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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Yu Zhang Jie Xu Cheng Zhao Jiuxiang Dong the State Key Laboratory of Synthetical Automation for Process Industries and the Key Laboratory of Vibration and Control of Aero-Propulsion Systems Ministry of Education College of Information Science and Engineering Northeastern University Shenyang P.R. China

In this paper, we tackle the control and trajectory planning problems for the cooperative transportation system of cable-suspended payload with multi Unmanned Aerial Vehicles (UAVs). Firstly, a payload controller is presented considering the dynamic coupling between the UAV and the payload to accomplish the active suppression of payload swing and the complex payload trajectory tracking. Secondly, different from the simplification of obstacles in most approaches, we propose three Insetting Formation (IF) algorithms for the complete obstacle shape to generate collision-free waypoints for the cooperative transportation system. An IF strategy is proposed by integrating three IF algorithms to improve the success rate of obstacle avoidance and reduce the algorithm complexity for performing the aggressive flight. Finally, we verify the robustness and high performance of the proposed algorithm through benchmark comparison and real-world experiments. Moreover, our source code is released as an open-source ros package.

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Molecular Imprinted Polymer on Optical Fiber Sensor for Ethanol Vapor Biomarker Detection

Molecular Imprinted Polymer on Optical Fiber Sensor for Etha...

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IEEE SENSORS

作者： Pannathorn Jitpratak Akhilesh Kumar Pathak Kankan Swargiary Charusluk Viphavakit Department of Biomedical Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Department of Mechanical Engineering Center for Smart Structures and Materials Northwestern University Evanston IL USA Faculty of Engineering International School of Engineering (ISE) Intelligent Control Automation of Process Systems Research Unit Chulalongkorn University Bangkok Thailand

An optical fiber sensor with a single mode-multimode-single mode (SMS) structure is proposed to detect ethanol vapor ranging between 100–500 ppm via the evanescent field interaction at the interface between the optical fiber and ethanol vapor. The proposed optical fiber sensor offers real-time and non-invasive monitoring of ethanol vapor, which is one of the biomarkers of diabetes. Molecular imprinted polymer (MIP) is coated at a multimode fiber region, which is considered to be a sensing area, to improve the selectivity of the ethanol biomarker. The sensor works based on wavelength interrogation by detecting the change in wavelength due to the change in vapor concentration. The fabricated sensor has a sensitivity of 0.0013 nm/ppm, which suggests the potential to be used as a monitoring device for breath analysis.

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Consensus Robustness under PI Protocols with Undirected Graphs

Consensus Robustness under PI Protocols with Undirected Grap...

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American control Conference (ACC)

作者： Qi Mao Dan Ma Yanling Ding Hui Peng Jie Chen Department of Electrical Engineering City University of Hong Kong Hong Kong China College of Information Science and Engineering State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China School of Automation Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control Guangdong University of Technology Guangzhou China

This paper concerns robust consensus problems for continuous-time first-order multi-agent systems with respect to uncertain gain and phase of the agent’s frequency response varying within certain ranges. We consider dynamic output feedback control protocol in the form of proportional-integral (PI) control. The agents can in general be nonminimum phase and unstable systems, which are interconnected by an undirected graph network. We seek to determine the largest ranges of gain and phase variations, referred to as the gain consensus margin (GCM) and the phase consensus margin (PCM), respectively, so that consensus can be achieved robustly within these ranges. Our main results consist of explicit analytical expressions of the GCM and PCM, which demonstrate how the agent’s unstable pole and nonminimum phase zero, as well as the network connectivity may fundamentally confine the gain and phase variation ranges so that consensus can or cannot be maintained.

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Classification on point-cloud of shoe-last curvature using weight-updated boosting based ensemble learning 9

Classification on point-cloud of shoe-last curvature using w...

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9th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2020

作者： Li, Zairan Wang, Dan Tianjin University Tianjin Key Laboratory of Process Measurement and Control School of Electrical Engineering and Automation China

Optimizing the curvature shape of shoe last is an important research content and a promising direction in current shoe-last design. The emergence of plantar pressure imaging method provided a new technical mean for shoe-last design. The point-cloud dataset was acquired from the plantar pressure experiments which may be used for generating comfort shoe-last curvature, and the key zones on last curvature may be classified and has potential benefit to the designers to produce comfort shoe. In this paper ensemble learning technologies are applied for classifying those points through the proposed weights-updated algorithms. The proposed weights-updated algorithm with boosting operation performed high effectiveness by comparing to k-NN, random forest (RF) and Bayers (NB) in classification accuracy. The proposed boosting based ensemble learning method will be potential applied in interactive design of industry and be beneficial to produce comfort shoes. © 2020 IEEE.

