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15th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2020

作者： Jiang, Han-Jing Wang, Yan-Bin Huang, Yabing Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China Institute of Artificial Intelligence School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China College of Computer Science and Technology Zhejiang University Hangzhou315000 China Department of Pathology Renmin Hospital of Wuhan University Wuhan430060 China

ISBN: (纸本)9789811613531

Drug-disease association depicts the accessibility landscape of the association at the molecular level, thereby revealing the intermolecular reaction in the process of drug reposition. However, the scarcity of drug-disease association data often complicates the drug reposition. In this work, we present a method for predicting drug-disease association, which is called drug-disease association prediction via Gaussian interaction profile kernel and long short-term memory network (G-LSTM). G-LSTM combines a recurrent network framework with a Gaussian interaction profile kernel to learn underlying features that accurately characterize drug-disease-association data. We have verified G-LSTM models on the two benchmark datasets Fdataset and Cdataset, respectively. The experimental results show that the predictive performance was significantly improved, with AUC of 0.9527 and 0.9705, respectively. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Long short-term memory

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Label Cluster Chains for Multi-Label Classification

arXiv

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arXiv 2024年

作者： Gatto, Elaine Cecília Nakano, Felipe Kenji Read, Jesse Ferrandin, Mauri Cerri, Ricardo Vens, Celine Department of Computer Science Federal University of São Carlos SP São Carlos13565-905 Brazil Faculty of Medicine Katholieke Universiteit Leuven West Flanders Kortrijk8500 Belgium École Polytechnique Polytechnic Institute of Paris Palaiseau Paris91120 France Department of Control Automation and Computing Engineering Federal University of Santa Catarina SC Blumenau89036-002 Brazil Institute of Mathematical and Computing Sciences University of São Paulo SP São Carlos13566-590 Brazil

Multi-label classification is a type of supervised machine learning that can simultaneously assign multiple labels to an instance. To solve this task, some methods divide the original problem into several sub-problems (local approach), others learn all labels at once (global approach), and others combine several classifiers (ensemble approach). Regardless of the approach used, exploring and learning label correlations is important to improve the classifier predictions. Ensemble of Classifier Chains (ECC) is a well-known multi-label method that considers label correlations and can achieve good overall performance on several multi-label datasets and evaluation measures. However, one of the challenges when working with ECC is the high dimensionality of the label space, which can impose limitations for fully-cascaded chains as the complexity increases regarding feature space expansion. To improve classifier chains, we propose a method to chain disjoint correlated label clusters obtained by applying a partition method in the label space. During the training phase, the ground truth labels of each cluster are used as new features for all of the following clusters. During the test phase, the predicted labels of clusters are used as new features for all the following clusters. Our proposal, called Label Cluster Chains for Multi-Label Classification (LCC-ML), uses multi-label Random Forests as base classifiers in each cluster, combining their predictions to obtain a final multi-label classification. Our proposal obtained better results compared to the original ECC. This shows that learning and chaining disjoint correlated label clusters can better explore and learn label correlations. © 2024, CC BY.

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A Risk-Averse Just-In-Time Scheme for Learning-Based Operation of Microgrids With Coupled Electricity-Hydrogen-Ammonia Under Uncertainties

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IEEE Transactions on Sustainable Energy 2025年

作者： Li, Longyan Ning, Chao Pan, Guangsheng Zhang, Leiqi Gu, Wei Zhao, Liang Du, Wenli Shahidehpour, Mohammad Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China School of Electrical Engineering Southeast University Nanjing210096 China Zhejiang Key Laboratory of Distributed Generations and Microgrid Technology State Grid Zhejiang Electric Power Research Institute Hangzhou310014 China Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology China Department of Electrical and Computer Engineering Illinois Institute of Technology ChicagoIL60616 United States

This paper proposes a Risk-Averse Just-In-Time (RAJIT) operation scheme for Ammonia-Hydrogen-based Micro-Grids (AHMGs) to boost electricity-hydrogen-ammonia coupling under uncertainties. First, an off-grid AHMG model is developed, featuring a novel multi-mode ammonia synthesis process and a hydrogen-ammonia dual gas turbine with tunable feed-in ratios. Subsequently, a state-behavior mapping strategy linking hydrogen storage levels with the operation modes of ammonia synthesis is established to prevent cost-ineffective shutdowns. The proposed model substantially improves operational flexibility but results in a challenging nonlinear fractional program. Based upon this model, a data-driven RAJIT scheme is developed for the real-time rolling optimization of AHMGs. Unlike conventional one-size-fits-all schemes using one optimization method throughout, the data-driven RAJIT intelligently switches between cost-effective deterministic optimization and risk-averse online-learning distributionally robust optimization depending on actual risk profiles, thus capitalizing on the respective strengths of these two optimization methods. To facilitate the solution of the resulting nonlinear program, we develop an equivalent-reformulation-based solution methodology by leveraging a constraint-tightening technique. Numerical simulations demonstrate that the proposed scheme guarantees safety and yields an overall cost reduction up to 14.6% compared with several state-of-the-art methods. © 2025 IEEE.

