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2021 International Automatic control Conference, CACS 2021

作者： Changsila, Yanita Banjerdpongchai, David Intelligent Control Automation of Process Systems Research Unit Dept. of Electrical Engineering Faculty of Engineering Chulalongkorn University 254 Phayathai Road Pathumwan Bangkok10330 Thailand

ISBN: (纸本)9781665444125

The operation of most wastewater treatment systems is an open-loop system. There is limited feedback control of membrane bioreactors (MBR) which makes it impossible to regulate the quality of the treated water. The objectives of this paper are twofold. First, we analyze the equilibrium point of the MBR nonlinear model. Second, we utilize output feedback control with state observer and design optimal PID controllers. We determine the optimum equilibrium point and derive a linearized model of MBR. Then, we design the state observer to estimate the non-measurable state using the pole placement method. Both the measurable output and estimated state are fed back through PID controller. The objectives of PID control consist of stabilization and performance improvement. Genetic Algorithm is applied to find the optimal PID parameters that minimize the integral of absolute error and satisfy the specified time-domain criteria. We apply the observer-based PID controller to the linearized model of MBR. Numerical results demonstrate the design of PID controller and the improvement of the closed-loop response and quality of the treated water. © 2021 IEEE

关键词： Bioreactors

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Event-Triggered Cooperative Adaptive Cruise control of Vehicular Platoons*

Event-Triggered Cooperative Adaptive Cruise Control of Vehic...

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IEEE Conference on Decision and control

作者： Fuyu Zhao Weinan Gao Tengfei Liu Zhong-Ping Jiang School of Electrical and Electronic Engineering Nanyang Technological University Singapore State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang Liaoning China Department of Electrical and Computer Engineering Tandon School of Engineering New York University Brooklyn NY USA

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This paper presents a novel policy iteration (PI) based event-triggered cooperative adaptive cruise control (CACC) approach for vehicular platoons, which are composed of autonomous vehicles. An observer is established to observe the signal of leading vehicle. To reduce computation and communication resources, event-triggered based adaptive optimal controllers are designed by using the PI algorithm without relying on the knowledge of system dynamics. Sufficient conditions are introduced to achieve the leader-to-formation stability (LFS) of the vehicular platoons. Simulation results are presented to verify the effectiveness of the proposed design.

关键词： Sufficient conditions Event detection System dynamics Simulation Heuristic algorithms Optimal control Observers Stability analysis Vehicle dynamics Cruise control

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Supervised Dynamic Latent Variable Models for Fault Identification in Dynamic processes

Supervised Dynamic Latent Variable Models for Fault Identifi...

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2021 CAA Symposium on Fault Detection, Supervision, and Safety for Technical processes, SAFEprocess 2021

作者： Niu, Qiqi Shen, Chengkai Lyu, Yuting Liu, Yi Zhou, Le Zhejiang University of Science Technology School of Automation and Electrical Engineering Zhejiang Hangzhou China Institute of Process Equipment and Control Engineering Zhejiang University of Technology Zhejiang Hangzhou China

ISBN: (纸本)9781665401159

With an increasing application of the multivariate statistical process monitoring method, the fault identification becomes more and more crucial after the fault detection, which is benefited to fault troubleshooting effectively and quickly. To deal with the dynamic process and the impact of random noise on fault identification, a novel fault identification method based on supervised autoregressive dynamic latent variable is proposed in this paper. After the fault label structure is added on the unsupervised model, the relationship between fault information and dynamic latent feature is strengthened. Then, the fault cause is determined based on the fault relevance method. Finally, the validity of method is verified by a numerical example and an actual wastewater treatment case. © 2021 IEEE.

关键词： Fault detection

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Design of indirect-type iterative learning control for continuous-time batch processes with the repetitive process setting

Design of indirect-type iterative learning control for conti...

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Asian control Conference

作者： Robert Maniarski Wojciech Paszke Hongfeng Tao Zhihe Zhuang Institute of Automation Electronic and Electrical Engineering University of Zielona Zielona Góra Poland Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Jiangnan University Wuxi China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

An indirect iterative learning control law is proposed for a class of continuous-time batch processes with time-varying uncertainties, input delay, and disturbances. First, by designing a predictor based on a state observer we are able to estimate the future state and compensate for the input delay. Then, based on the estimated state we design a robust $H$ ∞ controller in the presence of time-varying uncertainties and load disturbances. Additionally, the differential repetitive process setting for the design of the iterative learning control scheme is applied and hence the convergence of the tracking error in trial-to-trial direction occurs. Finally, the simulation results verify the new method's effectiveness.