关键词： Learning systems

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Research on Data Encryption in Lightweight Embedded Web Server 10

Research on Data Encryption in Lightweight Embedded Web Serv...

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10th International Conference on control, automation and Information Sciences, ICCAIS 2021

作者： Li, Pengfei Qu, Junsuo Shi, Haonan Xi'an University of Posts Telecommunications School of Automation Xi'an China Xi'an University of Posts Telecommunications Xi'an Key Laboratory of Advanced Control and Intelligent Process School of Automation Xi'an China Xi'an University of Posts Telecommunications School of Communication and Information Engineering Xi'an China

ISBN: (纸本)9781665440295

From the perspective of reducing the configuration complexity of IoT device parameters and improving data security, a lightweight embedded Web server is designed based on the TencentOS tiny operating system to reduce the hardware requirements of the embedded Web server design. In order to improve the security and transmission reliability of IoT monitoring data, a mechanism for data encryption is proposed. Embedded Elliptic Curve Cryptography (ECC) in Flash inside the chip to ensure the security of key data during transmission. The data monitoring platform receives and decrypts the received data, and stores the data into a database server after processing. The experimental results show that the security of data transmission and reached the expected goals. © 2021 IEEE.

关键词： Internet of things

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Cooperative Optimal Output Tracking for Discrete-Time Multiagent Systems: Stabilizing Policy Iteration Frameworks and Analysis

arXiv

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arXiv 2025年

作者： Li, Dongdong Dong, Jiuxiang College of Information Science and Engineering Northeastern University Shenyang110819 China State Key Laboratory of Synthetical Automation of Process Industries Northeastern University Shenyang110819 China Key Laboratory of Vibration and Control of Aero-Propulsion Systems Ministry of Education Northeastern University Shenyang110819 China

In this paper, two model-free optimal output tracking frameworks based on policy iteration for discrete-time multiagent systems are proposed. First, we establish a framework of stabilizing policy iteration that can start from any initial feedback control policy, relaxing the dependence of traditional policy iteration on the initial stabilizing control policy. Then, another efficient and equivalent Q-learning policy iteration framework is developed, which is shown to require only less system data to get the same results as the stabilizing policy iteration. Both frameworks obtain stabilizing control policy by iterating the stabilizing virtual closed-loop system step-by-step to the actual closed-loop system. Multiple explicit schemes for the iteration step-size/coefficient are designed and their stability during the above iterations is analyzed. By using the generated closed-loop stabilizing control policy and two frameworks, the optimal feedback control gain is obtained. The approximate solution of the regulator equations is found by model-free iteration, which leads to the optimal feedforward gain. Finally, the cooperative optimal output tracking is realized by a distributed feedforward-feedback controller. The proposed algorithms are validated by simulation. Copyright © 2025, The Authors. All rights reserved.

关键词： Feedback control

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Reduced Network Cumulative Constraint Violation for Distributed Bandit Convex Optimization under Slater’s Condition

arXiv

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arXiv 2024年

作者： Zhang, Kunpeng Yi, Xinlei Ding, Jinliang Cao, Ming Johansson, Karl H. Yang, Tao State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai201800 China Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen GroningenAG 9747 Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper studies the distributed bandit convex optimization problem with time-varying inequality constraints, where the goal is to minimize network regret and cumulative constraint violation. To calculate network cumulative constraint violation, existing distributed bandit online algorithms solving this problem directly use the clipped constraint function to replace its original constraint function. However, the use of the clipping operation renders Slater’s condition (i.e, there exists a point that strictly satisfies the inequality constraints at all iterations) ineffective to achieve reduced network cumulative constraint violation. To tackle this challenge, we propose a new distributed bandit online primal–dual algorithm. If local loss functions are convex, we show that the proposed algorithm establishes an O(T max{c,1−c})network regret bound and an O(T 1−c/2) network cumulative constraint violation bound, where T is the total number of iterations and c ∈ (0, 1) is a user-defined trade-off parameter. When Slater’s condition holds, the network cumulative constraint violation bound is reduced to O(T 1−c). In addition, if local loss functions are strongly convex, for the case where strongly convex parameters are unknown, the network regret bound is reduced to O(T1−c), and the network cumulative constraint violation bound is O(T1−c/2) and O(T1−c) without and with Slater’s condition, respectively. For the case where strongly convex parameters are known, the network regret bound is further reduced to O)(log(T)), and the network cumulative constraint violation bound is reduced to O(log(T)T) and O(log(T)) without and with Slater’s condition, respectively. To the best of our knowledge, this paper is among the first to establish reduced (network) cumulative constraint violation bounds for (distributed) bandit convex optimization with time-varying constraints under Slater’s condition. Finally, a numerical example is provided to verify the theoretical results. Copyright © 2

关键词： Convex optimization

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Q-Learing-Based Multi-Rate Optimal control and Its Application

Q-Learing-Based Multi-Rate Optimal Control and Its Applicati...

