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European control Conference (ECC)

作者： Robert Maniarski Wojciech Paszke Hongfeng Tao Eric Rogers Institute of Automation Electronic and Electrical Engineering University of Zielona Góra Zielona Góra Poland Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Jiangnan University Wuxi China School of Electronics and Computer Science University of Southampton Southampton UK

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

This paper investigates the problem of designing robust iterative learning control laws for discrete-time batch processes with norm-bounded parameter uncertainties. A law of proportional-differential type is designed to achieve robust convergence of the tracking error in the batch-to-batch direction. It is shown that the design problem can be written as a two-dimensional system. Then, the recently developed non-conservative conditions for (structural) stability analysis for a linear Roesser model are used. The conditions for the existence and computation of the required control law matrices are linear matrix inequality-based. Finally, comparative simulation results show the effectiveness of the new design.

关键词： Uncertain systems Analytical models Simulation Computational modeling Batch production systems Europe Linear matrix inequalities

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Hierarchical Motion Planning and Offline Robust Model Predictive control for Autonomous Vehicles

Hierarchical Motion Planning and Offline Robust Model Predic...

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American control Conference (ACC)

作者： Hung Duy Nguyen Minh Nhat Vu Nguyen Ngoc Nam Kyoungseok Han Automation & Control Institute (ACIN TU Wien Vienna Austria Austrian Institute of Technology GmbH (AIT) Vienna Austria School of Mechanical Engineering Kyungpook National University Daegu South Korea Faculty of Electrical and Electronic Engineering Phenikaa University Hanoi Vietnam

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

Driving vehicles in complex scenarios under harsh conditions is the biggest challenge for autonomous vehicles (AVs). To address this issue, we propose hierarchical motion planning and robust control strategy using the front active steering system in complex scenarios with various slippery road adhesion coefficients while considering vehicle uncertain parameters. Behaviors of human vehicles (HVs) are considered and modeled in the form of a car-following model via the Intelligent Driver Model (IDM). Then, in the upper layer, the motion planner first generates an optimal trajectory by using the artificial potential field (APF) algorithm to formulate any surrounding objects, e.g., road marks, boundaries, and static/dynamic obstacles. To track the generated optimal trajectory, in the lower layer, an offline-constrained output feedback robust model predictive control (RMPC) is employed for the linear parameter varying (LPV) system by applying linear matrix inequality (LMI) optimization method that ensures the robustness against the model parameter uncertainties. Furthermore, by augmenting the system model, our proposed approach, called offline RMPC, achieves outstanding efficiency compared to three existing RMPC approaches, e.g., offset-offline RMPC, online RMPC, and offline RMPC without an augmented model (offline RMPC w/o AM), in both improving computing time and reducing input vibrations.

关键词： Vibrations Uncertain systems Computational modeling Roads Trajectory Planning Autonomous vehicles

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Adaptive Mpc-Based Optimization of Battery Discharge Strategy for Autonomous Pmsm Vehicles

SSRN

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SSRN 2024年

作者： Ismail, Moustafa Magdi Al-Dhaifallah, Mujahed Rezk, Hegazy Ur Rahman Habib, Habib Khalique Junejo, Abdul Hamad, Samir A. Electrical Engineering Department Faculty of Engineering Minia University EL-Minya61517 Egypt Dhahran31261 Saudi Arabia King Fahd University of Petroleum & Minerals Dhahran31261 Saudi Arabia Department of Electrical Engineering College of Engineering in Wadi Alddawasir Prince Sattam bin Abdulaziz University Saudi Arabia Department of Electrical Engineering Faculty of Electrical and Electronics Engineering University of Engineering and Technology Taxila Taxila47050 Pakistan Electrical Engineering Department Qaid-eAwam University of Engineering Science and Technology Nawabshah67450 Pakistan Department of Process Control Technology Faculty of Technology and Education Beni-Suef University Beni Suef Egypt Prince Sattam bin Abdulaziz University Saudi Arabia Minia University Egypt

Effective battery management is critical for the performance and lifespan of smart electric vehicle (EV) systems. Therefore, reducing battery discharge is key to improving the range of EVs. This paper proposes an adaptive model predictive control (AMPC) strategy for optimizing battery discharge of EVs. Specifically, AMPC autonomously controls the smart EV by managing the lateral position, yaw angle, and PMSM to provide the required traction torque at the desired speed. The strategy updates the operating points of the predictive model at each time step to accurately represent the nonlinear plant across different speed regions, using vehicle linear velocity and stator currents. Meanwhile, the stator inductances and induced motor torque are estimated via a third order generalized integrator. Finally, simulation results demonstrate that the AMPC significantly reduces battery discharge current, watt-hour per kilometer, capacity rate, and parallel cell units. Meanwhile, the AMPC improves lane-keeping assistance in the electric power steering system and ensures precise tracking of speed and torque. A finite element method parameterized PMSM simulation model enhances motor capture. Consequently, AMPC shows superior performance in vehicle dynamics and PMSM control compared to the classic MPC approach. © 2024, The Authors. All rights reserved.

