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作者： Sean Smith Emmanuel Witrant Ya-Jun Pan GIPSA-lab Université Grenoble Alpes - CNRS Grenoble France Department of Mechanical Engineering Dalhousie University Halifax NS Canada Department of Mechanical Engineering Advanced Control and Mechatronics Laboratory Dalhousie University Halifax NS Canada

ISBN: (数字)9798331540081

ISBN: (纸本)9798331540098

This article investigates high-precision robust heading control for an autonomous sailboat. First, the mathematical model of an autonomous sailboat is highlighted and discussed, with a particular focus on the heading dynamics that must be robustly controlled under real-world conditions. Typical control difficulties such as system disturbances, modeling uncertainty, control actuation saturation, and measurement noise are considered and addressed with reference to the controller and system modeling. We propose a control method that ensures robust heading control of an autonomous sailboat in the presence of these challenges. A reference simulator in Matlab/Simulink is used as a simulation testbed to demonstrate the benefits of state-of-the-art robust control developments. A multiphase simulation is conducted to compare the advantages and disadvantages of model-based robust control with linear techniques such as proportional-integral-derivative (PID) control.

关键词： Robust control Uncertainty Sensitivity PI control Noise Sea measurements Systems modeling Mathematical models PD control Testing

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Planning and Decision-making for Connected Autonomous Vehicles at Road Intersections:A Review

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Chinese Journal of mechanical engineering 2021年第5期34卷 26-43页

作者： Shen Li Keqi Shu Chaoyi Chen Dongpu Cao Department of Civil Engineering Tsinghua UniversityBeijingChina CogDrive Lab Department of Mechanical and Mechatronics EngineeringUniversity of WaterlooWaterlooON N2L 3G1Canada School of Vehicle and Mobility Tsinghua UniversityBeijingChina

Planning and decision-making technology at intersections is a comprehensive research problem in intelligent transportation systems due to the uncertainties caused by a variety of traffic *** wireless communication advances,vehicle infrastructure integrated algorithms designed for intersection planning and decision-making have received increasing *** this paper,the recent studies on the planning and decision-making technologies at intersections are primarily *** general planning and decision-making approaches are presented,which include graph-based approach,prediction base approach,optimization-based approach and machine learning based *** connected autonomous vehicles(CAVs)is the future direction for the automated driving area,we summarized the evolving planning and decision-making methods based on vehicle infrastructure cooperative *** four-way signalized and unsignalized intersection(s)are investigated under purely automated driving traffic and mixed *** study benefit from current strategies,protocols,and simulation tools to help researchers identify the presented approaches’challenges and determine the research gaps,and several remaining possible research problems that need to be solved in the future.

关键词： Planning Decision-making Autonomous intersection management Connected autonomous vehicles

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Effects of post heat treatment on microstructure and mechanical properties of Ti5553 parts made by laser powder bed fusion

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Journal of Alloys and Compounds 2023年第1期938卷

作者： Ramachandiran, Nivas Asgari, Hamed Dibia, Francis Eybel, Roger Muhammad, Waqas Gerlich, Adrian Toyserkani, Ehsan Lab Department of Mechanical and Mechatronics Engineering University of Waterloo WaterlooONN2L 3G1 Canada Lab Department of Mechanical and Mechatronics Engineering University of Waterloo WaterlooONN2L 3G1 Canada Safran Landing Systems 574 Monarch Avenue AjaxONL1S 2G8 Canada Department of Mechanical and Mechatronics Engineering University of Waterloo WaterlooONN2L 3G1 Canada