关键词： Uncertainty Simulation Batch production systems process control Observers Delays Iterative learning control

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Deep Learning-Based Prediction of Subsurface Oil Reservoir Pressure Using Spatio-Temporal Data 49

Deep Learning-Based Prediction of Subsurface Oil Reservoir P...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Cheng, Haibo He, Yunpeng Zeng, Peng Li, Shichao Vyatkin, Valeriy Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang China Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Luleå University of Technology Department of Computer Science Electrical and Space Engineering Luleå Sweden Aalto University Department of Electrical Engineering and Automation Helsinki Finland

ISBN: (纸本)9798350331820

Prediction of subsurface oil reservoir pressure are critical to hydrocarbon production. However, the accurate pressure estimation faces great challenges due to the complexity and uncertainty of reservoir. The underground seepage flow and petrophysical parameters (permeability and porosity) are important but difficult to measure in oilfield. Deep learning methods have been successfully used in reservoir engineering and oil & gas production process. In this study, the effective but inaccessible subsurface seepage fields are not used, only the spatial coordinates and temporal information are selected as model input to predict reservoir pressure. A stacked GRU-based deep learning model is proposed to map the relationship between spatio-temporal data and reservoir pressure. The proposed deep learning method is verified by using a three-dimensional reservoir model, and compared with commonly-used methods. The results show that the stacked GRU model has a better performance and higher accuracy than other deep learning or machine learning methods in pressure prediction. © 2023 IEEE.

关键词： Forecasting

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Influence of the Kalman Filtering Initial Setting on SINS Initial Alignment and an Improved Method for the Alignment of Large Misalignment Angles 30

Influence of the Kalman Filtering Initial Setting on SINS In...

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30th Saint Petersburg International Conference on Integrated Navigation Systems, ICINS 2023

作者： Ning, Xiaoge Huang, Jixun Li, Jianxun Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Department of Automation Shanghai China Beijing Aerospace Times Optical-Electronic Co. Ltd Beijing China Beijing Institute of Aerospace Control Devices Beijing China

ISBN: (纸本)9785919950950

This paper analyzes the instability of the filtering system of the initial alignment under a quasi-static base and points out the great influence of Kalman filtering initial value setting on the filtering results. This is instructive for many conditions under initial alignment and integrated navigation. Meanwhile, an improved method for the alignment of large misalignment angles is proposed by replacing the body-frame bias state with the geographic-frame bias state. Simulation experiments show that it can improve the horizontal alignment accuracy by 0.1°and vertical alignment accuracy by 1.6°. © 2023 Concern CSRI Elektropribor, JSC.

关键词： Alignment

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Pointer Meter Reading Under Noise Based on Virtual Data Generation

Pointer Meter Reading Under Noise Based on Virtual Data Gene...

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Chinese automation Congress (CAC)

作者： Jinyang Zhu Zhezhuang Xu Ye Lin College of Electrical Engineering and Automation Fuzhou University Fuzhou China Education Department of Fujian Province Key Laboratory of Industrial Automation Control Technology and Information Processing Fuzhou China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Using machine vision for meter reading significantly enhances the efficiency of industrial monitoring. However, meters in outdoor environment are often subject to the noise such as rain and fog, which affect the accuracy of meter readings. Additionally, the meter images and labels under noise are hard to obtain. To address these challenges, We propose a method for pointer meter reading under noise based on virtual data generation. Firstly, We utilize Unity to construct an industrial meter scene, which generates the images of meter under noise and theri labels. Secondly, we develop a U-Net network with an ASPP module, which expands the receptive field of network and enhances the ability of segmentation network to capture global semantic information under noise. Finally, the angular method is used to calculate the meter readings. Experimental results show that this method can effectively read meters under noise in outdoor environments.

关键词： Meters Image segmentation Rain Accuracy Noise Semantics Object segmentation Data collection Meter reading Monitoring

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Distributed Coordinated Optimal control for Synchronous Operation of Virtually Coupled Train Set 27

Distributed Coordinated Optimal Control for Synchronous Oper...

