a significant decrease in similarity when posture deviates from normal alignment. However, the precision of similarity recognition decreases during high-intensity movements. Future research will aim to refine this approach to help athletes better understand their physical limits. By quantifying similarity metrics, athletes may make informed adjustments to body positioning, enhancing safety and performance in subsequent exercises.
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11:10-11:30, Paper TBT1.3 | |
Recognition and Early Warning of Ride-Hailing Vehicle Aggregation Based on Multi-Source Spatiotemporal Data Fusion |
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Wu, Yue | Beijing Intelligent Transportation Development Center |
Zhong, Yang | Beijing Intelligent Transportation Development Center |
Yu, Haitao | Beijing Intelligent Transportation Development Center |
Jiong, Wang | Beijing Intelligent Transportation Development Center |
Yan, Huaimin | Institute of Automation, Chinese Academy of Sciences |
Wang, Jingcheng | Institute of Automation, Chinese Academy of Sciences |
Dai, Xingyuan | Institute of Automation, Chinese Academy of Sciences |
Zhao, Hongxia | Institute of Automation Chinese Academy of Sciences |
Lv, Yisheng | Institute of Automation, Chinese Academy of Sciences |
Keywords: Sensor/data fusion, Time-varying Systems, Real-time Systems
Abstract: This paper proposes a deep learning-based hierarchical warning method designed to detect and respond to abnormal ride-hailing vehicle clustering. By integrating previously developed traffic forecasting and anomaly detection techniques, the method can differentiate varying degrees of clustering severity and trigger appropriate actions. The proposed approach fuses multi-source traffic data, utilizing a convolution-based spatio-temporal feature extraction module to predict ride-hailing vehicle arrival times, and implements a hierarchical warning system based on predefined thresholds. Validation results show that the proposed method can assess the difference between predicted and actual arrival times to evaluate the model's confidence. On a real historical dataset from Beijing, significant deviations were used to identify abnormal ride-hailing behavior, achieving accurate graded warnings.
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TCT1 |
Level 18 – Pacific Penthouse |
Presentation Only Papers |
Regular Session |
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14:00-14:20, Paper TCT1.1 | |
Cyber-Secure Fault Detection and Estimation for Nonlinear CPS Using Resilient Unknown Input Interval Observers |
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Liu, Qidong | University of Electronic Science and Technology |
Ding, Derui | University of Shanghai for Science and Technology |
Han, Qing-Long | Swinburne University of Technology |
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14:20-14:40, Paper TCT1.2 | |
From Distributed Average Consensus to Gain Margin Optimization |
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Chai, Li | Wuhan University of Science and Technology |
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14:40-15:00, Paper TCT1.3 | |
Secure Virtual Coupling Control for Future Railway Cybersecurity |
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Ge, Xiaohua | Swinburne University of Technology |
Han, Qing-Long | Swinburne University of Technology |
Zhang, Xianming | Swinburne University of Technology |
Pan, Dengfeng | Swinburne University of Technology |
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15:00-15:20, Paper TCT1.4 | |
Resource-Efficient Platooning Control of Heterogeneous Connected Automated Vehicles under Replay Attacks |
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Pan, Dengfeng | Swinburne University of Technology |
Ding, Derui | University of Shanghai for Science and Technology |
Ge, Xiaohua | Swinburne University of Technology |
Han, Qing-Long | Swinburne University of Technology |
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TDT1 |
Level 18 – Pacific Penthouse |
Linear Systems |
Regular Session |
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16:00-16:20, Paper TDT1.1 | |
Static Output Feedback Pole Placement Control: Returning Back to the State Space Algebraic Roots |
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Bajodah, Abdulrahman H. | King Abdulaziz University |
Mibar, Hassen | Jeddah College of Technology |
Keywords: Linear Systems
Abstract: This work modifies the Ackermann's pole placement methodology to analyze and to solve the static output feedback pole placement (SOPP) problem for general MIMO LTI systems. To fulfill that purpose, the Moore-Penrose generalized inverse (MPGI)-based Greville formula for linear vector equations is generalized to solve parameter-dependent linear matrix equations. The two mathematical tools are integrated together to develop a necessary and sufficient condition of solution existence for the SOPP problems. The guaranteed existence of the controllability matrix MPGI provides a flexibility to assess non controllable LTI systems for SOPP problem solvability. The proposed design algorithm is based on solving nonlinear coupled equations, but it is non iterative and does not involve norm optimization. Moreover, the proposed design does not involve dimensionality restrictions on the system triplet, and it does not involve pole multiplicity restrictions on the open loop system or the sought closed loop system. The present analysis and synthesis of the pole placement problem utilize only basic state space algebraic manipulations of LTI models, and do not appeal to involved geometric-algebraic concepts, LMIs, or Laplace domain techniques. Three examples are provided to illustrate the control design methodology.
