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Chinese Automation Congress (CAC)

作者： Hao Yang Jinlong Wang Zhezhuang Xu Boyu Chen Qingdong Zhang Education Department of Fujian Province Key Laboratory of Industrial Automation Control Technology and Information Processing College of Electrical Engineering and Automation Fuzhou University Fuzhou China Sansteel Minguang Co. Ltd. Sanming China

Steel plates are highly customized according to different customer demands. In this case, the outbound date, the specifications of the steel plates and the distribution of stacks must be simultaneously considered when the steel plates are stored in the yard. Improper storage of steel plates significantly increases the number of shuffles during outbound operations. To overcome the challenge, we propose an efficient steel plate storage scheme based on the actual scenario of existing steel plate distribution in the yard. Firstly, a model for steel plate storage scheduling is established to minimize the number of extra blocking plates. Then, three heuristic algorithms are designed to solve the problem. Comparative experiments are carried out to verify the effectiveness of the proposed algorithm. The experimental results show that the proposed method can sufficiently improve the efficiency of steel plates scheduling.

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Transformer-Based Sequence Modeling with Action Discretization for Robotic Grasping

Transformer-Based Sequence Modeling with Action Discretizati...

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Chinese Automation Congress (CAC)

作者： Yaokun Hou Song Zheng Zhezhuang Xu Meng Yuan Ping Huang Weibing Huang Department of Fujian Province Key Laboratory of Industrial Automation Control Technology and Information Processing Education College of Electrical Engineering and Automation Fuzhou University Fuzhou China Evomotion Co. Ltd. Shenzhen Guangdong China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

The powerful representational and sequential modeling capabilities of Transformer have been validated in various fields such as natural language processing. However, how to better address sequential decision-making problems like robotic grasping through the Transformer architecture and achieve autonomous control of robotic grasping remains a longstanding challenge. Models that directly output continuous decision actions for robotic arms often rely on mean squared error (MSE) loss for training, which is unable to effectively handle the randomness and diversity of actions. This limitation leads to the generation of relatively singular actions in certain grasping scenarios, reducing the success rate of grasping. To address this issue, this paper proposes a Transformer-based method for discretizing robotic arm actions, where actions are discretized by dimension to enable autoregressive modeling. Experimental results demonstrate that this method effectively improves the grasping performance of robotic arms in simulation environments.

关键词： Training Automation Decision making Grasping Transformers Manipulators Natural language processing Trajectory

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Optimization for Pickup Vehicle Scheduling in Steel Logistics Park Based on Enhanced SPEA2

Optimization for Pickup Vehicle Scheduling in Steel Logistic...

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Chinese Automation Congress (CAC)

作者： Hongjie Xu Jinlong Wang Zhezhuang Xu Boyu Chen Qingdong Zhang Education Department of Fujian Province Key Laboratory of Industrial Automation Control Technology and Information Processing College of Electrical Engineering and Automation Fuzhou University Fuzhou China Sansteel Minguang Co. Ltd. Sanming China

Pickup vehicle scheduling in the steel logistics park is a critical issue in determining the outbound effciency of steel products. Steel products are distributed in the yards of the steel logistics park with mixed storage, and the optional yards for each pickup operation are not unique, which greatly increases the scheduling complexity. To overcome this challenge, in this paper, we propose a pickup vehicle scheduling problem with mixed steel storage (PVSP-MSS) to optimize makespan of pickup vehicle and makespan of steel logistics park simultaneously. The optimization problem is described as a multi-objective problem, and an enhanced Strength Pareto Evolutionary Algorithm 2 (ESPEA) is proposed to solve the problem with high efficiency. Experiments are executed based on data collected from a real steel logistics park. The results confirm that ESPEA can significantly reduce both makespan of each pickup vehicle and makespan of steel logistics park.

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Constructive on-line learning for a neuro-fuzzy network with fuzzy sets obtained by Delaunay triangulation

Constructive on-line learning for a neuro-fuzzy network with...