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Chinese control and Decision Conference, CCDC

作者： Zhenxing Xia Wei Dai School of Information and Control Engineering China University of Mining and Technology Xuzhou State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China

ISBN: (纸本)9781665478977

In this paper, adaptive dynamic programming (ADP) algorithm, with lifting technology, is develop to solve the multi-rate optimal control problem for discrete-time linear systems. We make use of the lifting technology to convert the multi-rate sample control problem to the single-rate one in the uniform cycle. The propose a Q-Leaming based approach to learn the optimal regulator by a value iteration (VI) algorithm. First, a class of continuous-time (CT) linear system with multi-timescale is considered. Then, the convergence of a Q-Learning based algorithm is given. It is proven that the iterative cost function precisely converges to the optimal value, and the control input also converges to the optimal values. Finally, HIL system for grinding process is given to illustrate the effective performance of the proposed method.

关键词： Linear systems Regulators Q-learning System dynamics Heuristic algorithms Optimal control process control

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An Improved Cooperative Team Spraying control of a Diffusion process With a Moving or Static Pollution Source

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IEEE/CAA Journal of Automatica Sinica 2020年第2期7卷 494-504页

作者： Juan Chen Baotong Cui Yang Quan Chen Bo Zhuang Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education)and School of IoT Engineering Jiangnan UniversityWuxi 214122China Mechatronics Embedded Systems and Automation LaboratoryUniversity of CaliforniaMerced CA 95343 USA

This paper is concerned with a control problem of a diffusion process with the help of static mesh sensor networks in a certain region of interest and a team of networked mobile actuators carrying chemical *** major contribution of this paper can be divided into three parts:the first is the construction of a cyber-physical system framework based on centroidal Voronoi tessellations(CVTs),the second is the convergence analysis of the actuators location,and the last is a novel proportional integral(PI)control method for actuator motion planning and neutralizing control(e.g.,spraying)of a diffusion process with a moving or static pollution source,which is more effective than a proportional(P)control *** optimal spraying control cost function is ***,the minimization problem of the spraying amount is ***,a new CVT algorithm based on the novel PI control method,henceforth called PI-CVT algorithm,is introduced together with the convergence analysis of the actuators location via a PI control ***,a modified simulation platform called diffusion-mobile-actuators-sensors-2-dimension-proportional integral derivative(Diff-MAS2D-PID)is *** addition,a numerical simulation example for the diffusion process is presented to verify the effectiveness of our proposed controllers.

关键词： Centroidal Voronoi tessellations(CVTs) diffusion processes mobile actuator-sensor networks(MAS-Net) PI control

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Stealthy False Data Injection Attacks in Multi-Channel Vehicular Communication: White-Box and Gray-Box Strategies

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IEEE Transactions on Vehicular Technology 2025年

作者： Xu, Chongcong Zheng, Fangfang Guo, Ge Southwest Jiaotong University School of Transportation and Logistics Chengdu611756 China Southwest Jiaotong University National Engineering Laboratory of Integrated Transportation Big Data Application Technology National United Engineering Laboratory of Integrated and Intelligent Transportation Chengdu611756 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China Northeastern University at Qinhuangdao School of Control Engineering Qinhuangdao066004 China

Understanding the vulnerabilities of vehicular networks from an attacker's perspective is crucial for identifying stealthy false data injection (FDI) attacks and developing robust defense methods. This paper investigates stealthy FDI attacks in multi-channel vehicular communication systems. We construct a multi-source state estimation system using a sequential Kalman filter to integrate and estimate redundant state information transmitted by preceding vehicles across multiple channels. To enhance the system's resilience against FDI attacks, we incorporate a Sage-Husa adaptive filter and a chi-squared detector, which dynamically estimate and detect channel noise based on estimation errors. Within this framework, we utilize real-time state information and channel transmission residual to determine the probability of an attack window occurring. The attack process is divided into three phases, during which critical noise disturbances are introduced to create attack windows, allowing the attack to progressively align with the target state. Based on this analysis, we develop an optimization model for attack generation with complete channel information (AG-with-CCI) to facilitate a white-box attack. Additionally, acknowledging that attackers may not have access to real-time information from all channels, we analyze the iterative equations of state estimation errors and residuals to establish the conditions under which stealthy FDI attacks can be successfully executed, enabling the attack generation with attacked channel information (AG-with-ACI) to achieve a gray-box attack. Numerical simulations demonstrate that both attack methods can evade current detection mechanisms and achieve their intended objectives. © 2025 IEEE.

关键词： Adaptive filtering

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