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16:20-16:40, Paper TDT1.2 | |
On Functional Estimator Design for Linear Discrete-Time Descriptor Systems |
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Lone, Jaffar Ali | Indian Institute of Technology Patna |
Jaiswal, Juhi | Indian Institute of Technology Patna |
Bhaumik, Shovan | Indian Institute of Technology Patna |
Tomar, Nutan Kumar | Indian Institute of Technology Patna |
Keywords: Linear Systems, Linear Matrix Inequalities, Estimation
Abstract: This paper addresses the problem of designing functional estimators for linear discrete-time descriptor systems. Unlike full-state estimators, functional estimators are preferred as they directly estimate specific linear combinations of system states without requiring the estimation of the entire state vector. This work presents a new set of sufficient conditions for the existence of functional estimators for discrete-time descriptor systems, expressed in terms of a rank condition and a linear matrix inequality formulation. The effectiveness of the proposed approach is demonstrated through its application to estimating the state of charge of a lithium-ion battery. An academic example is also provided to show that the obtained conditions are less restrictive than those in the existing literature on functional estimators for linear discrete-time descriptor systems.
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16:40-17:00, Paper TDT1.3 | |
Model Order Reduction for Negative Imaginary Systems: Structure-Preserving Approach |
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Mabrok, Mohamed | Qatar University, Doha, Qatar |
Meskin, Nader | Qatar University |
Khattab, Tamer | Qatar University |
Keywords: Linear Systems, Robust Control and Systems
Abstract: Model order reduction (MOR) comprises techniques to simplify the analysis and design of large-scale dynamical systems by reducing their complexity and dimensionality. However, MOR methodologies may fail to preserve structural properties of the original system, including stability, passivity, and negative imaginary (NI) behavior. NI systems constitute a class of dissipative systems prevalent in applications such as flexible structure dynamics and nanopositioning systems, wherein high-order models are frequently encountered. This study proposes a MOR methodology for NI systems that maintains the NI property and improves accuracy. The proposed approach relies on a parameter optimization framework, wherein the reduced order model (ROM) is obtained by iteratively tuning its matrix elements to minimize the error between the original system and the ROM. The NI property is enforced by imposing structural constraints on the ROM parameterization. The efficacy of the proposed method is demonstrated on several NI system examples and compared to existing MOR techniques. It is shown that the proposed approach can achieve significant reduction in model order while preserving the NI property and enhancing the accuracy of the ROM.
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TODV |
Room T2 |
On Demand Videos of Paper Presentation 1 |
Regular Session |
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08:00-17:20, Paper TODV.1 | |
Reducing Order Modelling of Zeta Converter through Hurwitz Polynomial and Padé Approximation |
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Kumari, Khushboo | Motilal Nehru National Institute of Technology Allahabad |
Kumar, Deepak | Motilal Nehru National Institute of Technology Allahabad |
Sreeram, Victor | University of Western Australia |
Keywords: Complex Systems, Linear Systems
Abstract: This paper introduces a new interval model reduction approach for simplifying the dynamic modeling of a Zeta converter using Hurwitz polynomial and Padé approximation. A Zeta converter, characterized as a fourth-order DC-DC buck-boost converter with a non-inverting output, typically exhibits complex dynamic behavior due to variations in its components. To address this, the converter is modeled as an interval system, accounting for ±2% and ±10% variations in system parameters. The interval model is then reduced to a lower-order system by applying the proposed technique. The effectiveness of the reduced-order models is evaluated through time response analysis. The results confirm that the proposed method reduces the model's complexity while preserving essential characteristics, demonstrating the robustness and practicality of the suggested technique.
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