关键词： Adaptive control systems

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Stability analysis and stabilization of discretized uncertain spatially interconnected systems

Stability analysis and stabilization of discretized uncertai...

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International Conference on Methods and Models in automation and Robotics (MMAR)

作者： Bartłomiej Sulikowski Krzysztof Gałkowski Łukasz Hładowski Anton Kummert Joerg Velten Institute of Control and Computation Engineering University of Zielona Góra Zielona Góra Poland Institute of Automation Electronic and Electrical Engineering University of Zielona Góra Zielona Góra Poland Faculty of Electrical Information and Media Engineering University of Wuppertal Wuppertal Germany

In this paper spatially interconnected (ladder) systems have been discussed. First, the multidimensional, in that case, 2D - continuous in time and discrete in the spatial variable, has been introduced. Next, the temporal dynamics has been discretized, which has allowed to create the general, discrete model for the system dynamics. It has been assumed that system elements are the subject of uncertainty of the norm bounded form. Finally, robust stability testing and robust stabilizing controller design conditions have been proposed and its effectiveness is illustrated by an simulation example.

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Optimal control of Automatic Manipulator for Elimination of Galvanic Line Load Oscillation

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica electrical engineering and computer science 2021年第2期65卷 91-105页

作者： Autsou, Siarhei Rassõlkin, Anton Vaimann, Toomas Demidova, Galina Saroka, Viktor Karpovich, Dzmitry Kallaste, Ants Department of Automation of Production Processes and Electrical Engineering Faculty of Chemical Technology and Technique Belarussian State Technological University 13a Sverdlova str. Minsk220006 Belarus Department of Electrical Power Engineering and Mechatronics Tallinn University of Technology 5 Ehitajate street Tallinn19086 Estonia Faculty of Control Systems and Robotics Itmo University 49 Kronverksky Pr. St. Petersburg197101 Russia

This paper provides an analysis of the current state-of-The-Art technologies in the field of auto-operators used in production during the electroplating process. General schemes of operations are presented, benefits and drawbacks of each scheme are discussed. The paper discusses an increase in the operating efficiency of the auto-operator in transient conditions (braking and acceleration) by reducing suspension oscillations and provides an example of a similar problem from other industries. In addition to the classification of the auto-operators, three main ways and control methods of the auto-operator of a galvanic line are presented. The main ways of eliminating oscillations during the movement of the auto-operator, as well as the rationale for the choice of adaptive (optimal) control, based on and comparing the basic control algorithms of the robot manipulator, are discussed. The comparative analysis of algorithms used to determine the optimal control has been carried out. Application field of each optimal control method described, moreover advantages and disadvantages as well as implementation methods described. Bellman dynamic programming method was chosen to eliminate oscillations of the suspension with details during the auto-operator transient conditions, the chosen method takes into account all necessary conditions to achieve the desired result. © 2021 Budapest University of Technology and Economics. All rights reserved.

关键词： Dynamic programming

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Adaptive Sensitivity Amplification control with Q-Learning for Cable-Driven Lower-Limb Exoskeletons

Adaptive Sensitivity Amplification Control with Q-Learning f...

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Chinese control Conference (CCC)

作者： Linzhen Zhong Xiaodong Wang Guanbin Gao Yashan Xing Faxiang Zhang Faculty of Information Engineering & Automation Kunming University of Science and Technology Kunming China Yunnan International Joint Laboratory of Intelligent Control and Application of Advanced Equipment Kunming China Faculty of Mechanical & Electrical Engineering Kunming University of Science & Technology Kunming China

This paper proposes a sensitivity amplification control (SAC) based on Q-learning for the cable-driven lower-limb exoskeleton (CDLEX) to guarantee the tracking performance and achieve comfortable human-robot interaction (HRI). There is no requirement for direct measurement of HRI in the SAC scheme, hence the force/torque sensors are avoided. For the purpose of accommodating the uncertainties of the interaction environment, such as the individual gaits and suddenly changing walking trajectories, the Q-learning algorithm is utilized to realize online parameter tuning of SAC. Finally, comparative numerical simulations are included to verify the effectiveness of the control scheme.

