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5th IEEE International Conference on Electronic information and Communication Technology, ICEICT 2022

作者： Hadi, Abdul Huang, Xinqi Ali, Burhan Li, Yingsong College of Information and Communications Engineering Harbin Engineering University Harbin150001 China College of Intelligent System and Control Science Engineering Harbin Engineering University Harbin150001 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui Hefei China

ISBN: (数字)9781665472111

ISBN: (纸本)9781665472111

Two sparse adaptive filtering (AF) algorithms based on Andrew's sine estimator (ASE) are presented to achieve improved performance for identifying sparse systems, where the ASE is derived within the least-square framework. Furthermore, zero-attracting (ZA) scheme is used in ASE to construct ZA-ASE and its re-weighting form (RZA-ASE) to combat non-Gaussian noises and use the sparse characteristics of the system. Their performance is investigated via simulations and compared with the least-mean square (LMS) and the maximum correntropy criterion (MCC) algorithms to show their superior performance. © 2022 IEEE.

关键词： Adaptive filtering

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Group Cooperation in Intergroup Conflicting Networks: An Evolutionary Game Approach

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IFAC-PapersOnLine 2023年第2期56卷 3459-3464页

作者： Aixin Liu Lin Wang Guanrong Chen Jing Wu Xinping Guan Department of Automation Shanghai Jiao Tong University Shanghai 200240 China Department of Electrical Engineering City University of Hong Kong Hong Kong China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China

Most intergroup conflicts arise from rivalry over limited resources, malicious disturbance, or hostile attitudes; therefore, it is critical to investigate individuals’ behaviors involved in intergroup conflicting contexts. Focusing on cooperation issues among individuals, in this study we establish an evolutionary game framework for analyzing cooperation and conflicts that arise within and inter-groups of intergroup conflicting networks. We first model the intergroup conflicting networked evolutionary games (ICNEGs). Then, we analyze the ICNEGs and prove that the evolution of ICNEGs can be expressed as a logical dynamic system. Finally, we apply the obtained results to a simplified Israeli-Palestinian conflict scenario. Our case study demonstrates that only by adopting suitable initial strategy profiles can a certain scale of group cooperation be continuously generated without suffering casualties.

关键词： Coupled networks intergroup conflicting cooperation evolutionary game approach

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Self-supervised Multi-frame Monocular Depth Estimation with Pseudo-LiDAR Pose Enhancement

Self-supervised Multi-frame Monocular Depth Estimation with ...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Wenhua Wu Guangming Wang Jiquan Zhong Hesheng Wang Zhe Liu MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University Shanghai China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Insititute of Medical Robotics Shanghai Jiao Tong University Shanghai China

Depth estimation is one of the most important tasks in scene understanding. In the existing joint self-supervised learning approaches of depth-pose estimation, depth estimation and pose estimation networks are independent of each other. They only use the adjacent image frames for pose estimation and lack the use of the estimated geometric information. To enhance the depth-pose association, we propose a monocular multi-frame unsupervised depth estimation framework, named PLPE-Depth. There are a depth estimation network and two pose estimation networks with image input and pseudo-LiDAR input. The main idea of our approach is to use the pseudo-LiDAR reconstructed from the depth map to estimate the pose of adjacent frames. We propose depth re-estimation with a better pose between the image pose and the pseudo-LiDAR pose to improve the accuracy of estimation. Besides, we improve the reconstruction loss and design a pseudo-LiDAR pose enhancement loss to facilitate the joint learning. Our approach enhances the use of the estimated depth information and strengthens the coupling between depth estimation and pose estimation. Experiments on the KITTI dataset show that our depth estimation achieves state-of-the-art performance at low resolution. Our source codes will be released on https://***/IRMVLabIPLPE-Depth.

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Switched High-Gain Based Interval Observer Design for Harmonic Oscillator system 42

Switched High-Gain Based Interval Observer Design for Harmon...

