IFAC-PapersOnLine最新文献_第7页

Application of Speed Prediction Based on Gaussian Process Regression to the Airfoil Sail VLCC 基于高斯过程回归的速度预测在翼型风帆VLCC中的应用

IFAC-PapersOnLine Pub Date : 2025-01-01 Epub Date: 2025-12-04 DOI: 10.1016/j.ifacol.2025.11.637

Zeping Liu , Ziteng Huo , Yufu Gao , Yi Guo , Shenghai Wang , Guangdong Han

引用次数: 0

Low Visibility Enhancement for Intelligent Marine Vehicles in Hazy Environments⁎ 雾霾环境下智能船舶低能见度增强方法研究

IFAC-PapersOnLine Pub Date : 2025-01-01 Epub Date: 2025-12-04 DOI: 10.1016/j.ifacol.2025.11.623

Shumin Fan , Ning Wang , Tianyu Song

{"title":"Low Visibility Enhancement for Intelligent Marine Vehicles in Hazy Environments⁎","authors":"Shumin Fan , Ning Wang , Tianyu Song","doi":"10.1016/j.ifacol.2025.11.623","DOIUrl":"10.1016/j.ifacol.2025.11.623","url":null,"abstract":"<div><div>Visible-light vision sensors have emerged as a cost-effective and easily deployable solution for enhancing marine vessel navigation safety. However, their effectiveness is substantially compromised in hazy marine environments, where captured images often exhibit severe contrast reduction, color distortion, and interference from sea surface waves and specular reflections. These degradation effects collectively impair visual perception accuracy and range, posing risks to navigational safety. To address these challenges, this paper proposes MDNet, a Maritime Dehazing Network designed to improve visual clarity for maritime vehicles in low-visibility hazy conditions. The MDNet framework integrates two core components: a Multi-receptive-field feature enhancement block (MFEB) and a multi-expert collaborative interaction block (MCIB). The MFEB leverages parallel multi-branch processing to perform multi-scale feature extraction, enabling the network to simultaneously capture global contextual information and fine-grained texture details. The MCIB further enhances adaptability by dynamically selecting optimal expert modules tailored to learn degradation features at different network depths, thereby effectively modulating multi-granularity contextual information in degraded images. Extensive experiments validate that MDNet achieves state-of-the-art performance, outperforming existing methods in both quantitative metrics and qualitative visual assessments. Additionally, the proposed method demonstrates practical utility by significantly boosting the accuracy and reliability of target detection in hazy marine scenarios, thereby advancing the safety and stability of autonomous navigation systems.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 22","pages":"Pages 148-153"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145665681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Multi-Output Regression-Based Method for Predicting Structural Responses of Deepwater Jacket Platforms 基于多输出回归的深水导管架平台结构响应预测方法

IFAC-PapersOnLine Pub Date : 2025-01-01 Epub Date: 2025-12-04 DOI: 10.1016/j.ifacol.2025.11.644

Ren Mengyao , Su Xin , Zhang Qi

{"title":"A Multi-Output Regression-Based Method for Predicting Structural Responses of Deepwater Jacket Platforms","authors":"Ren Mengyao , Su Xin , Zhang Qi","doi":"10.1016/j.ifacol.2025.11.644","DOIUrl":"10.1016/j.ifacol.2025.11.644","url":null,"abstract":"<div><div>In real-world engineering scenarios, deep-water jacket platforms are exposed to complex, varying loads— including tension and bending—resulting from the combined actions of waves, currents, and wind. These conditions can induce structural damage and potentially compromise the integrity of the platform. This study establishes a data foundation for further analysis by utilizing the dynamic response data collected from an actual platform and applies a multi-output regression modeling approach. Six representative environmental parameters—wind speed, wind direction, current speed, current direction, significant wave height, and peak period—are selected as input features. A K-Nearest Neighbors (KNN) algorithm is employed to construct the mapping relationship between environmental conditions and structural responses. Subsequently, a multi-output regression model is developed to predict the mechanical response of the platform based on marine environmental inputs. This method effectively addresses the high computational cost associated with traditional numerical analysis, overcomes the limitations of single-output prediction models, and enhances both prediction accuracy and efficiency, thereby contributing to the safe operation of offshore platforms.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 22","pages":"Pages 271-276"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145665685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Construction of Motion Planning and Control System for UVMS Manipulator Based on MoveIt 基于MoveIt的UVMS机械手运动规划与控制系统的构建

