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international conference on Electronic Engineering and informatics (EEI)

作者： Gonghe Li Linna Zhou Xiaomin Liu Chunyu Yang School of Information and Control Engineering China University of Mining and Technology Xuzhou China Faculty of School of Information and Control Engineering China University of Mining and Technology Xuzhou China

ISBN: (数字)9798350353594

ISBN: (纸本)9798350353600

A model-based cross-scale reinforcement learning optimal control method is proposed for a class of nonlinear singularly perturbed systems. Initially, according to the singular perturbation theory, the original singularly perturbed system is decomposed into fast and slow subsystems, thereby transforming the original optimal control problem into optimal control problems for the fast and slow subsystems. A cross-scale information interaction mechanism is proposed, where full-order system state data is sampled to update the initial values of the fast and slow subsystems. this approach helps overcome the limitations associated with the online solving of rigid equations and reduce the cumulative errors. To approximate the solution of the Hamilton-Jacobi-Bellman (HJB) equations for the fast and slow subsystems, neural networks (NNs) are employed to approximate the cost functions within iterative processes. Simulation resultst validated the effectiveness of the proposed method.

关键词： Perturbation methods Optimal control Reinforcement learning Artificial neural networks Cost function Mathematical models Data models Iterative methods informatics

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KI-Net: AI-Based Optimization in Industrial Manufacturing—A Project Overview 18th

KI-Net: AI-Based Optimization in Industrial Manufacturing—...

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18th international conference on Computer Aided Systems theory, EUROCAST 2022

作者： Freudenthaler, Bernhard Martinez-Gil, Jorge Fensel, Anna Höfig, Kai Huber, Stefan Jacob, Dirk Software Competence Center Hagenberg GmbH Softwarepark 32a Hagenberg4232 Austria Innsbruck University of Innsbruck Technikerstraße 21a Innsbruck6020 Austria Rosenheim Technical University of Applied Sciences Hochschulstraße 1 Rosenheim83024 Germany Salzburg University of Applied Sciences Urstein Süd 1 Puch/Salzburg5412 Austria University of Applied Sciences Kempten Bahnhofstraße 61 Kempten87435 Germany

ISBN: (纸本)9783031253119

Artificial intelligence (AI) is a crucial technology of industrial digitalization. Especially in the production industry, a great potential is present in optimizing existing processes, e.g., concerning resource consumption, emission reduction, process and product quality improvements, predictive maintenance, and so on. Some of this potential is addressed by methods of industrial analytics beyond specific production technology. Furthermore, particular technological aspects in production systems address another part of this potential, e.g., mechatronics, robotics and motion control, automation systems, and so on. the problem is that the field of AI includes many research areas and methods, and many companies are losing the overview of the necessary and appropriate methods for solving the company problems. the reasons for this are, on the one hand, a lack of expertise in AI and, on the other hand, high complexity and risks of use for the companies (especially for SMEs). As a result, many potentials cannot yet be exploited. the KI-NET project aims to fill this gap, whereby a project overview is presented in this contribution. © 2022, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： robotics

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Implementation of Water Cooling System control of 6-MeV Linear Accelerator for Fruit Sterilization

Implementation of Water Cooling System Control of 6-MeV Line...

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international conference on robotics and automation Sciences (ICRAS)

作者： Nattawat Yachum Surapong Kokkrathoke Somjai Chunjarean Keerati Manasatitpong Nilaped Russamee Accelerator Research and Development Synchrotron Light Research Institute Nakom ratchasima Thailand

ISBN: (数字)9798350352504

ISBN: (纸本)9798350352511

In-house 6-MeV Linear Accelerator (linac) for fruit Sterilization Laboratory in Synchrotron Light Research Institute, thailand which is operated to control an electron beam energy and used for the generation of X-ray radiation. the experiments required an important component, such as linac tube, Electron gun, Microwave source and One of the components affect to Quality, Stability and Reliability of the linac operation that is Water Cooling System (WCS) control. there is used to minimize heat dissipation on the linac tube. It is specification of operation within 40°C. though the designing linac structure was operated which the parameters at 90 Hz repetition rate frequency and 5 µs pulse width beam. Fluctuation of the beam energy suggested that stability of the WCS was insufficient to X-ray intensity of fruit sterilization application. the improvement of WCS was reduced high temperatures on the linac surface and also adjusted fine control parameters with PID controller algorithm of water temperature was suppressed to within 40±0.1°C. As a result of the improvement the X-Ray intensity was effective for stabilization of fruit Sterilization application.