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IEEE Conference on Decision and control

作者： C. Pereira A. Dourado R. Babuska ISEC-Instituto Superior de Engenharia de Coimbra Coimbra Portugal Universidade de Coimbra Polo II Coimbra Portugal Department of Information Technology and Systems Control Engineering Laboratory Delft University of Technnology Delft Netherlands

ISBN: (纸本)0780366387

This paper addresses the design and gradual building of a rule based neuro-fuzzy network using piecewise linear multidimensional membership functions obtained by Delaunay partition of the input space. Online growing and pruning techniques are used to obtain a parsimonious structure. The proposed network is shown to be useful in approximating unknown nonlinearities of dynamic systems. A control framework is applied, taking advantage of the piecewise linear property of the model. For each simplex, the local inverse model can easily be calculated. The operation of this adaptive control scheme using the online constructive algorithm and the inverse of the local linear model is demonstrated using a simulation example and a laboratory scale process.

关键词： Fuzzy neural networks Fuzzy sets Neural networks Piecewise linear techniques Multidimensional systems Space technology Laboratories Piecewise linear approximation Inverse problems Adaptive control

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ntelligent Word Semantic Proofing System for Special Field

ntelligent Word Semantic Proofing System for Special Field

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Computational engineering in Systems Applications, CESA, IMACS Multiconference on FLAGGED

作者： Xiaoping Qiu Yi Wang Yang Xu School of Economics and Management Southwest Jiaotong University Chengdu Sichuan China Department of Network Engineering Chengdu University of Information and Technology Chengdu China Intelligent Control Development Center Southwest Jiaotong University Chengdu Sichuan China

An intelligent word semantic proofing system for special field is discussed deeply in this paper. Firstly, the flowchart of the semantic analysis is introduced. Secondly, the rigid reasoning and the soft reasoning are discussed in detail. Then the quotation judgment is presented for our experiment. Subsequently the bases and the modules in the system and their relations are illustrated. The experiment shows that it is feasible and practical method for semantic analysis

关键词： Flowcharts Expert systems Systems engineering and theory Yttrium information technology Intelligent control Databases Natural language processing Artificial intelligence Speech synthesis

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A Distributionally Robust Model Predictive control for Static and Dynamic Uncertainties in Smart Grids

arXiv

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arXiv 2024年

作者： Li, Qi Shi, Ye Jiang, Yuning Shi, Yuanming Wang, Haoyu Poor, H. Vincent The Institute of Mathematical Sciences ShanghaiTech University China The School of Information Science and Technology ShanghaiTech University China The Automatic Control Laboratory EPFL Switzerland The Department of Electrical Engineering Princeton University PrincetonNJ08544 United States

The integration of various power sources, including renewables and electric vehicles, into smart grids is expanding, introducing uncertainties that can result in issues like voltage imbalances, load fluctuations, and power losses. These challenges negatively impact the reliability and stability of online scheduling in smart grids. Existing research often addresses uncertainties affecting current states but overlooks those that impact future states, such as the unpredictable charging patterns of electric vehicles. To distinguish between these, we term them static uncertainties and dynamic uncertainties, respectively. This paper introduces WDR-MPC, a novel approach that stands for two-stage Wasserstein-based Distributionally Robust (WDR) optimization within a Model Predictive control (MPC) framework, aimed at effectively managing both types of uncertainties in smart grids. The dynamic uncertainties are first reformulated into ambiguity tubes and then the distributionally robust bounds of both dynamic and static uncertainties can be established using WDR optimization. By employing ambiguity tubes and WDR optimization, the stochastic MPC system is converted into a nominal one. Moreover, we develop a convex reformulation method to speed up WDR computation during the two-stage optimization. The distinctive contribution of this paper lies in its holistic approach to both static and dynamic uncertainties in smart grids. Comprehensive experiment results on IEEE 38-bus and 94-bus systems reveal the method's superior performance and the potential to enhance grid stability and reliability. Copyright © 2024, The Authors. All rights reserved.

关键词： Predictive control systems

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Identification of primary shape descriptors on 3D scanned particles

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica Electrical engineering and computer science 2018年第2期62卷 59-64页

作者： Ludmány, Balázs Domokos, Gábor Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics P.O.B. 91 BudapestH-1521 Hungary MTA-BME Morphodynamics Research Group P.O.B. 91 BudapestH-1521 Hungary Department of Mechanics Materials and Structures Faculty of Architecture Budapest University of Technology and Economics P.O.B. 91 BudapestH-1521 Hungary

The number of global mechanical equilibria as a shape descriptor (among others, for sedimentary particles) is at the forefront of current geophysical research. Although the technology is already available to provide scanned, 3D images of the particles (appearing as fine spatial discretization of smooth surfaces), nevertheless, the automated identification and measurement of global equilibria on such 3D images has not been solved so far. The main difficulty lies in the algorithmic distinction between local equilibria (associated with the small un-evenness of the pebble's surface) and global equilibria, associated with the overall shape. The former are easily measured, however, only the latter provide meaningful physical information. Here we provide and illustrate an algorithm to detect global equilibrium points on a finely discretized, polyhedral surface provided by 3D scan of sedimentary particles. © Budapest University of technology and Economics. All rights reserved.

