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International Conference on Computer Theory and Applications (ICCTA)

作者： Sohila Megahed Ayman El-Badawy Automation and Control German International University Mechatronics Engineering Department German University in Cairo

ISBN: (数字)9798331529680

ISBN: (纸本)9798331529697

A state estimator using soft actor-critic (SAC) reinforcement learning (RL) algorithm is presented in this paper. Estimating states of non linear systems is a challenging task due to the inherent complexities of such systems, including uncertainties, nonlinearities, and measurement noise. Motivated by the need to address these limitations, thereby enhancing control performance, this work proposes an efficient state estimation technique. Specifically, we aim to replace the computationally expensive gain calculation within the Extended Kalman Filter (EKF) with the output of a neural network trained using the SAC algorithm. This approach eliminates the requirement for explicit computation of the covariance and Jacobian matrices, which are significant bottlenecks in the EKF. Consequently, the estimation process exhibits improved efficiency, particularly after the neural network has been adequately trained. To validate the efficacy of the proposed technique, a deep RL agent was implemented, trained, and tested on an unmanned aerial vehicle (UAV) system. The convergence of the estimation error and the observed 71% reduction in simulation execution time serve as evidence for the accuracy and efficiency of this estimation method.

关键词： Estimation error Accuracy Neural networks Reinforcement learning Autonomous aerial vehicles Real-time systems Mathematical models Vectors State estimation Nonlinear systems

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Simultaneous Estimation of Human Motion Intention and Time-Varying Arm Stiffness for Enhanced Human-Robot Interaction

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IEEE Transactions on Cognitive and Developmental Systems 2024年第3期17卷 510-524页

作者： Wu, Huayang Zhu, Chengzhi Cheng, Long Yang, Chenguang Li, Yanan University of Sussex Department of Engineering and Design BrightonBN1 9RH United Kingdom South China University of Technology Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering Guangzhou510640 China Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Beijing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China University of Liverpool Department of Computer Science LiverpoolL69 3BX United Kingdom

Recent advances in physiological human motor control research indicate that human endpoint stiffness magnitude increases linearly with grasp force. Based on these findings, a scheme was proposed in this paper to integrate the linear quadratic estimation (LQE) filter with the stiffness model inferred from grasp force, which can simultaneously estimate the human arm's stiffness and motion intention. Then, an online variable impedance controller (VIC) was designed based on previous estimations for physical human-robot interaction (pHRI). The proposed stiffness model and estimation method were validated through experiments using a planar robotic interface. In order to assess its performance in practical pHRI tasks, the implementation of human arm stiffness and intention estimation combining with VIC was extended to a teleoperation peg-in-hole and robot-assisted rehabilitation tasks. The experimental results demonstrate that the proposed method can effectively estimate human motion intention and arm stiffness simultaneously. Compared to existing methods, the proposed VIC enhances pHRI in terms of increased flexibility, effective guidance, and reduced human effort. © 2016 IEEE.

关键词： Human robot interaction

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Acoustic Positioning of Partial Discharges in High-Voltage Transformer Tank

Acoustic Positioning of Partial Discharges in High-Voltage T...

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2024 International Ural Conference on Electrical Power engineering, UralCon 2024

作者： Karandaev, Alexandr S. Loginov, Andrey B. Nikolaev, Andrey A. Moscow Polytechnic University Department of Automation and Control Moscow Russia Power Engineering and Automated Systems Institute Nosov Magnitogorsk State Technical University Magnitogorsk Russia Magnitogorsk Iron and Steel Works Magnitogorsk Russia

ISBN: (纸本)9798350386028

This report reviews an example of acoustic positioning of partial discharges (PD) in the tank of a high-voltage oil-filled transformer. The literature review confirms the importance of PD monitoring and justifies the feasibility of positioning discharge activity centers. The precise positioning of PD sources is required to determine the location of insulation defects. The authors provide brief information on the development of PD positioning methods and note that their practical application has been insufficiently covered in publications. They present the results of electromagnetic and acoustic PD positioning in a 110 kV transformer. Some details are provided on the devices and measurement methods used, including the localization of areas with increased PD intensity using one acoustic sensor and the subsequent center localization through the installation of 4 sensors at even intervals. The authors provide PD signals and defect impulses received from each of the sensors and demonstrate the difference in the registration time of these signals. They explain the principle behind PD center positioning, which is determined considering delays in signal reception. The authors demonstrate the usage of the Inva (Portable) software for the processing and visualization of acoustic positioning results. They note that changes in the propagation rate of acoustic waves in a heterogeneous medium result in the reduced accuracy of results. The authors also outline the prospects of the research into the elimination of occurring defects. © 2024 IEEE.

关键词： Oil filled transformers

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automation System Architecture of pH Neutralization Process in Batik Wastewater Treatment Plant 4

Automation System Architecture of pH Neutralization Process ...