关键词： Ammonia

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Implementation of a Human-Robot Collaboration System Based On Smart Hand Gesture and Speech Recognition

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Journal of the Chinese Society of Mechanical Engineers, Transactions of the Chinese institute of Engineers, Series C/Chung-Kuo Chi Hsueh Kung Ch'eng Hsuebo Pao 2020年第6期41卷 755-762页

作者： Chen, Shang-Liang Huang, Li-Wu Huang, Chung-Chi Lee, Feng-Chi Huang, Ho-Chuan Chen, Chien-Yu Institute of Manufacturing Information and Systems National Cheng Kung University Tainan70101 Taiwan Department of Automation and Control Engineering Far East University Tainan74448 Taiwan Department of Mechatronics Control Industrial Technology Research Institute Hsinchu310 Taiwan Department of Intelligent Commerce National Kaohsiung University of Applied Sciences Kaohsiung824 Taiwan Computer Science and Information Engineering National University of Tainan Tainan70005 Taiwan

With the development of artificial intelligence technology, the robot arm will be applied in more fields, undertake more work, and become an important assistant of humans. Especially in the manufacturing industry, if a perfect human-robot cooperation (HRC) model can be developed, in which the engineer is responsible for complex operations and monitoring the production process and the robot arm is responsible for highly repetitive and tiring work, the flexibility of the manufacturing process can be improved, the risk of personnel injury can be reduced, and the production line productivity can be improved. To realize the human-robot collaboration system that can be applied in various fields, the technologies of robot arm control, human-robot interaction (HRI), Radio Frequency Identification, machine-to-machine communication, and automatic speech recognition (ASR), etc. are combined in this research. Besides, the HRC in intelligent manufacturing is taken as the demonstration result of this research. In this application example, the human-robot interaction function is realized through smart hand gesture and speech recognition technology, which enables the user to communicate commands to the robot arm most intuitively and easily. The robot arm can execute specific actions, provide processing prompts, or read corresponding motion control command macros according to different commands, to realize various processing contents required by users. © 2020, Chinese Mechanical Engineering Society. All right reserved.

关键词： Radio frequency identification (RFID)

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Design of ILC laws with conditions for stabilizing linear 2D discrete Roesser models

Design of ILC laws with conditions for stabilizing linear 2D...

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IEEE Conference on Decision and control

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)9781665467612

ISBN: (纸本)9781665467629

This paper considers the design of iterative learning control schemes by transforming the task into an equivalent problem of designing stabilizing control laws for the Roesser model for linear two-dimensional systems. Then, based on a non-conservative version of stability and stabilization conditions for linear 2D systems, a control law is designed based on linear matrix inequalities. In addition, some control performance indexes are improved by choosing the locations for the relevant transfer function, leading to faster convergence. Also, an additional linear matrix inequality constraint is developed to minimize the gain of designed controllers and facilitate their practical implementation. Furthermore, the problem of ILC control law design for strictly proper system dynamics using anticipative action. Finally, a numerical example demonstrates the effectiveness of the new results, including advantages when compared to the existing alternatives.

关键词： State feedback Uncertainty System dynamics Transfer functions Stability analysis Linear matrix inequalities Performance analysis

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Maneuver Classification for Road Vehicles with Constrained Filtering Techniques ⁎

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IFAC-PapersOnLine 2020年第2期53卷 15495-15500页

作者： Olivér Törö Tamás Bécsi Szilárd Aradi Máté Kolat Péter Gáspár Department of Control for Transportation and Vehicle Systems Budapest University of Technology and Economics Systems and Control Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences

Environment perception and situation awareness are keystones for autonomous road vehicles. The problem of maneuver classification for road vehicles in the context of multi-model state estimation under model uncertainty is addressed in this paper. The conventional approach is to define different motion models that match the desired type of movements. In this work we used a single motion model as a starting point and applied constraints to construct such filters that are fine tuned for the predefined maneuvers. The estimation is carried out in the interacting multiple model framework, where the elemental filters are constrained Kalman filters. To capture the characteristics of the considered maneuvers linear equality and non-equality state constraints were used. The performance of the proposed method is demonstrated in a simulation environment participating an observer and a maneuvering vehicle.

关键词： Manoeuvring target Road traffic Constraints Estimation algorithms Simulation Filtering

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Fault-tolerant cooperative control of networked discrete-event systems

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IFAC-PapersOnLine 2020年第4期53卷 123-128页

作者： Markus Zgorzelski Jan Lunze Institute of Automation and Computer Control Ruhr-Universität Bochum Universitätsstrasse 150 D-44780 Bochum Germany

Networked discrete-event systems like smart manufacturing systems consist of subsystems, which are physically coupled and digitally connected by a communication network. The subsystems are able to solve their local tasks autonomously and to cooperate with another subsystem if necessary. In the second situation, the network units of both subsystems initiate the cooperation via the communication network. The flexibility of the subsystems to solve autonomous and cooperative tasks demonstrates an important property that is required for manufacturing systems in Industry 4.0. The paper concerns the situation that a fault occurs within a subsystem, which has to be detected and the controller has to be adapted. To this aim, the subsystems are extended by a diagnostic unit and a reconfiguration unit. The diagnostic unit detects and identifies the fault, whereas the reconfiguration unit applies a locally reconfigured controller. It is shown that if the fault has the property to be networked reconfigurable, the fault is locally reconfigurable without affecting the overall system.

