检索结果-内蒙古大学图书馆

High Precision Tracking control Method Based on Model-Following control and Equivalent-Input-Disturbance 3

学校读者我要写书评

暂无评论

High Precision Tracking Control Method Based on Model-Follow...

3rd International Workshop on intelligent systems, IWIS 2023

作者： Jiang, Ruoyu She, Jinhua School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Engineering Tokyo University of Technology Tokyo192-0982 Japan

ISBN: (纸本)9798350305043

This paper presents a high-precision control method based on the model-following control (MFC) and equivalent-input-disturbance (EID) approaches. The MFC approach ensures that the output of the plant tracks the output of a desired nominal model. The EID estimates and eliminates an external disturbance. The combination of these two methods effectively achieves high-precision tracking. The validity of this method is demonstrated by a vibration-suppression example through simulations. © 2023 IEEE.

关键词： Equivalent-input-disturbance model-following control vibration suppression

Distributed Pose-graph Optimization with Multi-level Partitioning for Collaborative SLAM

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Li, Cunhao Guo, Guanghui Yi, Peng Hong, Yiguang The Department of Control Science and Engineering Tongji University Shanghai China The Department of Control Science and Engineering National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Tongji University Shanghai China

The back-end module of Distributed Collaborative Simultaneous Localization and Mapping (DCSLAM) requires solving a nonlinear Pose Graph Optimization (PGO) under a distributed setting, also known as SE(d)-synchronization. Most existing distributed graph optimization algorithms employ a simple sequential partitioning scheme, which may result in unbalanced subgraph dimensions due to the different geographic locations of each robot, and hence imposes extra communication load. Moreover, the performance of current Riemannian optimization algorithms can be further accelerated. In this letter, we propose a novel distributed pose graph optimization algorithm combining multi-level partitioning with an accelerated Riemannian optimization method. Firstly, we employ the multilevel graph partitioning algorithm to preprocess the naive pose graph to formulate a balanced optimization problem. In addition, inspired by the accelerated coordinate descent method, we devise an Improved Riemannian Block Coordinate Descent (IRBCD) algorithm and the critical point obtained is globally optimal. Finally, we evaluate the effects of four common graph partitioning approaches on the correlation of the inter-subgraphs, and discover that the Highest scheme has the best partitioning performance. Also, we implement simulations to quantitatively demonstrate that our proposed algorithm outperforms the state-of-the-art distributed pose graph optimization protocols1 Copyright © 2024, The Authors. All rights reserved.

关键词： Optimization

SCIPaD: Incorporating Spatial Clues into Unsupervised Pose-Depth Joint Learning

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Feng, Yi Guo, Zizhan Chen, Qijun Fan, Rui The Department of Control Science & Engineering The College of Electronics & Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems Shanghai Institute of Intelligent Science and Technology The State Key Laboratory of Intelligent Autonomous Systems Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai201804 China

Unsupervised monocular depth estimation frameworks have shown promising performance in autonomous driving. However, existing solutions primarily rely on a simple convolutional neural network for ego-motion recovery, which struggles to estimate precise camera poses in dynamic, complicated real-world scenarios. These inaccurately estimated camera poses can inevitably deteriorate the photometric reconstruction and mislead the depth estimation networks with wrong supervisory signals. In this article, we introduce SCIPaD, a novel approach that incorporates spatial clues for unsupervised depth-pose joint learning. Specifically, a confidence-aware feature flow estimator is proposed to acquire 2D feature positional translations and their associated confidence levels. Meanwhile, we introduce a positional clue aggregator, which integrates pseudo 3D point clouds from DepthNet and 2D feature flows into homogeneous positional representations. Finally, a hierarchical positional embedding injector is proposed to selectively inject spatial clues into semantic features for robust camera pose decoding. Extensive experiments and analyses demonstrate the superior performance of our model compared to other state-of-the-art methods. Remarkably, SCIPaD achieves a reduction of 22.2% in average translation error and 34.8% in average angular error for camera pose estimation task on the KITTI Odometry dataset. Our source code is available at https://***/SCIPaD. Copyright © 2024, The Authors. All rights reserved.