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42nd Chinese control Conference, CCC 2023

作者： Ming, Tianhang Wang, Xiaoling Liu, Bo Su, Housheng College of Automation & Ai Nanjing University of Posts and Telecommunications Nanjing210023 China Nanjing210023 China College of Information Engineering Minzu University of China Beijing100081 China Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligence Control of Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581543

In this paper, we revisit the interval observer design problem of harmonic oscillator system with unknown but bounded external disturbance and measurement noise. With the bounding information of the external disturbance and measurement noise, a high-gain interval observer is firstly defined and constructed for the harmonic oscillator system to realize the interval estimation on the state and the robust control of the system. Then, a switched high-gain interval observer is proposed to reduce the influence of the measurement noise for a tighter interval width on the state estimation. Finally, some numerical simulations are given to verify the theoretical results. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Robust control

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Remote Sensing Image Object Detection Based on Improved Sparse R-CNN

Journal of Network Intelligence

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Journal of Network Intelligence 2023年第4期8卷 1303-1320页

作者： Zhao, Li-Quan Chen, Chun-Lu Zhong, Tie Cui, Ying Jia, Yan-Fei Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin 132012 China School of Electric Power Engineering Northeast Electric Power University Jilin 132012 China Zhuhai Power Supply Bureau Guangdong Electric Power Corporation Zhuhai 519000 China School of Electrical and Information Engineering Beihua University Jilin 132013 China

A more precise sparse region convolutional neural network algorithm is developed to increase the accuracy of remote sensing object recognition. Firstly, a new intersection over union method is proposed to solve the problem that the intersection over union used in sparse region convolutional neural network cannot well measure the offset between the ground-truth box and the proposal box. It introduces multiple geo-metric factors that are overlap area, center point distance, vertex distance between the ground-truth box and the proposal box, and diagonal distance of minimum enclosing of the ground-truth box and the proposal box and into the new intersection over union. The proposed intersection over union can measure the offset between the ground-truth box and the proposal box to optimal the proposal box. Secondly, to improve the detection precision of sparse region convolutional neural network, a dual branches dynamic instance interaction head is designed. The proposed dynamic interaction head consists of a fully connected branch and a convolution branch. The fully connected head is used for both bounding box regression and object classification. The convolution branch is only used for bounding box regression. Compared with original sparse region convolutional neural network, the average mAP and recall are 3.55% and 5.75% higher, and the average detection speed is only 0.85 FPS slower. The proposed method realizes balance between detection precision and detection speed. © 2023, Taiwan Ubiquitous information CO LTD. All rights reserved.

关键词： Remote sensing

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Towards Efficient Path Finding and Moving Stability-Focused Trajectory Planning for Mobile Robots

Towards Efficient Path Finding and Moving Stability-Focused ...

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IEEE International Conference on Robotics and Biomimetics

作者： Muyang Hou Zhenya Lei Haidong Hu Zhong Wang Yong Wang Le Xie Hesheng Wang Department of Automation Shanghai Jiao Tong University Shanghai China School of Information and Control Engineering China University of Mining and Technology Xuzhou China Beijing Institute of Control Engineering Beijing China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Nowadays, mobile robots play an important role in a variety of service scenarios. They need to plan and track trajectories to accomplish tasks such as delivery or guided tours. In such tasks, there are two remaining challenges: on one hand, the time and memory consumption of present path planners are still significant; on the other hand, service robots, which have a higher center of gravity, demand greater moving stability than that of current trajectory planners provide. To address these two challenges. Firstly, we propose a safety boundary first A* which fully utilizes environmental obstacle information to create a safety boundary and searches in it to quickly find an initial path. Secondly, we formulate the trajectory optimization problem as a nonlinear optimization problem, where the smoothness, safety, feasibility, and moving stability of the robot are taken into account. Furthermore, to constrain the robot's lateral acceleration, we design a time allocation algorithm based on non-uniform B-spline, enhancing the quality of the resulting trajectory. Simulations and real-world experiments demonstrate that our algorithms significantly improve path search efficiency, enhance moving stability, reduce the difficulty of tracking, and improve the quality of task completion.

关键词： Hands Trajectory tracking Trajectory planning Service robots Stability analysis Safety Mobile robots Resource management Splines (mathematics) Trajectory optimization

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Stability Analysis of Boolean Networks: Exploring the Influence of Multi-bit Function Perturbations

Stability Analysis of Boolean Networks: Exploring the Influe...

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IEEE Conference on Decision and control

作者： Aixin Liu Lin Wang Guanrong Chen Xinping Guan Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Department of Electrical Engineering City University of Hong Kong Hong Kong SAR China

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This study investigates the impact of multi-bit function perturbations (MFPs) on the steady-state distribution of Boolean networks (BNs), with a focus on robust stability. First, the algebraic formulation of BNs under MFPs is introduced. Then, a novel stability criterion is proposed, demonstrating that monotonically decreasing perturbations can effectively ensure the stability of BNs against MFPs. A significant advantage of this approach is that it enables robust stability assessment without remodeling the perturbed BNs. Applying this methodology to a simplified Boolean model of the lactose operon in Escherichia coli reveals that MFPs can serve as strategic tools to promote stability within BNs, rather than being merely disruptive.

