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27th International Conference on System Theory, control and Computing, ICSTCC 2023

作者： Vasiliev, Iulian Luca, Laurentiu Barbu, Marian Vilanova, Ramon Caraman, Sergiu Department of Automation and Electrical Engineering Dunărea de Jos University of Galati Galati Romania Department of Automation Systems and Advanced Control Research Autonomous University of Barcelona Barcelona Spain

ISBN: (纸本)9798350337983

This paper deals with an analysis regarding the effect of Sewer Network operation on the performances of the integrated wastewater collecting and treatment system. The analysis is done by considering various control actions for the output storage tank of the sewer network, comparing a series of performance indicators defined for both subsystems with their "no control" value. Two cases have been considered regarding the control actions for the output storage tank of the sewer network: 1. keeping the output valve at a constant opening and 2. keeping the output valve at the maximum opening possible such as the outflow is limited to a constant value. While the second case did not prove advantageous, the first one showed that lowering the sewer network output valve opening would improve the integrated system performances. © 2023 IEEE.

关键词： Wastewater treatment

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FTEKFNet: Hybridizing Physical and Data-driven Estimation Algorithms for Vehicle State

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-11页

作者： Wang, Yan Hu, Fengqing Tian, Cheng Li, Panshuo Huang, Hailong Yin, Guodong Huang, Chao Department of Industrial and System Engineering The Hong Kong Polytechnical University Hong Kong Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnical University Hong Kong School of Automation and the Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control Guangdong University of Technology Guangzhou China School of Mechanical Engineering Southeast University Nanjing China

Sideslip angle and vehicle velocity are crucial for both traditional and autonomous vehicles. They play essential roles in chassis stability control, as well as in tasks such as path planning and tracking control. However, these states cannot be directly measured by onboard sensors, therefore various vehicle state estimation algorithms have been developed. Most of these algorithms assume that the noise characteristics are known, ignoring the impact of missing measurement data, and cannot simultaneously handle the effects of colored noise and white noise. To address these issues, we propose a fault-tolerant extended Kalman filter network (FTEKFNet), which integrates both physics-based and data-driven methods for vehicle state estimation. Based on the Fault Tolerant Extended Kalman Filter (FTEKF) iterative framework, a pre-trained artificial neural network is utilized to directly predict the Kalman gain, and it is combined with FTEKF to form FTEKFNet. Experimental results under different conditions demonstrate that FTEKFNet can simultaneously deal with unknown noise and data loss problems and has good adaptability to color noise. The estimation performance of the proposed algorithm is better than the traditional FTEKF and EKF methods. IEEE

关键词： Extended Kalman filters

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Real Time Optimization for Operation of Water Distribution Systems to Water Leakage Reduction 14

Real Time Optimization for Operation of Water Distribution S...

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14th International Conference on Electronics, Computers and Artificial Intelligence, ECAI 2022

作者： Dai, Pham Duc Viet, Nguyen Hoang Thuyloi University Department of Control Engineering and Automation Hanoi Viet Nam

ISBN: (数字)9781665495356

ISBN: (纸本)9781665495356

Water loss occurring in water distribution systems (WDSs) can be reduced by regulating operations of Pressure Reducing Valves (PRVs) installed in WDSs. This practical problem can be casted into a nonlinear program (NLP). The quality control of WDSs depends on how fast the solution of the NLP is deduced. It is due to the fact that solving such the optimization normally requires a large computation time, the fully accurate solution of the NLP is thus not suitable for real time control. In this paper, we applied the sensitivity-based method for deriving the real time pressure settings for PRVs, which is appropriate for real time control of the WDS. One benchmark WDS is taken for optimal pressure control to demonstrate the efficacy of the sensitivity-based method. The results have shown that the real time solution by the sensitivity-based method while requiring a negligible time computation have acceptable accuracy. © 2022 IEEE.

关键词： Water distribution systems

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Feasibility Analysis of Path Planning Algorithms 16

Feasibility Analysis of Path Planning Algorithms

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16th International Conference on INnovations in Intelligent SysTems and Applications, INISTA 2022

作者： Allozi, Elbera Yilmaz, Abdurrahman Ervan, Osman Temeltas, Hakan Istanbul Technical University Control and Automation Engineering Department Istanbul Turkey

ISBN: (数字)9781665498104

ISBN: (纸本)9781665498104

Path planning, which aims to find the most suitable route between source and destination, is a challenging problem in mobile robotics. Although there are several study ideas on the path planning challenges of mobile robots in the literature, there is no approach that evaluates path quality qualitatively and quantitatively. It is significant to choose the optimal path by analyzing the properties of the path and the planning algorithm for effectiveness and efficiency. In this paper, we proposed a feasibility analysis to evaluate the quality of the path planning algorithm from various perspectives. This paper defines criteria for path planning algorithms and investigates traceability, smoothness, and shortness factors. Furthermore, by using these test results, a novel artificial neural network-based method has been proposed to enhance path planning algorithms without altering them. © 2022 IEEE.