关键词： Networked discrete-event system network unit fault-tolerant control

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Cooperative control of a flexible manufacturing system

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IFAC-PapersOnLine 2020年第2期53卷 10423-10430页

作者： Markus Zgorzelski Jan Lunze Institute of Automation and Computer Control Ruhr-Universität Bochum Universitätsstrasse 150 D-44780 Bochum Germany

This paper considers networked discrete-event systems. Local state-feedback controllers enable each subsystem to reach local target states. Due to the physical restrictions between the subsystems, the local target states might not be reachable autonomously, but cooperatively with the help of other subsystems. Therefore, each subsystem is extended by a network unit, which detects and resolves possible physical restrictions. If cooperation is necessary, the network units temporarily modify their local target states while applying situation-dependent communication. The proposed method is applied to the flexible manufacturing system HANS and its applicability to real-life systems is demonstrated by experimental results.

关键词： Networked discrete-event systems cooperative tracking control

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Asynchronous Distributed Optimization via ADMM with Efficient Communication

arXiv

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arXiv 2023年

作者： Rikos, Apostolos I. Jiang, Wei Charalambous, Themistoklis Johansson, Karl H. Department of Electrical and Computer Engineering Division of Systems Engineering Boston University BostonMA02215 United States Hong Kong Hong Kong Department of Electrical and Computer Engineering School of Engineering University of Cyprus Nicosia1678 Cyprus Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland Division of Decision and Control Systems KTH Royal Institute of Technology StockholmSE-100 44 Sweden Digital Futures United Kingdom

In this paper, we focus on an asynchronous distributed optimization problem. In our problem, each node is endowed with a convex local cost function, and is able to communicate with its neighbors over a directed communication network. Furthermore, we assume that the communication channels between nodes have limited bandwidth, and each node suffers from processing delays. We present a distributed algorithm which combines the Alternating Direction Method of Multipliers (ADMM) strategy with a finite time quantized averaging algorithm. In our proposed algorithm, nodes exchange quantized valued messages and operate in an asynchronous fashion. More specifically, during every iteration of our algorithm each node (i) solves a local convex optimization problem (for the one of its primal variables), and (ii) utilizes a finite-time quantized averaging algorithm to obtain the value of the second primal variable (since the cost function for the second primal variable is not decomposable). We show that our algorithm converges to the optimal solution at a rate of O(1/k) (where k is the number of time steps) for the case where the local cost function of every node is convex and not-necessarily differentiable. Finally, we demonstrate the operational advantages of our algorithm against other algorithms from the literature. © 2023, CC BY.

关键词： Cost functions

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FusionPlanner: A Multi-task Motion Planner for Mining Trucks via Multi-sensor Fusion

arXiv

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arXiv 2023年

作者： Teng, Siyu Li, Luxi Li, Yuchen Hu, Xuemin Li, Lingxi Ai, Yunfeng Chen, Long Department of Computer Science Hong Kong Baptist University Hong Kong Department of Computer Science BNU-HKBU United International College Zhuhai China The School of Artificial Intelligence Hubei University Wuhan China Waytous Inc. Haidian Distinct Beijing China Indianapolis United States School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences China

In recent years, significant achievements have been made in motion planning for intelligent vehicles. However, as a typical unstructured environment, open-pit mining attracts limited attention due to its complex operational conditions and adverse environmental factors. A comprehensive paradigm for unmanned transportation in open-pit mines is proposed in this research. Firstly, we propose a multi-task motion planning algorithm, called FusionPlanner, for autonomous mining trucks by the multi-sensor fusion method to adapt both lateral and longitudinal control tasks for unmanned transportation. Then, we develop a novel benchmark called MiningNav, which offers three validation approaches to evaluate the trustworthiness and robustness of well-trained algorithms in transportation roads of open-pit mines. Finally, we introduce the Parallel Mining Simulator (PMS), a new high-fidelity simulator specifically designed for open-pit mining scenarios. PMS enables the users to manage and control open-pit mine transportation from both the single-truck control and multi-truck scheduling perspectives. The performance of FusionPlanner is tested by MiningNav in PMS, and the empirical results demonstrate a significant reduction in the number of collisions and takeovers of our planner. We anticipate our unmanned transportation paradigm will bring mining trucks one step closer to trustworthiness and robustness in continuous round-the-clock unmanned transportation. Copyright © 2023, The Authors. All rights reserved.

关键词： Motion planning

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