关键词： Adaptation models Robust stability Perturbation methods Stability criteria Escherichia coli Robustness Steady-state Convergence

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Optimal control in Both Steady State and Transient Process with Unknown Disturbances

arXiv

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arXiv 2024年

作者： Li, Ming Wang, Zhaojian Liu, Feng Cao, Ming Yang, Bo The Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai Jiao Tong University Shanghai200240 China The State Key Laboratory of Power System The Department of Electrical Engineering Tsinghua University Beijing100084 China The Institute of Engineering and Technology University of Groningen Groningen9747 AG Netherlands

The scheme of online optimization as a feedback controller is widely used to steer the states of a physical system to the optimal solution of a predefined optimization problem. Such methods focus on regulating the physical states to the optimal solution in the steady state, without considering the performance during the transient process. In this paper, we simultaneously consider the performance in both the steady state and the transient process of a linear time-invariant system with unknown disturbances. The performance of the transient process is illustrated by the concept of overtaking optimality. An overtaking optimal controller with known disturbances is derived to achieve the transient overtaking optimality while guaranteeing steady-state performance. Then, we propose a disturbance independent near-optimal controller, which can achieve optimal steady-state performance and approach the overtaking optimal performance in the transient process. The system performance gap between the overtaking optimal controller and the proposed controller proves to be inversely proportional to the control gains. A case study on a power system with four buses is used to validate the effectiveness of the two controllers. © 2024, CC BY.

关键词： Electromagnetic transients

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Cross-Modal Registration Using Adaptive Modeling in Infrastructure-based Vehicle Localization*

Cross-Modal Registration Using Adaptive Modeling in Infrastr...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Fei Wang Yuesheng He Hanyang Zhuang Chenxi Yang Ming Yang Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University China University of Michigan - Shanghai Jiao Tong University Joint Institute. Shanghai Jiao Tong University China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Infrastructure-based vehicle localization, in comparison to single-agent approaches, offers several advantages including reduced system cost, extended perception range, enhanced data fusion capabilities, and energy savings. Many conventional approaches impose limitations on the types of objects due to the need for specific object-end modifications, such as applying perceptual markers like color-labeled plates and reflective balls. LiDAR presents a solution in terms of object arbitrariness, as it addresses the challenges of feature-free object modeling and continuous registration. However, achieving complete environmental coverage with LiDAR remains prohibitively expensive, particularly in extensive areas. Hence, this study proposes a cross-modal localization approach using adaptive modeling, employing LiDAR for object modeling and cost-effective sensor cameras for object tracking through image-point-cloud registration. Accurate correspondence between the model and observation can be estimated in real-time. The experiments are conducted in a typical scenario that requires adaptive modeling: Autonomous Valet Parking (AVP). Results demonstrate that the proposed system achieves comparable performance with significantly reduced system costs, highlighting its potential for large-scale deployment.

关键词： Location awareness Adaptation models Accuracy Laser radar Costs Remotely guided vehicles Robot vision systems

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Data-Driven Distributionally Robust Mixed-Integer control through Lifted control Policy

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IEEE Transactions on Automatic control 2025年

作者： Ma, Xutao Ning, Chao Du, Wenli Shi, Yang Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education Shanghai200237 China University of Victoria Department of Mechanical Engineering VictoriaBCV8W 3P6 Canada

This paper investigates the finite-horizon distributionally robust mixed-integer control (DRMIC) of uncertain linear systems. However, deriving an optimal causal feedback control policy to this DRMIC problem is computationally formidable for most ambiguity sets. To address the computational challenge, we propose a novel distributionally robust lifted control policy (DR-LCP) method to derive a high-quality approximate solution to this DRMIC problem for a rich class of Wasserstein metric-based ambiguity sets, including the Wasserstein ambiguity set and its variants. In theory, we analyze the asymptotic performance and establish a tight non-asymptotic bound of the proposed method. In numerical experiments, the proposed DR-LCP method empirically demonstrates superior performance compared with existing methods in the literature. ©1963-2012 IEEE.

关键词： Mixed-integer linear programming

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