Rapid heating and solidification rates involved in additive manufacturing result in non-homogenous microstructural features, microsegregation and residual stresses, leading to deteriorated mechanical properties. Although the rather new Ti-5553 (Ti‐5Al‐5Mo‐5V‐3Cr) metastable β-Ti alloy is printable by laser powder-bed fusion (LPBF), it exhibits poor mechanical strength compared to conventionally forged components due to the lack of second phase strengthening in the as-printed state. Therefore, post-processing heat treatment is essential to enhance the mechanical properties of the printed parts. In this research work, LPBF-made Ti-5553 specimens were subjected to varying heat treatment cycles to modify their corresponding microstructure in terms of the morphology and distribution of α particles. Differential Scanning Calorimetry (DSC), X-Ray diffraction (XRD) patterns, and electron backscatter diffraction (EBSD) results suggest that solutionizing at the upper α + β region (800 °C) offers a good combination of finer grain size and satisfactory α dissolution. On aging in the range of 500 – 700 °C for 0.5 – 4 h, growth of α particles with different morphologies was observed. A combination of multiple α morphologies, including Widmanstätten, lenticular, cylindrical and lamellar was identified based on the heat treatment conditions. Consequently, a wide range of microhardness from 300 to 500 HV was observed due to phase transformations in the microstructure, which control the mechanical properties. The subsequent tensile tests validated the improved mechanical properties further as the tensile strength increased from 780 ± 10–1640 ± 6.29 MPa, compared to the as-printed specimens. Examination of the fracture surfaces revealed intergranular failure following aging at 500 °C due to segregation of α particles at grain boundaries. At 600 °C, the fracture was initially intergranular, which slowly transformed to a ductile fracture with time. At 700 °C, the fracture was mainly duc

关键词： Titanium alloys

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Laser powder bed fusion of difficult-to-print γ′ Ni-based superalloys: A review of processing approaches, properties, and remaining challenges

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Additive Manufacturing 2025年 106卷

作者： Enrique, Pablo D. Minasyan, Tatevik Toyserkani, Ehsan Multi-Scale Additive Manufacturing Lab Department of Mechanical and Mechatronics Engineering University of Waterloo 200 University Avenue West WaterlooONN2L 3G1 Canada

Metal additive manufacturing (AM) promises a revolution with the potential to fabricate more complex, lighter, and higher performance components while simplifying supply chains and reducing material waste. However, many of the superalloys that are critical to applications requiring superior high-temperature properties are also challenging to process using fusion-based AM. The number of publications on this topic has grown significantly in the past five years, reflecting a growing interest within industry and academia. This article reviews and discusses the challenges associated with powder bed fusion - laser beam (PBF-LB) of γ′ Ni-based superalloys and recent approaches that have enabled their processing. This includes process parameter optimization, alloy modification, and heat treatment, all of which have been shown to produce material with reduced defect density. Additionally, the properties of γ′ Ni-based superalloys made with PBF-LB and conventional (cast and wrought) processes are compared and the reasons for the observed differences are discussed. Current and future research trends are provided based on the current outstanding challenges and prevailing theories in the literature, as well as an outlook on the adoption of PBF-LB γ′ Ni-based superalloys in industry. © 2025 The Authors

关键词： Superalloys

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Nonlinear Model Predictive control for Autonomous Sailboat with Optimization of Sail Angle

Nonlinear Model Predictive Control for Autonomous Sailboat w...

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OCEANS

作者： Junzhuo Wu Ya-Jun Pan Chao Shen Sean Smith Emmanuel Witrant Department of Mechanical Engineering Advanced Control and Mechatronics Lab Dalhousie University Halifax Canada Department of Systems and Computer Engineering Carleton University Ottawa Canada GIPSA-lab Université Grenoble Alpes-CNRS Grenoble France Departement of Mechanical Engineering Dalhousie University Halifax Nova Scotia Canada

ISBN: (数字)9798331540081

ISBN: (纸本)9798331540098

This paper studies trajectory tracking control problems of sailing vessels using a nonlinear model predictive control (NMPC) approach with a novel sail angle optimization approach. The proposed sail angle optimization method accounts for physical constraints during practical implementation such as operational sail angle bound and rate of change in sail angles. This technique also emphasizes the potential to use the sail to plan a safe trajectory, while a simple proportional-derivative (PD) controller is used for rudder angle regulation. The NMPC is implemented for trajectory tracking control in the simulation. Results show that the proposed controller can achieve excellent tracking performance in the presence of environmental disturbances in terms of ocean waves.