关键词： Cooling Electron beams Synchrotrons Optical wavelength conversion Linear particle accelerator control systems Electron tubes

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Intelligent control of an Integrated Energy System: Low Carbon Modeling and Intelligent Optimization

Intelligent Control of an Integrated Energy System: Low Carb...

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international conference on Electronic Engineering and informatics (EEI)

作者： Zezheng Fu Wenting Lin Degang Yang College of Computer and Information Science Chongqing Normal University Chongqing China Chongqing Engineering Research Center of Educational Big Data Intelligent Perception and Application Chongqing China

ISBN: (数字)9798350353594

ISBN: (纸本)9798350353600

An integrated energy system is a complex system that requires intelligent control to optimize its operation. this paper proposes an intelligent control method for integrated energy systems based on a low carbon model. the model integrates a variety of low carbon technologies such as carbon capture systems, demand response, carbon emissions trading, and clean energy generation. the effect of the proposed intelligent control methods on reducing system costs and carbon emissions is verified through a case study. the results show that the combination of the intelligent control method and the low carbon model leads to a significant reduction in system operating costs and carbon emissions. this provides an important reference for intelligent control of the existing integrated energy system from a low-carbon approach.

关键词： Green energy Costs Carbon dioxide Emissions trading Mathematical models Demand response Sustainable development informatics Optimization Intelligent control

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Enhancing Mobile robotics with Federated Learning: A Collaborative Approach to Supervised Semantic Mapping in Logistic Environments

Enhancing Mobile Robotics with Federated Learning: A Collabo...

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international conference on control and Robots (ICCR)

作者： Sebastian Hoose Marko Harasic Dennis Lehmann Adrian Paschke Fraunhofer IML Fraunhofer FOKUS

ISBN: (数字)9798331518158

ISBN: (纸本)9798331518165

Semantic mapping has many use cases in mobile robotics. For example, in logistic environments, it is applied to find and transport loading goods or in mobile manipulation to identify objects to grasp, and it often relies on neural networks to accomplish image detection and segmentation for semantic mapping. Data sets are usually required to train those neural networks, which are difficult to generate for many organizations since their creation requires qualified personnel. this paper demonstrates how federated learning, combined with supervised neural networks, effectively reduces the effort for semantic map training while maintaining data sovereignty. It allows organizations to facilitate their individual training data generation efforts to build semantic maps by collaborating with other organizations without sharing their training data and, therefore, not losing their data sovereignty. At the same time, they can reduce their individual effort to generate and train data.

关键词： Training Federated learning Semantics Neural networks Supervised learning Training data Organizations Personnel Robots Logistics

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Improvements to the Bacterial Memetic Algorithm used for Fuzzy Rule Base Extraction

Improvements to the Bacterial Memetic Algorithm used for Fuz...

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6th IEEE international conference on Computational Intelligence for Measurement Systems and Applications (CIMSA 2008)

作者： Laszlo Gal Janos Botzheim Laszlo T. Koczy Department of Technology Informatics and Economy University of West Hungary Szombathely Hungary Institute of Information Technology and Electrical Engineering Szechenyi Istvan University Gyor Hungary Department of Automation Szechenyi Istvan University Gyor Hungary Department of Telecommunication and Media Informatics Budapest University슠of슠Technology슠and슠Economics Hungary

In this paper we discuss new methods to improve the Bacterial Memetic Algorithm (BMA) used for fuzzy rule base extraction. the first two methods are knot order violation handling methods which improves the performance of the BMA rather in the case of more complex fuzzy rule base. the third method is a new modification of the BMA in which the order of the operators is modified. this method improves the performance of the BMA rather in the case of less complex fuzzy rule base.

关键词： Fuzzy systems Mamdani-type inference systems Bacterial Memetic Algorithm (BMA) Levenberg-Marquardt method Knot order violation BMA with the modified operator execution order

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Interfaces and models for the diagnosis of cyber-physical ecosystems

IEEE International Conference on Digital Ecosystems and Tech...

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IEEE international conference on Digital Ecosystems and Technologies 2012年

作者： Klar, Dennis Huhn, Michaela Institute of Theoretical Computer Science Technische Universität Braunschweig D-38106 Braunschweig Germany Department of Informatics Clausthal University of Technology D-38678 Clausthal-Zellerfeld Germany

ISBN: (纸本)9781467317030

When the multi-agent paradigm is applied to cyber-physical ecosystems, the diagnosis of physical failures and unexpected interference must be handled by the agents' internal adaptive task planning or external maintenance. In both cases, a profound knowledge of potential dependencies and their run-time manifestations is required. the open, evolutionary aspect of such systems adds to the complexity of failure interaction patterns. As a solution, we propose to adopt techniques from the systemlevel diagnosis of automation systems. By extending existing MAS metamodels with explicit resource and dependency models, an integrated diagnostic knowledge base can be established. the diagnostic viewpoint provides interfaces with enhanced semantics based on causality and symptom propagation and transformation. the formalization enables the checking of diagnostic consistency based on interface compatibility. Results are demonstrated within a smart airport transport scenario. © 2012 IEEE.