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Minimized Variance control of Communication Delays for Markov Switching Channels in IIoT

Minimized Variance Control of Communication Delays for Marko...

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International Conference on automation and Computing (ICAC)

作者： Hui Liu Xuewu Dai Qiwei Zhang Fei Qin State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China Faculty of Engineering and Environment Northumbria University Newcastle upon Tyne UK School of Electronics Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China

This paper mainly considers the wireless communication scenario where equipment in different working conditions switches its channel state in the actual industrial field. To address the problem of uncertain communication delays in wireless control systems, we model the randomness introduced by the inevitable multipath fading channels as a Markov process. The distribution of communication delays is controlled in a statistical sense, given the probability density function(PDF) of power gain under various channel states and the Markov transition matrix. Based on the principle of Shannon channel capacity, we propose an algorithm for controlling the shape of the PDF to find the optimal transmission power for each channel state in the sense of minimizing delay variance. Then the transmission power is adjusted according to the channel state in real-time, and the PDF shape of the communication delays is controlled to present a Gaussian distribution of minimized variance. Compared with the delay variance of 80 ms by using fixed transmission power, the simulation results show that the variance of the communication delays is reduced to 0.1 ms when the wireless channel states is known.

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Solar Radiation Forecasting Based on Random Forest and XGBoost 7

Solar Radiation Forecasting Based on Random Forest and XGBoo...

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7th International Conference on Green Technology and Sustainable Development, GTSD 2024

作者： Nguyen, Nhat-Truong Tuong Dao, Thai Cat Tuyen Nguyen, Le Nhut Nguyen, Thanh-Dat Le, Minh-Vuong French, Isobel Timothea Doan, Van-Tuong Kim Vo, Van Hoang Tran, Nghi C. Pham, Duc-Hung Nguyen, Van-Trung Ho Chi Minh City University of Technology and Education Department of Renewable Energy Viet Nam Ho Chi Minh City Industry and Trade College Department of Control Engineering and Automation Viet Nam LILAMA2 International Technology College Dongnai Viet Nam Institute of Cognitive Neuroscience National Central University Taiwan College of Information and Communication Technology Can Tho University Viet Nam Hung Yen University of Technology and Education Faculty Electrical and Electronic Engineering Viet Nam

ISBN: (纸本)9798350386073

Renewable energy offers a viable alternative to depleting fossil fuels, contributing to global warming and greenhouse gas emissions. Thus, solar energy is widely favored as a renewable energy source. However, the output power of solar systems is unstable and is highly dependent on environmental circumstances such as radiation, humidity, temperature, and wind. Therefore, accurately estimating solar radiation is crucial for successful integration of the solar system into existing electrical grid systems. In this study, two different machine learning models, XGBoost and Random Forest, were used to predict solar radiation data in Ho Chi Minh City, Vietnam. The results show that RMSE and MAE of the Random Forest model (61.09 and 24.37) is smaller compared to XGBoost (61.31 and 25.08). Regression value of the two models is close to 0.955. In summary, this paper demonstrates that these two machine learning algorithms effectively forecast solar radiation, with the Random Forest model showing better performance. © 2024 IEEE.

关键词： Solar irradiance

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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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An Alternative Approach to Reduce Switching Frequency on Semiconductor Switches in Power Electronic Converters

An Alternative Approach to Reduce Switching Frequency on Sem...

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International Conference on control, automation and Information Sciences (ICCAIS)

作者： Trung Tuyen Bui Duy Trinh Tran Tien Dung Vo Khac Tuan Nguyen Van Nam Giap Quang Dich Nguyen Institute for Control Engineering and Automation-ICEA Hanoi University of Science and Technology Ha Noi Viet Nam Faculty of Electrical Engineering Vinh University of Technology Education Vinh Viet Nam School of Electrical and Electronic Engineering Hanoi University of Science and Technology Ha Noi Viet Nam

This article presents an alternative approach to reduce the switching frequency in switching elements within power electronic converters. The aim is to address the challenges of conventional semiconductor devices in high-frequency switching, such as switch transition times and high-frequency pulse generation. With the proposed configuration, the semiconductor switch components and pulse generator operate at a lower frequency than the output frequency of the converter. Simulations to verify the approach will be conducted using PLECS software.

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