关键词： Mobile robots

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Data-driven finite-time adaptive attitude tracking control for spacecraft

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Advances in Space Research 2025年第12期75卷 8780-8791页

作者： Wang, Jianhui He, Guangping Bian, Guibin Geng, Shixiong College of Mechanical & Energy Engineering Beijing University Of Technology Beijing100124 China Department of Mechanical and Electrical Engineering North China University of Technology Beijing100144 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

This paper proposes a novel data-driven finite-time adaptive control method for the spacecraft attitude tracking control problem with inertial uncertainty. Based on the dynamic regression extension technique, the disturbance unit matrix is introduced, and the parameter estimation law in the form of algebraic equations is presented, which realizes the arbitrarily small convergence of parameter estimation error. The convergence of parameter estimation errors is verified through stability analysis. Globally non-singular fast terminal sliding mode control is designed to achieve finite-time arrival of the sliding surface and convergence of the system state error. The stability analysis of the closed-loop system demonstrates the effectiveness of the proposed method. Furthermore, the effectiveness and superiority of the proposed method are verified through numerical simulations of spacecraft attitude tracking control. © 2025 COSPAR

关键词： Attitude control

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Real-Time Implementation of MEKF using VDPL Localization Algorithm by Utilizing MATLAB & ROS Communication

Real-Time Implementation of MEKF using VDPL Localization Alg...

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2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024

作者： Altınpınar, Ozan Vahit Contarlı, Emre Can Sezer, Volkan Department of Mechatronics Engineering Smart and Autonomous Systems Laboratory Istanbul Technical University Istanbul Turkey Department of Control and Automation Engineering Smart and Autonomous Systems Laboratory Istanbul Technical University Istanbul Turkey

ISBN: (纸本)9798350379433

Mobile robots, which are produced to fulfill certain tasks to make our lives easier, are becoming more and more common in our environment day by day. In the long run, these robots can be more cost-effective, faster, and more efficient than humans in accomplishing tasks. In order for mobile robots to fulfill the tasks, they need to be able to safely navigate to specific destinations without hitting obstacles. Safely reaching a given goal most accurately and shortly is the problem of autonomy. This autonomy problem is divided into sub-problems and algorithms are needed to solve each sub-problem. The main sub-problems in the field of autonomy are localization, mapping, local planning, and global planning. The main purpose of this paper is to describe how the position information computed by a MEKF (Modified Extended Kalman Filter) localization algorithm using the VDPL (Virtual Dynamic Point Landmark) algorithm, which was previously designed in MATLAB, is published to the ROS environment via a topic. This position information can be used together with the local and global planning algorithms in the navigation stack to realize fully autonomous driving capability in a real-time environment. Using these algorithms, full-autonomous driving tests were conducted on the Turtlebot3 mobile robot in a real-time environment according to a predefined scenario. The performance results of both simulation and real-world tests show that the MEKF using the VDPL algorithm outperforms the AMCL algorithm in the navigation stack in both cases. © 2024 IEEE.

关键词： Extended Kalman filters

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Attitude-trajectory Coupled control of Mars Pinpoint Landing using Nonlinear Model Predictive control 41

Attitude-trajectory Coupled Control of Mars Pinpoint Landing...

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第41届中国控制会议

作者： Qitian Chen Shaoyuan Li Yuanyuan Zou Yanning Guo Department of Automation Shanghai Jiao Tong University Department of Control Science and Engineering Harbin Institute of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

The trajectory guidance and attitude control of Mars lander is a key point in Mars pinpoint landing *** land precisely and efficiently at the target point,an attitude-trajectory coupled control methodology is designed using nonlinear model predictive control(NMPC) in this *** advantage is that it can optimize both trajectory and attitude with online *** addition,it can deal with various physical *** achieve this autonomous control algorithm,a complex dynamics model coupled with the translational and rotational motions of the lander is ***,some physical constraints such as sight-line constraint are ***,a quadratic cost function is designed to minimize the *** simulations verify the feasibility of this autonomous control *** details are presented to demonstrate the effectiveness of the proposed algorithm.

关键词： pinpoint landing nonlinear model predictive control trajectory optimization attitude-trajectory coupled control

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Model Predictive control of a wastewater treatment process using neural networks 28

Model Predictive Control of a wastewater treatment process u...