关键词： Semantics

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Finite-Iteration Learning control for Nonlinear Systems with Parameter Uncertainties

Finite-Iteration Learning Control for Nonlinear Systems with...

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international conference on Electronic Engineering and informatics (EEI)

作者： Zihan Li Dong Shen School of Mathematics Renmin University of China Beijing P.R. China

ISBN: (数字)9798350353594

ISBN: (纸本)9798350353600

For most of the existing iterative learning control (ILC) results, the tracking of the target trajectory is achieved asymptotically as the iteration number tends to infinity. In this study, a finite-iteration learning control (FILC) strategy is proposed to achieve the accurate tracking of trajectory in a finite iteration number. As the first study of FILC, a linear parameterized system with parameter uncertainties is considered in this article. To eliminate the influence of unknown parameters, we first design a parameter update law. the true value of the unknown parameter is estimated in a finite iteration number by using the proposed parameter update law. then, with the help of the true value of unknown parameter, a novel fractional-power structure control law with a iteration-varying control gain is designed. Under the proposed FILC scheme, the tracking of target trajectory is achieved in a finite-iteration number. the computation method of the iteration number is given. Illustrative examples are provided to verify the theoretical results.

关键词： Uncertain systems Target tracking Accuracy Estimation control systems Stability analysis Trajectory Nonlinear systems informatics Iterative learning control

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RH-SQL: Refined Schema and Hardness Prompt for Text-to-SQL

RH-SQL: Refined Schema and Hardness Prompt for Text-to-SQL

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international conference on Electronic Engineering and informatics (EEI)

作者： Jiawen Yi Guo Chen Zixiang Shen Department of Automation Central South University Changsha China

ISBN: (数字)9798350353594

ISBN: (纸本)9798350353600

Text-to-SQL is a technology that converts natural language queries into the structured query language SQL. A novel research approach that has recently gained attention focuses on methods based on the complexity of SQL queries, achieving notable performance improvements. However, existing methods entail significant storage and training costs, which hampers their practical application. To address this issue, this paper introduces a method for Text-to-SQL based on Refined Schema and Hardness Prompt. By filtering out low-relevance schema information with a refined schema and identifying query hardness through a Language Model (LM) to form prompts, this method reduces storage and training costs while maintaining performance. It's worth mentioning that this method is applicable to any sequence-to-sequence (seq2seq) LM. Our experiments on the Spider dataset, specifically with large-scale LMs, achieved an exceptional Execution accuracy (EX) of 82.6%, demonstrating the effectiveness and greater suitability of our method for real-world applications.

关键词： Training Structured Query Language Costs Natural languages Filtering algorithms Information filters Generators Complexity theory informatics Lenses

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Modeling and Validation of a Single-Axis Tilting Quadrotor with Enhanced Attitude control

Modeling and Validation of a Single-Axis Tilting Quadrotor w...

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robotics, automation and Artificial Intelligence (RAAI), IEEE international conference on

作者： Pushkar Kumar Amit Shukla Darshankumar Prajapati Ankit Mehra Ashish Rana Indian Institute of Technology Mandi Himachal Pradesh India

ISBN: (数字)9798331520038

ISBN: (纸本)9798331520045

Standard quadrotors are inherently limited by their underactuated nature, typically offering only 4 degrees of freedom (DOF) through their four rotors. While sufficient for general applications, however this design falls short in scenarios requiring full attitude control, improved wind resistance, aerial manipulation and other specialized capabilities. this paper presents the design, implementation, and evaluation of a novel fully actuated 6-DOF quadrotor featuring a single-axis tilting mechanism. Our proposed design incorporates four rotors and two tilt motors, enabling complete position and attitude control. We derive a comprehensive dynamic model of the quadrotor and discuss the control parameters crucial for stable flight. the paper details the practical implementation of this design on actual hardware, demonstrating its feasibility beyond theoretical concepts. Furthermore, we showcase the quadrotor's enhanced performance through experimental results. these results highlight the advantages of our fully actuated design over traditional underactuated quadrotors in applications requiring precise aerial manipulation and resilience to external disturbances

关键词： Resistance Attitude control Rotors Aerodynamics 6-DOF Vehicle dynamics Standards Robots Quadrotors Resilience

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