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4th engineering Physics International Conference 2023, EPIC 2023

作者： Diyah, Nazuwatussya Ekawati, E. Pradipta, J. Yulia, E. Master Program of Instrumentation and Control Faculty of Industrial Technology Institut Teknologi Bandung Indonesia Engineering Physics Research Group Faculty of Industrial Technology Institut Teknologi Bandung Indonesia Doctoral Program of Engineering Physics Faculty of Industrial Technology Institut Teknologi Bandung Indonesia Center for Instrumentation Technology and Automation Institut Teknologi Bandung Indonesia

Batik production in home industries needs support wastewater treatment in a limited space. Therefore, a modular-type, lab-scale wastewater treatment plant (WWTP) with a capacity of 87.75 liters and a dimension of 1.5 m × 0.75 m × 1 m has been constructed. The WWTP combines three significant processes: equalization, neutralization, and adsorption. This study focuses on the monitoring systems for the pH neutralization process. The system uses four microprocessors in a master/Slave architecture and the I2C protocols for data communication between processors. The measuring instruments include pH, temperature, turbidity, and flow rate sensors. The actuators consist of submersible and peristaltic pumps. The operating range of pH, temperature, turbidity, and flow rate sensors are 0-14, 25-81.44℃, 0-3000 NTU, and 6.49-20.84 ml/s respectively. The pumps work in Pulse Width Modulation (PWM) mode with an operating range of 125-225 PWM. All sensors and actuators operate linearly within the operating range with a correlation coefficient of 0.97-1. © 2023 Institute of Physics Publishing. All rights reserved.

关键词： Turbidity

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Sequential Convex Program for Variable Speed Pump Scheduling in Water Distribution Systems

Sequential Convex Program for Variable Speed Pump Scheduling...

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International Conference on Electronics, Computers and Artificial Intelligence (ECAI)

作者： Pham Duc Dai Department of Control Engineering and Automation Thuyloi University Hanoi Vietnam

Operation of water distribution systems (WDSs) to reduction of water leakage can be achieved by properly operating variable speed pumps (VSPs). This practical problem can be casted into a nonlinear program (NLP) where decision variables are relative speeds of pumps while the state variables are flows and nodal heads. The formulated NLP consists of both convex and non-convex constraints, for this reason, we proposed to apply the sequential convex programming technique (SCP) for solving the NLP. The advantage of the SCP method lies in the fact that instead of solving the non-convex NLP, we solve sequential convex NLPs and, in this case, it requires less number of iterates for solution convergence than solving the problem directly by using standard NLP solvers. The effectiveness of the approach was demonstrated on two WDSs for optimal VSP scheduling problem

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Online Optimization in Power Systems With High Penetration of Renewable Generation:Advances and Prospects

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 839-858页

作者： Zhaojian Wang Wei Wei John Zhen Fu Pang Feng Liu Bo Yang Xinping Guan Shengwei Mei Key Laboratory of System Control and Information Processing Ministry of Education of ChinaDepartment of AutomationShanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Power System and the Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Institute of High Performance Computing(IHPC) Agency for Science Technology and Research(A*STAR)Singapore 138632Singapore

Traditionally,offline optimization of power systems is acceptable due to the largely predictable loads and reliable *** increasing penetration of fluctuating renewable generation and internet-of-things devices allowing for fine-grained controllability of loads have led to the diminishing applicability of offline optimization in the power systems domain,and have redirected attention to online optimization ***,online optimization is a broad topic that can be applied in and motivated by different settings,operated on different time scales,and built on different theoretical *** paper reviews the various types of online optimization techniques used in the power systems domain and aims to make clear the distinction between the most common techniques *** particular,we introduce and compare four distinct techniques used covering the breadth of online optimization techniques used in the power systems domain,i.e.,optimization-guided dynamic control,feedback optimization for single-period problems,Lyapunov-based optimization,and online convex optimization techniques for multi-period ***,we recommend some potential future directions for online optimization in the power systems domain.

关键词： optimization Lyapunov optimization online convex optimization online optimization optimization-guided control

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An Efficient Mixed Integer Nonlinear Program Model for Optimal Positions of Pressure Reducing Valves in Water Distribution Systems

An Efficient Mixed Integer Nonlinear Program Model for Optim...

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International Conference on Electronics, Computers and Artificial Intelligence (ECAI)

作者： Pham Duc Dai Department of Control Engineering and Automation Thuyloi University Hanoi Vietnam

Water loss happens in all water distribution systems (WDSs). To deal with such the problems, pressure management strategy should be applied to lessen the water leakage flow. The optimal pressure management is formulated to minimize the total of excessive pressures in all demand supplying nodes. In mathematical formulation, it is a mixed-integer nonlinear program (MINLP). The existing MINLP model having been used until now for optimizing PRV locations is proven to be hard for MINLP algorithms based gradient methods and therefore is only suitable for small-scale WDSs with a limited number of demand patterns. In this paper, an efficient non-smooth constraints are proposed to model whether PRVs are installed on links for the optimal PRV localization problem. Since these constraints can be approximated by relaxed forms of complementarity inequalities, high quality MINLP solution can be achieved in a reasonable computation time. To demonstrate the efficacy of our new modeling approach, comparison of the performance of the newly formulated MINLP with the existing one for solving optimal PRV locating problems for a real WDS are taken. The results have shown that with our new MINLP model, better MINLP solution can be attained even for WDSs with multiple demand patterns.