关键词： Trajectory tracking Oceans Optimization methods Ocean waves Predictive models Regulation Trajectory PD control Predictive control

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ML-ANet:A Transfer Learning Approach Using Adaptation Network for Multi-label Image Classification in Autonomous Driving

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Chinese Journal of mechanical engineering 2021年第5期34卷 107-117页

作者： Guofa Li Zefeng Ji Yunlong Chang Shen Li Xingda Qu Dongpu Cao Institute of Human Factors and Ergonomics College of Mechatronics and Control EngineeringShenzhen UniversityShenzhen 518060China Department of Mechanical and Mechatronics Engineering University of WaterlooWaterlooON N2L 3G1Canada Interactive Entertainment Group TencentShanghai 200233China Traffic Operations and Safety Laboratory University of Wisconsin-MadisonMadisonWI 53715USA.

To reduce the discrepancy between the source and target domains,a new multi-label adaptation network(ML-ANet)based on multiple kernel variants with maximum mean discrepancies is proposed in this *** hidden representations of the task-specific layers in ML-ANet are embedded in the reproducing kernel Hilbert space(RKHS)so that the mean-embeddings of specific features in different domains could be precisely *** kernel functions are used to improve feature distribution efficiency for explicit mean embedding matching,which can further reduce domain *** weather and cross-camera adaptation examinations are conducted to verify the effectiveness of our proposed *** results show that our proposed ML-ANet achieves higher accuracies than the compared state-of-the-art methods for multi-label image classification in both the adverse weather adaptation and cross-camera adaptation *** results indicate that ML-ANet can alleviate the reliance on fully labeled training data and improve the accuracy of multi-label image classification in various domain shift scenarios.

关键词： Autonomous vehicles Deep learning Image classification Multi-label learning Transfer learning

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Bidirectional Multi-Stack RNNs with Attention for Machine Translation

Bidirectional Multi-Stack RNNs with Attention for Machine Tr...

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On-Line Conference (ONCON), Industrial Electronics Society Annual

作者： Zhiren Chen Ziyu Qiu Nuo Chen the Department of Mechanical & Industrial Engineering University of Toronto Toronto Canada Faculty of Computer Science Dalhousie University Halifax Canada Department of Mechanical Engineering Advanced Control and Mechatronics Lab Dalhousie University Halifax Canada

This project developed a novel attention algorithm for multi-stack bidirectional encoder-decoder RNN (including GRU and LSTM) sequence-to-sequence models, particularly for language translation tasks. The attention mechanism utilizes matrix rearranging and multiplication to compute the significance of the vectors in the encoder output to the vectors in the current decoder hidden states when predicting each word. Our approach achieved 98% of the performance of fine-tuned pretrained T5-small, with 30% to 50% fewer parameters depending on vocabulary size, making our model an ideal choice in cases of single-processor training, low processor resource, limited memory, small dataset, or tasks not supported by pretrained transformers.

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Experimental Study on the Influence of Surface Carbon Content on Crack Initiation for 20Cr2Ni4A Steel 152nd

Experimental Study on the Influence of Surface Carbon Conten...

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152nd Annual Meeting and Exhibition of The Minerals, Metals and Materials Society, TMS 2023

作者： Zhang, Yingtao Gong, Benxiang Guo, Yunpeng Wang, Gang Ji, Xiulin College of Mechanical and Electrical Engineering Hohai University Changzhou213022 China Inner Mongolia Fist Machinery Group Co. Ltd. Inner Mongolia Baotou014030 China Beijing Key Lab of Precision/Ultra-Precision Manufacturing Equipments and Control Tsinghua University Beijing100084 China Department of Mechatronics Engineering Shantou University Shantou515063 China

ISBN: (纸本)9783031225239

20Cr2Ni4A steel is a kind of low-carbon steel mainly used in manufacturing heavy-duty transmission gears. The carburizing and quenching process is a common strengthening method for gears to get the fine mechanical properties. For the reason of quenching deformation, grinding is used to improve tooth surface accuracy, leading to uneven distribution of surface carbon concentration. In this paper, the different carburizing processes are applied for the 20Cr2Ni4A samples. Different surface carbon content is obtained by grinding with different depths. Three-point bending fatigue test is conducted to study the relationship between crack initiation and surface carbon concentration. The crack initiation and propagation process is monitored by industrial cameras and strain gauges. The number of cycles of crack initiation is positively correlated with the surface carbon content within the range of 1%. And the carbide particles are the main fatigue source. © 2023, The Minerals, Metals & Materials Society.