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28th IEEE International Conference on Emerging Technologies and Factory automation, ETFA 2023

作者： Vasiliev, Iulian Luca, Irina Condrachi, Larisa Luca, Laurentiu Barbu, Marian Vilanova, Ramon Caraman, Sergiu Dunǎrea de Jos University of Galati Department of Automation and Electrical Engineering Galati Romania Autonomous University of Barcelona Department of Automation Systems and Advanced Control Research Barcelona Spain

ISBN: (纸本)9798350339918

This paper deals with the increasing of the operation efficiency of a wastewater treatment plant by reducing the level of pollutant concentration in the effluent. In essence, the main goal is the reduction of the concentration of organic substrate, Model Predictive control algorithm being used for this, considering as a model of the wastewater treatment process a neural network model based on a simplified mathematical model of the 4th order. For the implementation of the control algorithm, two neural networks were trained. In the first version of the neural network, it was considered that all 4 state variables are measurable and in the second version, only the organic substrate was considered measurable. Regarding the training of the two neural networks, good results were obtained in the case of both versions. Instead, the control algorithm gave better results when the second neural network was used (lower values of the substrate, lower variations of the aeration rate, which means a lower cost of operation). © 2023 IEEE.

关键词： Neural networks

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Intelligent On-Line System for Monitoring Technical Condition of High-Voltage Cable Couplings

Intelligent On-Line System for Monitoring Technical Conditio...

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2024 International Russian Smart Industry Conference, SmartIndustryCon 2024

作者： Gasiyarov, Vadim R. Voronin, Stanislav V. Radionov, Andrey A. Lyubimov, Ivan V. Evdokimov, Sergey A. Khramshin, Vadim R. Moscow Polytechnic University Department of Automation and Control Moscow Russia South Ural State University Department of Mechatronics and Automation Chelyabinsk Russia Power Engineering and Automated Systems Institute Nosov Magnitogorsk State Technical University Magnitogorsk Russia

ISBN: (纸本)9798350395044

The article provides the characteristics of the end cable couplings of the closed switchgear 110 kV at the electric steelmaking workshop of the metallurgical plant. The functions of the continuous technical condition monitoring system are substantiated, including continuous temperature monitoring and on-line registration of partial discharges in the insulation. The first function provides monitoring of the operational load, and the second has the maximum sensitivity for diagnosing defect propagation. A functional diagram of the developed intelligent on-line system for monitoring technical condition with digital signal transmission is provided. The choice of sensors and processor unit is justified. The authors consider the temperature control system of high-voltage equipment 'WDM-T', including a wireless sensor and an information receiver. The results of monitoring the thermal regime are provided, the advantages of partial discharge analysis are pointed out. The temperature trends of the end couplings included in the cable line phases are considered. The system is implemented on the closed switchgear 110 kV end couplings, its long-term operation has confirmed the effectiveness of technical condition monitoring. The developed system may be a component of an on-line cyberphysical system for monitoring the condition of high-voltage equipment in the electric steelmaking workshop. © 2024 IEEE.

关键词： Electric lines

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A Multi-party Asymmetric Self-play Algorithm and Its Application in Multi-USV Adversarial Game Simulations 24

A Multi-party Asymmetric Self-play Algorithm and Its Applica...

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2024 International Conference on Machine Learning, Pattern Recognition and automation engineering, MLPRAE 2024

作者： Rao, Jinjun Wang, Cong Liu, Mei Lei, Jingtao Giernacki, Wojciech Department of Precision Mechanical Engineering School of Mechatronic Engineering and Automation Shanghai University China Institute of Robotics and Machine Intelligence Faculty of Automatic Control Robotics and Electrical Engineering Poznan University of Technology Poland

ISBN: (纸本)9798400709876

Aiming at the problem that the combination of self-play (SP) and deep reinforcement learning (DRL) only involves two-party games and the policy learning of each party is limited, a multi-party asymmetric self-play algorithm (MASP) is proposed. Firstly, by improving the ELO scoring system, the ELO scoring takes into account each party of the unmanned surface vehicle (USV) clusters, and the imbalance of the number of USV clusters, so that the frequency of exchanging strategies of all USV clusters in the confrontation process is equal. Secondly, it ensures that USV clusters have a balanced combat ability, and at the same time ensures that the combat ability of all parties is strong and weak and the gap is not too wide. In addition, the parameters are dynamically set to reduce the update frequency of the policy of the stronger party. The experimental results show that the MASP can make the USV clusters learn more effective policies, have a shorter game time, and obtain higher rewards and ELO scores in the simple 2v2 adversarial game scenario and the three-party game scenario of a warship escort mission. © 2024 ACM.

关键词： Deep reinforcement learning

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