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BFuse-Net: Bonferroni Mean Operator-Aided Fusion of Neural Networks for Medical Image Classification 5th

BFuse-Net: Bonferroni Mean Operator-Aided Fusion of Neural ...

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5th International Conference on Medical Imaging and Computer Aided Diagnosis, MICAD 2024

作者： Ghosh, Triyas Chakraborty, Soham Kaplun, Dmitrii Gulvanskii, Vyacheslav Sarkar, Ram Department of Computer Science and Engineering Jadavpur University Kolkata700032 India Artificial Intelligence Research Institute China University of Mining and Technology Xuzhou China Department of Automation and Control Processes Saint Petersburg Electrotechnical University "LETI" Saint Petersburg Russia

ISBN: (纸本)9789819638628

In this paper, we have proposed a novel model, called Bonferroni Mean Operator-aided Fusion of Neural Networks (BFuse-Net). Here, we have taken advantage of the capabilities of four deep learning models as the base learners and then applied a customized attention method to prioritize different fine-grained features by passing their outputs via four parallel pipelines. Next, we have employed a novel aggregation method, a modified Bonferroni Mean operator, to merge the decision scores acquired from every pipeline, prioritizing their individual contributions above their interactions with others in the decision scores. Three medical image datasets— LC25000 (colon cancer), Oral Squamous Cell Carcinoma, and Malaria Cell Images have been used for experimentation. The model yields state-of-the-art outcomes for the three datasets. The source codes and additional results can be found at GitHub repository. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Deep learning

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Extended Kalman Filter Based Nonlinear Probabilistic Model Predictive control of an Autonomous Motorcycle

Extended Kalman Filter Based Nonlinear Probabilistic Model P...

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International Conf on Electrical and Electronic engineering (ICEEE)

作者： Nurettin Çerçi Yaprak Yalçin Mechatronics Engineering Department Istanbul Technical University Istanbul Turkey Control and Automation Engineering Department Istanbul Technical University Istanbul Turkey

ISBN: (数字)9798350362541

ISBN: (纸本)9798350362558

This work focuses on the control of a nonlinear autonomous motorcycle model using Probabilistic Model Predictive control (MPC). The main purpose of this work is to control the speed, yaw angle and roll angle of the motorcycle while keeping its balance during a maneuver. The Probabilistic MPC takes into account the probabilistic disturbances acting on the control inputs or the state variables. The cost function of the optimization of this proposed nonlinear probabilistic MPC is different than the cost of traditional deterministic MPC, such that, it contains terms that represent the mean of the state variable which is calculated with the help of an Extended Kalman Filter (EKF) and also the terms as the functions of covariances of the state variables and control inputs. The optimization algorithm is fed with these mean and covariance values every time instant, then the controller calculates the optimal control sequence to apply it to the system model. The speed of the motorcycle, the yaw angle and, the roll angle of the motorcycle are controlled with good efficiency.

关键词： Costs Motorcycles Optimal control Predictive models Probabilistic logic Cost function Kalman filters Predictive control

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Dynamic Parameter Identification based on the Least Squares method for a 6-DOF Manipulator

Dynamic Parameter Identification based on the Least Squares ...

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2023 International Conference on System Science and engineering, ICSSE 2023

作者： Nguyen, Ngoc Thien Nguyen, Thi Ngoc Thuy Tong, Hai Ninh Truong, Hoai Vu Anh Tran, Duc Thien Ho Chi Minh City University of Technology and Education Automation Control Department Ho Chi Minh City70000 Viet Nam Department of Mechanical Engineering Gyeongbuk37673 Korea Republic of

ISBN: (纸本)9798350322941

Accurate dynamics play crucial roles in designing advanced control algorithms to ensure the feasibility, stability, and efficiency of the system. However, the manipulator is a complex multi-input-multi-output system, and so many system noises seriously affect parameter identification results, thereby the process of determining them is challenging. In order to manage this challenge, a Least Squares (LS) method is proposed to estimate the dynamic parameters. First of all, the kinematics of the system is built according to Denavit-Hartenberg (DH) notation, and the dynamic model is calculated by using Lagrange-Euler equations. After that, the regrouped parameters in the dynamic model are given to the general linear matrix to apply the least squares method for the model. Finally, to demonstrate the effectiveness and reliability of the proposed method, data acquisition is carried out by using a PD controller in simulations via Simscape Multibody/MATLAB Simulink for the dynamic estimate model and the Solidworks robot model. After that, the Root Mean Squared Error (RMSE) formula is used to analyze the accuracy of the LS method. © 2023 IEEE.

关键词： Dynamic models

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