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27th IEEE International Conference on Intelligent Transportation Systems, ITSC 2024

作者： Luo, Xiaolin Wang, Dongming Wang, Wei Ji, Yindong Liu, Hongjie Beijing Jiaotong University State Key Laboratory of Advanced Rail Autonomous Operation Beijing100044 China University of California Department of Electrical and Computer Engineering RiversideCA92521 United States Traffic Control Technology Co. Ltd Beijing100070 China Tsinghua University Department of Automation Beijing100084 China School of Automation and Intelligence Beijing Jiaotong University Beijing100044 China

ISBN: (纸本)9798331505929

Virtual coupling technologies have been widely studied in recent years, due to their merits of flexibility and efficiency. However, to operate a virtually coupled train set (VCTS) as a single train, the synchronous operation is still a critical problem to be addressed, especially in arriving. To this end, we propose a distributed coordinated optimal control (DCOC) approach integrated with distributed optimization and model predictive control. First, we formulate a globally coordinated optimal control problem for VCTS, where the states of units in VCTS are coupled in the cost and constraints. Then, we design a distributed algorithm to solve the global problem, where local problems are decoupled into ones with fewer dimensions. Next, we employ distributed model predictive control to guarantee the satisfaction of safety constraints before the convergence of the distributed algorithm. Finally, experimental results demonstrate that our approach can achieve stable and synchronous operation for VCTS and save by 90% computation time than existing centralized approaches. © 2024 IEEE.

关键词： Predictive control systems

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Target recognition technology for unmanned ships based on improved YOLOv5 4

Target recognition technology for unmanned ships based on im...

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2024 4th International Conference on Intelligent Traffic Systems and Smart City, ITSSC 2024

作者： Yuan, Mingkai Liang, Bingnan Wang, Haoliang Dong, Yixuan School of Marine Engineering Dalian Maritime University Dalian116026 China Department of Automation Shanghai Jiaotong University Shanghai200240 China Dalian Key Laboratory of Swarm Control and Electrical Technology for Intelligent Ships Dalian116026 China State Key Laboratory of Maritime Technology and Safety Dalian116026 China

ISBN: (纸本)9781510686304

To enable safe and efficient autonomous navigation of unmanned ships in complex marine environments, particularly when encountering overtaking, head-on, or crossing scenarios, it is crucial to accurately identify and detect unknown unmanned vessels. This paper proposes a lightweight object detection algorithm tailored to these challenges. The lightweight network Ghostnet is used to improve the backbone network of the YOLOv5s algorithm, achieving lightweight target detection. By introducing the ECA attention mechanism, the model can better focus on important information in the image, enhancing the ability of feature representation, and improving the model's capability for complex scene understanding and target recognition and localization. Finally, the MPDIoU is used as the bounding box loss function for the YOLOv5s algorithm, which not only improves convergence speed but also obtains more accurate regression results. Comparative experiments show that the proposed improved algorithm outperforms models such as YOLOv5-BiFPN, YOLOv5-CBAM, and YOLOv5-SE in terms of model size, computational complexity, parameter count, detection speed, and average precision. © 2025 SPIE.

关键词： Marine navigation

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无人飞行器在不确定扰动下的动态目标跟踪

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engineering 2024年第4期35卷 74-85页

作者： Yanjie Chen Yangning Wu Limin Lan Hang Zhong Zhiqiang Miao Hui Zhang Yaonan Wang School of Mechanical Engineering and Automation Fuzhou UniversityFuzhou 350108China Department of Computer Science Aberystwyth UniversityAberystwyth SY233DBUK School of Robotics Hunan UniversityChangsha 410082China College of Electrical and Information Engineering Hunan UniversityChangsha 410082China National Engineering Research Center of Robot Visual Perception and Control Technology Hunan UniversityChangsha 410082China

This study proposes an image-based visual servoing(IBVS)method based on a velocity observer for an unmanned aerial vehicle(UAV)for tracking a dynamic target in Global Positioning System(GPS)-denied *** proposed method derives the simplified and decoupled image dynamics of underactuated UAVs using a constructed virtual camera and then considers the uncertainties caused by the unpredictable rotations and velocities of the dynamic target.A novel image depth model that extends the IBVS method to track a rotating target with arbitrary orientations is *** depth model ensures image feature accuracy and image trajectory smoothness in rotating target *** relative velocities of the UAV and the dynamic target are estimated using the proposed velocity *** to the velocity observer,translational velocity measurements are not required,and the control chatter caused by noise-containing measurements is *** integral-based filter is proposed to compensate for unpredictable environmental disturbances in order to improve the antidisturbance *** stability of the velocity observer and IBVS controller is analyzed using the Lyapunov *** simulations and multistage experiments are conducted to illustrate the tracking stability,anti-disturbance ability,and tracking robustness of the proposed method with a dynamic rotating target.

关键词： Unmanned aerial vehicle Visual servoing Velocity observer Target tracking

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