关键词： Sedimentology

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Model-Based Reinforcement Learning for Robotic Arm control with Limited Environment Interaction

Model-Based Reinforcement Learning for Robotic Arm Control w...

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IEEE International Conference on Cyber technology in Automation, control, and Intelligent Systems

作者： Yi Chen Xiao Sun Song Zheng Weibing Huang Sheng Zeng Dan Chen Zhezhuang Xu Education Department of Fujian Province Key Laboratory of Industrial Automation Control Technology and Information Processing College of Electrical Engineering and Automation Fuzhou University Fuzhou China Evomotion Co. Ltd. Guangdong Shenzhen China

Reinforcement Learning (RL) has been applied to robotic arm control, which enables the agent to learn an effective policy to solve complex tasks. However, it requires constant interaction with the environment leading to low sample efficiency. In this paper, we propose a robotic arm control approach based on planning via lookahead search, which is a model-based RL algorithm to improve the sample efficiency. The approach builds an environment model in order to obtain the dynamics of the environment. Thus the model can be used to plan future actions by a tree-based search. The experiments show that our approach can solve the task of robotic arm control with less environmental samples.

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Foreign Material Detection and Localization in Stored Grain with Passive RFID Tag Arrays

Foreign Material Detection and Localization in Stored Grain ...

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IEEE International Conference on RFID-technology and Applications (RFID-TA)

作者： Erbo Shen Weidong Yang Xuyu Wang Shiwen Mao Henan Key Laboratory of Grain Photoelectric Detection & Control Henan University of Technology Zhengzhou China Kaifeng University Kaifeng China College of Information Science & Engineering Henan University of Technology Zhengzhou China Knight Foundation School of Computing & Information Sciences Florida International University Miami FL USA Department of Electrical and Computer Engineering Auburn University Auburn AL USA

In the early stage of harvesting, transportation, and storage, the grain could be mingled with clods from the field, metal pieces from aging machines, and other objects of foreign material, which will greatly influence the grain quality and food security. In this paper, we propose a novel radio frequency (RF) sensing system termed TagSee, which leverages passive RFID tag arrays. The goal is to simultaneously sense the presence of foreign materials and locate their locations in the 3D space, to automatically monitor the stored grain. Specifically, we use RFID received signal strength (RSS) and phase as features for foreign material detection. To design the TagSee system, we first introduce a sensing space division method. Then, an Euclidean Distance Ratio (EDR) algorithm and a heuristic method are proposed to achieve high localization accuracy. Experimental results show that TagSee can effectively detect foreign materials in stored grain and achieve a centimeter-level localization accuracy.

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An LMI Approach to Exponential Stability Analysis of Neural Networks with Time-Varying Delay

An LMI Approach to Exponential Stability Analysis of Neural ...

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IEEE Region 10 International Conference TENCON

作者： Wu-hua Chen Xiaomei Lu Zhi-hong Guan Wei Xing Zheng College of Mathematics and Information Science Guangxi University Nanning Guangxi China Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan Hubei China School of QMMS University of Western Ontario Penrith NSW Australia

This paper focuses on the problem of delay- dependent stability analysis of neural networks with variable delay. Two types of variable delay are considered: one is differentiable and has bounded derivative; the other one is continuous and may vary very fast. By introducing a new type of Lyapunov-Krasovskii functional, new delay-dependent sufficient conditions for exponential stability of delayed neural networks are derived in terms of linear matrix inequalities. We also obtain delay-independent stability criteria. These criteria can be tested numerically and very efficiently using interior point algorithms. Two examples are presented which show our results are less conservative than the existing stability criteria.

关键词： Stability analysis Neural networks Sufficient conditions Delay effects Stability criteria Linear matrix inequalities Lyapunov method Artificial neural networks Convergence Circuit stability

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