IFAC-PapersOnLine Pub Date : 2025-01-01 Epub Date: 2025-12-04 DOI: 10.1016/j.ifacol.2025.11.648

Chao Zhu, Deda Kong, Shouxu Zhang, Yang Zhao, Xiaoxu Liu

引用次数: 0

Underactuated unmanned underwater vehicle speed adaptive cooperative allocation control 欠驱动无人潜航器速度自适应协同分配控制

IFAC-PapersOnLine Pub Date : 2025-01-01 Epub Date: 2025-12-04 DOI: 10.1016/j.ifacol.2025.11.651

Xinwei Cuan , Andong Wang , Heng Guo , Yuhao Hu , Shaolong Yang , Gang Wan , Xinyu Li

{"title":"Underactuated unmanned underwater vehicle speed adaptive cooperative allocation control","authors":"Xinwei Cuan , Andong Wang , Heng Guo , Yuhao Hu , Shaolong Yang , Gang Wan , Xinyu Li","doi":"10.1016/j.ifacol.2025.11.651","DOIUrl":"10.1016/j.ifacol.2025.11.651","url":null,"abstract":"<div><div>To address the inherent limitations of Underactuated underwater unmanned underwater vehicles (AUVs) in terms of rudder efficiency degradation at low speeds and high energy consumption of transverse thrusters, this paper proposes a speed-adaptive collaborative control framework that dynamically allocates steering torque between the rudder and thrusters based on the real-time speed and environmental disturbances. The core innovation lies in a control architecture that mixes selfdisturbance control (ADRC) with an enhanced Sigmoid-based allocation strategy. A dynamic speed threshold adjustment mechanism is designed to adaptively augment thruster actuation in the event of persistent heading errors and rudder inefficiency, ensuring fast response in critical situations. Finally, it is verified through the lake test experiment that the lateral error of AUV is always controlled less than 0.2m at 2 knots of navigation speed, and the average heading error is no more than 0.85% when the AUV is carried out at variable navigation speed. The test proves that this method effectively solves the problem of synergistic optimization of low-speed and high-speed maneuverability and energy efficiency of underdriven UUVs.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 22","pages":"Pages 313-317"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145665703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mobile Robot Exploration Without Maps via Out-of-Distribution Deep Reinforcement Learning 基于分布外深度强化学习的无地图移动机器人探索

IFAC-PapersOnLine Pub Date : 2025-01-01 Epub Date: 2025-12-22 DOI: 10.1016/j.ifacol.2025.12.292

Shathushan Sivashangaran , Apoorva Khairnar , Azim Eskandarian

{"title":"Mobile Robot Exploration Without Maps via Out-of-Distribution Deep Reinforcement Learning","authors":"Shathushan Sivashangaran , Apoorva Khairnar , Azim Eskandarian","doi":"10.1016/j.ifacol.2025.12.292","DOIUrl":"10.1016/j.ifacol.2025.12.292","url":null,"abstract":"<div><div>Autonomous Mobile Robot (AMR) navigation in dynamic environments that may be GPS denied, without a-priori maps, is an unsolved problem with potential to improve humanity’s capabilities. Conventional modular methods are computationally inefficient, and require explicit feature extraction and engineering that inhibit generalization and deployment at scale. We present an Out-of-Distribution (OOD) Deep Reinforcement Learning (DRL) approach that includes functionality in unstructured terrain and dynamic obstacle avoidance capabilities. We leverage accelerated simulation training in a racetrack with a transition probability to parameterize spatial reasoning with intrinsic exploratory behavior, in a compact, computationally efficient Artificial Neural Network (ANN), which we transfer zero-shot with a reward component to mitigate differences between simulation and real world physics. Our approach enables utility without a separate high-level planner or real-time cartography and utilizes a fraction of the computation resources of modular methods, enabling execution in a range of AMRs with different embedded computer payloads.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 30","pages":"Pages 533-538"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145801840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive Algebraic Derivative Estimation for Battery Electric Buses Energy Consumption Forecasting⁎ 基于自适应代数导数估计的纯电动客车能耗预测方法