关键词： Crack initiation

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Interaction-Aware Cut-In Trajectory Prediction and Risk Assessment in Mixed Traffic

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IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1752-1762页

作者： Xianglei Zhu Wen Hu Zejian Deng Jinwei Zhang Fengqing Hu Rui Zhou Keqiu Li Fei-Yue Wang the College of Intelligence and Computing Tianjin UniversityTianjin 300350 the China Automotive Technology and Research Center Co.Ltd. Tianjin 300300China the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body College of Mechanical and Vehicle EngineeringHunan UniversityChangsha 410082China the Department of Mechanical and Mechatronics Engineering University of WaterlooWaterlooON N2L3G1Canada the School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China the Macao University of Science and Technology MacaoChina the Waytous Inc. Qingdao 266000China IEEE the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Accurately predicting the trajectories of surrounding vehicles and assessing the collision risks are essential to avoid side and rear-end collisions caused by *** improve the safety of autonomous vehicles in the mixed traffic,this study proposes a cut-in prediction and risk assessment method with considering the interactions of multiple traffic *** integration of the support vector machine and Gaussian mixture model(SVM-GMM)is developed to simultaneously predict cut-in behavior and *** dimension of the input features is reduced through Chebyshev fitting to improve the training efficiency as well as the online inference *** on the predicted trajectory of the cut-in vehicle and the responsive actions of the autonomous vehicles,two risk measurements are introduced to formulate the comprehensive interaction risk through the combination of Sigmoid function and Softmax ***,the comparative analysis is performed to validate the proposed method using the naturalistic driving *** results show that the proposed method can predict the trajectory with higher precision and effectively evaluate the risk level of a cut-in maneuver compared to the methods without considering interaction.

关键词： Cut-in behavior interaction-aware mixed traffic risk assessment trajectory prediction

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A Data-Driven Distributed control Scheme: Learning Multi-Objective Agent-Based MPC for Path-Tracking

A Data-Driven Distributed Control Scheme: Learning Multi-Obj...

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International Conference on Intelligent Transportation

作者： Jiaming Zhong Reza Valiollahi Mehrizi Yash Vardhan Pant Amir Khajepour Department of Mechanical and Mechatronics Engineering Mechatronic Vehicle Systems (MVS) Lab University of Waterloo Waterloo ON Canada Department of Electrical and Computer Engineering Control Learning and Logic (CL2) group University of Waterloo Waterloo ON Canada

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

Agent-based model predictive control (AMPC) has recently been proposed for vehicle systems with various controllers, such as differential braking and torque vectoring, where controllers are regarded as distributed agents contributing to the same objective. However, this scheme is challenging in handling multiple conflicting objectives with coupled agents. A common approach for such tasks is the integrated MPC, where all objectives and agents are stacked together in one optimization. Nevertheless, as more agents and objectives are involved, the integrated MPC will face challenges like computational burdens and maintenance difficulties in practice. To this end, this paper proposes a learning multi-objective AMPC that can improve design flexibility and computing efficiency. First, under the assumption of information exchange, a multi-objective AMPC tailored from the alternating direction method of multipliers (ADMM) is proposed to decouple the system and achieve the same performance as the integrated scheme iteratively. Second, a learning-based method for initializing iterations is proposed to accelerate convergence. In addition, a data management method is proposed for real-time efficiency, and an authentication module is designed for learning reliability. We compare the proposed scheme against the integrated scheme via a combined path-tracking simulation for autonomous vehicles with various controllers. The proposed scheme achieves the same control performance as the integrated one while reducing the computational time by 43.5 %. Furthermore, the learning-based method saves 88.6% more computational time than without learning, making it suitable for real-time implementation.

关键词： Learning systems Torque Decentralized control Reliability engineering Real-time systems Convex functions Planning Information exchange Convergence Predictive control

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