关键词： Cameras

Social Optimization in Noncooperative Games under Central Regulation

学校读者我要写书评

暂无评论

arXiv 2025年

作者： Du, Kaixin Meng, Min Li, Xiuxian Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai200092 China Department of Control Science and Engineering College of Electronics and Information Engineering The Shanghai Research Institute for Intelligent Autonomous Systems National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai China

This paper proposes a novel optimization problem building on noncooperative games under central regulation, which can be formulated as a bilevel structure. In the low-level, each player competes to minimize its own cost function that depends not only on the strategies of all players, but also on an intervention decision of the central regulator, while the central regulator located at the high-level attempts to achieve the social optimum, that is, to minimize the sum of cost functions of all players through an adjustable intervention decision. In this setting, under the intervention of the central regulator, the low-level players perform in a noncooperative game and aim to seek the Nash equilibrium, which indeed is related with the regulator’s decision. Meanwhile, the objective of the regulator is to choose a decision such that the social cost, i.e., the sum of cost functions of all players is minimum. This formulated bilevel social optimization problem is proven to be constrained, nonconvex and nonsmooth. To address this intricate problem, an inexact zeroth-order algorithm is developed by virtue of the smoothing techniques, allowing for the Nash equilibrium of the low-level game to be computed in an inexact manner. Levering the properties of smoothing techniques, it is rigorously shown that the devised algorithm achieves a sublinear convergence rate for computing a stationary point of a related optimization problem with a smoothed objective. Moreover, the sublinear convergence rate in the scenario where the exact equilibrium of the low-level game is available is also discussed. Finally, numerical simulations are conducted to demonstrate the efficiency of theoretical findings. Copyright © 2025, The Authors. All rights reserved.

关键词： Cost functions

A Soft-Sensor Modeling Method Based on Gated Stacked Isomorphic Autoencoder 41

学校读者我要写书评

暂无评论

A Soft-Sensor Modeling Method Based on Gated Stacked Isomorp...

第41届中国控制会议

作者： Jianjun Yang Xiaolu Xu Xiaohui Yin Wenxing Liu Yi Yuan Jian Peng 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 Huaxin Cement Co. Ltd

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Soft sensing mainly studies the real-time prediction of some key performance indicators or quality variables in the actual production process,which has the role of guiding production in the actual production *** stacked autoencoder is a multi-layer autoencoder *** input variables will be encoded and decoded through each layer of autoencoders,and the obtained hidden features will be retained as the input of the next *** this way,high-level data features can be successfully learned from the input layer to the intermediate *** isomorphic autoencoder reconstruct an identical data input layer,and the reconstruction is performed by minimizing the error of the decoded data from the original input ***,for a soft measurement model,some data information may also reduce the accuracy or generalization of the *** order to overcome the above shortcomings,this paper proposes a gated stacked isomorphic autoencoder,which evaluates the contribution of each hidden layer feature through the gating unit,and then integrates the information of different hidden layers to complete the prediction and estimation of related main ***,the effectiveness and feasibility of the method are verified in practical industrial cases.

关键词： Deep learning soft sensor stacked autoencoder gating unit

Online, Target-Free LiDAR-Camera Extrinsic Calibration via Cross-Modal Mask Matching

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Huang, Zhiwei Zhang, Yikang Chen, Qijun Fan, Rui The Department of Control Science & Engineering The College of Electronics & Information Engineering Shanghai Institute of Intelligent Science and Technology Shanghai Research Institute for Intelligent Autonomous Systems The State Key Laboratory of Intelligent Autonomous Systems Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai201804 China

LiDAR-camera extrinsic calibration (LCEC) is crucial for data fusion in intelligent vehicles. Offline, target-based approaches have long been the preferred choice in this field. However, they often demonstrate poor adaptability to real-world environments. This is largely because extrinsic parameters may change significantly due to moderate shocks or during extended operations in environments with vibrations. In contrast, online, target-free approaches provide greater adaptability yet typically lack robustness, primarily due to the challenges in cross-modal feature matching. Therefore, in this article, we unleash the full potential of large vision models (LVMs), which are emerging as a significant trend in the fields of computer vision and robotics, especially for embodied artificial intelligence, to achieve robust and accurate online, target-free LCEC across a variety of challenging scenarios. Our main contributions are threefold: we introduce a novel framework known as MIAS-LCEC, provide an open-source versatile calibration toolbox with an interactive visualization interface, and publish three real-world datasets captured from various indoor and outdoor environments. The cornerstone of our framework and toolbox is the cross-modal mask matching (C3M) algorithm, developed based on a state-of-the-art (SoTA) LVM and capable of generating sufficient and reliable matches. Extensive experiments conducted on these real-world datasets demonstrate the robustness of our approach and its superior performance compared to SoTA methods, particularly for the solid-state LiDARs with super-wide fields of view. Our toolbox and datasets are publicly available at ***/MIAS-LCEC. Copyright © 2024, The Authors. All rights reserved.