IFAC-PapersOnLine Pub Date : 2025-01-01 Epub Date: 2025-12-22 DOI: 10.1016/j.ifacol.2025.12.248

Tianyang Cui , Muhammad Waleed Khan , Ruixiao Sun , Guanhao Xu , Zejiang Wang

引用次数: 0

Emotion-Inspired Control for MPPT and Power Factor Correction in a Photovoltaic Converter System Connected to a Three-Phase AC Grid 与三相交流电网连接的光伏变流器系统中MPPT的情感激励控制及功率因数校正

IFAC-PapersOnLine Pub Date : 2025-01-01 Epub Date: 2025-12-22 DOI: 10.1016/j.ifacol.2025.12.275

Rasoul Milasi

引用次数: 0

Closed-Loop Active-Isolated Hamstring Stretching with an Electric Motor and FES 用电动马达和FES进行闭环主动隔离腿筋拉伸

IFAC-PapersOnLine Pub Date : 2025-01-01 Epub Date: 2025-12-22 DOI: 10.1016/j.ifacol.2025.12.226

Steven Evangelos , Nicholas Rubino , Victor H. Duenas

{"title":"Closed-Loop Active-Isolated Hamstring Stretching with an Electric Motor and FES","authors":"Steven Evangelos , Nicholas Rubino , Victor H. Duenas","doi":"10.1016/j.ifacol.2025.12.226","DOIUrl":"10.1016/j.ifacol.2025.12.226","url":null,"abstract":"<div><div>Hamstring spasticity in people with spinal cord injury (SCI) causes severe lower limb dysfunction. Static stretching is a primary treatment for spasticity. Active-Isolated stretching (AIS) is an effective strategy in rehabilitation and exercise science for reducing tension in overactive (i.e., spastic) muscles and improving range of motion (ROM). AIS is a more efficient lengthening technique due to its ability to bypass the myotactic (i.e., shortening) reflex that static stretching is subject to. Motivated to expand the scope of care for people with SCI, this paper develops novel closed-loop nonlinear controllers to facilitate AIS of the hamstrings. A robust electric motor kinematic controller is developed to move the leg from its initial supine position to the target end ROM by maintaining the leg within a kinematic range. When the leg reaches the end ROM, functional electrical stimulation (FES) is applied to the quadriceps to reciprocally inhibit (i.e., lengthen) the hamstrings, per AIS protocol. A custom FES controller tracks a desired active muscle torque using feedback from a load cell. An experiment was conducted to demonstrate safe control of AIS. A Lyapunov-based stability analysis is developed to guarantee exponential tracking of the motor and FES control loops. An output strictly passive condition is used to examine the influence of the FES-induced torque on the motor closed-loop error system when the leg is at the end ROM and both controllers are active.</div></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"59 30","pages":"Pages 138-143"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145801910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Discrete-time Two-Layered Forgetting RLS Identification under Finite Excitation⁎ 有限激励下的离散时间两层遗忘RLS辨识

IFAC-PapersOnLine Pub Date : 2025-01-01 Epub Date: 2025-12-22 DOI: 10.1016/j.ifacol.2025.12.220

Satoshi Tsuruhara , Kazuhisa Ito

引用次数: 0