关键词： Cameras

Small-size temperature/high-pressure integrated sensor via flip-chip method

学校读者我要写书评

暂无评论

Microsystems & Nanoengineering 2024年第4期10卷 153-162页

作者： Mimi Huang Xiaoyu Wu Libo Zhao Xiangguang Han Yong Xia Yi Gao Zeyu Cui Cheng Zhang Xiaokai Yang Zhixia Qiao Zhikang Li Feng Han Ping Yang Zhuangde Jiang State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement TechnologiesXi’an Jiaotong UniversityXi’an 710049China Xi’an Jiaotong University(Yantai)Research Institute for Intelligent Sensing Technology and System Xi’an Jiaotong UniversityXi’an 710049China Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing Yantai 265503China School of Mechanical Engineering Xi’an Jiaotong University710049 Xi’anChina School of Instrument Science and Technology Xi’an Jiaotong University710049 Xi’anChina Chongqing Key Laboratory of Micro-Nano Systems and Intelligent Sensing Chongqing Academician WorkstationChongqing 2011 Collaborative Innovation Center of Micro/Nano Sensing and Intelligent Ecological Internet of ThingsChongqing Technology and Business UniversityNan’an DistrictChongqing 400067China Xi’an Aerospace Yuanzheng Fluid Control Co.Ltd. Xi’an 710049China

Hydraulic technology with smaller sizes and higher reliability trends,including fault prediction and intelligent control,requires high-performance temperature and pressure-integrated *** designs rely on planar wafer-or chip-level integration,which is limited by pressure range,chip size,and low *** propose a small-size temperature/high-pressure integrated sensor via the flip-chip *** pressure and temperature units are arranged vertically,and the sensing signals of the two units are integrated into one plane through silicon vias and gold–gold bonding,reducing the lateral size and improving the efficiency of signal *** flip-chip technique ensures a reliable electrical connection.A square diaphragm with rounded corners is designed and optimised with simulation to sense high pressure based on the piezoresistive *** temperature sensing unit with a thin-film platinum resistor measures temperature and provides back-end high-precision compensation,which will improve the precision of the pressure *** integrated chip is fabricated by MEMS technology and packaged to fabricate the extremely small integrated *** integrated sensor is characterised,and the pressure sensor exhibits a sensitivity and sensitivity drift of 7.97mV/MPa and−0.19%FS in the range of 0–20 MPa and−40 to 120℃.The linearity,hysteresis,repeatability,accuracy,basic error,and zero-time drift are 0.16%FS,0.04%FS,0.06%FS,0.18%FS,±0.23%FS and 0.04%FS,*** measurement error of the temperature sensor and temperature coefficient of resistance is less than±1°C and 3142.997 ppm/℃,*** integrated sensor has broad applicability in fault diagnosis and safety monitoring of high-end equipment such as automobile detection,industrial equipment,and oil drilling platforms.

关键词： size corners sizes

Synthesis of Decoherence-Free Modes in Linear Quantum Passive systems via Robust Pole Placement

学校读者我要写书评

暂无评论

Synthesis of Decoherence-Free Modes in Linear Quantum Passiv...

2024 IEEE International Conference on systems, Man, and Cybernetics, SMC 2024

作者： Miao, Zibo Pan, Yu Gao, Qing School of Mechanical Engineering and Automation Adaptive Robotics Harbin Institute of Technology Guangdong Key Laboratory of Intelligent Morphing Mechanisms Shenzhen518055 China The Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China The School of Automation Science and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China

ISBN: (纸本)9781665410205

In this paper we extend our previous research on coherent observer-based pole placement approach to study the synthesis of robust decoherence-free (DF) modes for linear quantum passive systems, which is aimed at preservation of quantum information. In particular, DF modes can be generated by placing the poles on the imaginary axis via a coherent feedback design scheme, and these modes can further be simultaneously made robust against perturbations to the system parameters by minimizing the condition number associated with imaginary poles. We develop explicit algebraic conditions for the existence of such a coherent quantum controller, with the corresponding deign procedure provided. Examples are given to illustrate the process of tuning the DF modes towards perfect robustness via the proposed pole placement technique. © 2024 IEEE.

关键词： Poles

A Test Suite and An Optimizer for Dietary Nutrition Optimization Problem: From Constrained Many-Objective Perspective

学校读者我要写书评

暂无评论

A Test Suite and An Optimizer for Dietary Nutrition Optimiza...

2023 IEEE Congress on Evolutionary Computation, CEC 2023

作者： Ti, Yaqi Li, Changhe Yang, Shengxiang 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 Computer Science and Informatics De Montfort University Leicester United Kingdom

ISBN: (纸本)9798350314588

With increasing people who suffer from diet-related diseases, providing suggestions for personal daily nutrient-dense intake is highly expected. However, current dietary nutrition models are less precise, and dietary nutrition optimizers usually fail to give satisfactory solutions. Therefore, we construct a constrained many-objective nutrition model with more precise nutrient assessments and a scalable constrained many-objective benchmark set. This test suite has great flexibility in evaluating algorithms' performance on high dimensional search and objective spaces with some feasible region fragments. We also propose a kd-tree based dynamic constrained many-objective evolutionary algorithm to search for customized food combinations according to personal daily consumption and intake preference. Experiments show that our algorithm has better diversity maintenance ability in high dimension space. © 2023 IEEE.

关键词： Nutrition