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7th International Conference on control, Automation and Robotics (ICCAR)

作者： Yang, Jin Peng, Gang Huazhong Univ Sci & Technol Minist Educ Key Lab Image Proc & Intelligent Control Wuhan Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan Peoples R China

ISBN: (纸本)9781665449861

Prioritized experience replay (PER) chooses the experience data based on the value of Temporal-Difference (TD) error, it can improve the utilization of experience in deep reinforcement learning based methods. But since the value of TD error needs to be calculated when experience data sampled at each time, so the computational complexity of PER is high. And the hyperparameters in PER also affect the learning process. The hyperparameters need to be adjusted carefully. To cope above problems, we propose meta-learning-based experience replay buffer separation (MSER) in this paper. Firstly, the original experience replay buffer is divided into a successful experience buffer and a failure experience buffer, and the experience data of successful exploration or failure exploration are stored respectively. Secondly, the experience data is sampled randomly from two experience replay buffers according to a ratio, and the ratio is learned through the neural network designed by us. Finally, we conduct experiments in a simulation environment for trajectory planning of robot manipulator in V-REP. Extensive experiments show that the MSER proposed is capable of improving convergence rate by up to 9.1% in DDPG, compared to DDPG with PER. The convergence mean reward rises by up to 3.3% and the standard deviation reduce by 16.9%. In the evaluation, the success rate of trajectory planning for robot manipulator is up to 99%.

关键词： experience replay robot manipulator meta learning deep reinforcement learning

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Online energy management optimization of hybrid energy storage microgrid with reversible solid oxide cell: A model-based study

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JOURNAL OF CLEANER PRODUCTION 2023年 423卷

作者： Zhou, Yihuan Xia, Zhiping Liu, Xingbo Deng, Zhonghua Fu, Xiaowei Kupecki, Jakub Jin, Bing Li, Xi Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Educ Minist Wuhan 430074 Hubei Peoples R China Hubei Huazhong Elect Power Technol Dev Co Ltd Wuhan 430074 Hubei Peoples R China Shenzhen Huazhong Univ Sci & Technol Res Inst Shenzhen 518055 Guangdong Peoples R China Huazhong Univ Sci & Technol Belt & Rd Joint Lab Measurement & Control Technol Wuhan 430074 Hubei Peoples R China Inst Power Engn Ctr Hydrogen Technol CTH2 Augustowka 36 PL-02981 Warsaw Poland Inst Power Engn Mory 8 PL-01330 Warsaw Poland Univ Calif Irvine Natl Fuel Cell Res Ctr NFCRC Engn Lab Facil Irvine CA 92697 USA

Microgrids (MGs) that contain a reversible solid oxide cell (rSOC) system and battery energy storage system (BESS) are gaining prominence in terminal load supply and renewable energy consumption. However, the economy and durability are highly dependent on the reliability of its energy management system (EMS). Herein, a model-based online optimal control strategy is proposed to obtain optimal schedule decisions for EMS. Firstly, the aging of BESS and the efficiency of the rSOC system are considered simultaneously, and are modeled in detail. Subsequently, the optimal energy management (OEM) is formulated as a multi-objective optimization problem based on the constructed model. On this basis, to improve the efficiency and accuracy of the optimization search, a novel multi-objective evolutionary algorithm is proposed and verified, which hybridizes the non-dominated sorting genetic algorithm-II and tabu search, and incorporates improved crossover and mutation operations. Afterwards, data from a commercial user in Ningxia, China was used for the case study. The results show that the proposed control strategy can effectively slow down the aging of BESS and improve the efficiency of the rSOC system compared to the rule-based control strategy. Furthermore, compare with the rule-based control and economic dispatching strategy, the MG obtained a higher self-sufficiency rate (93.28%) and a shorter payback period (14.57 years) under the proposed OEM strategy.

关键词： Microgrid Reversible solid oxide cell Energy management system Multi -objective optimization Optimal energy management

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Fully Decoupled control of the Machine Directional Register in Roll-to-Roll Printing System

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2021年第10期68卷 10007-10018页

作者： Chen, Zhihua Zhang, Tao Zheng, Ying Wong, David Shan-Hill Deng, Zhonghua Guangzhou Univ Inst Comp Sci & Technol Guangzhou 510006 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Informat Proc & Intelligent Control Wuhan 430074 Peoples R China Natl Tsing Hua Univ Dept Chem Engn Hsinchu 30013 Taiwan

Roll-to-roll (R2R) printing systems provide a continuous process of thin, flexible material (called web) through printing cylinders, where the required patterns are printed on the web. Tension fluctuation caused by the upstream register control quantity may lead to the downstream register errors. Thus, it is a challenge to develop a register control algorithm to remove the couplings among the angular velocity, tension fluctuation, and register error. In this article, the register error is defined as the marks position misalignment between the first and the current printing unit. Based on the definition, amathematical model of registration is derived. Based on the model, a fully decoupled proportional-derivative (FDPD) control algorithm is proposed to completely remove the coupling between the upstream register control quantity and the downstream register error. Simulations and experiments are carried out to demonstrate the effectiveness of the proposed control algorithm. Compared with the other compensation control methods, FDPD is a complete decoupling control method, which can control the register errors of all downstream printing units (more than seven printing units) within +/- 0.05 mm, even if the upstream printing unit has a 3 mm register error. Decoupling formula included in the FDPD control is a first-order compensation formula, which is easy to implement in the actual industry. Furthermore, the proposed FDPD can deal with the situation where two adjacent gravure cylinders have different web lengths, which is not taken into account by other control methods.

关键词： Fully decoupled proportional-derivative (FDPD) control algorithm R2R printing system register control tension fluctuation

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Learning-based hierarchical control for fault-tolerant cooperation of networked marine surface vehicles

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INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR control 2022年第9期32卷 5717-5740页

作者： Liang, Chang-Duo Ge, Ming-Feng Wang, Leimin Liu, Zhi-Wei Li, Bo China Univ Geosci Sch Mech Engn & Elect Informat Wuhan 430074 Peoples R China Hubei Normal Univ Sch Mechatron & Control Engn Huangshi Hubei Peoples R China Cent South Univ Sch Automat Changsha Peoples R China China Univ Geosci Sch Automat Wuhan Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Minist Educ Wuhan Peoples R China

In this article, an efficient hierarchical control framework is proposed to address the cooperation problems (e.g., consensus tracking, formation tracking, and time-varying formation tracking) for the networked marine surface vehicles in the presence of external disturbances, actuator faults and failures. Based on this framework, several learning-based hierarchical control algorithms are developed, involving an iterative learning-based estimator and a local observer-based finite-time controller. The estimator is designed to achieve sufficiently precise estimation of the leader states through enough iterations, while the observer-based finite-time controller is used to observe and compensate the dynamic uncertainties as well as stabilize the error states in a finite time. By using the theories of Hurwitz, Schur, and Lyapunov stability, the sufficient conditions for guaranteeing the convergence of these learning-based hierarchical control algorithms are derived. Finally, numerical simulations are performed on the Cyber-Ships II to verify the effectiveness of the presented algorithms.

关键词： actuator faults and failures fault-tolerant cooperation learning-based hierarchical control algorithm networked marine surface vehicles

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Force sensorless admittance control of body weight support system

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ADVANCED ROBOTICS 2021年第7期35卷 425-436页

作者： Huo, Jun Huang, Jian Tu, Xikai Fu, Zhongzheng Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Minist Educ Image Proc & Intelligent Control Key Lab Wuhan Peoples R China Hubei Univ Technol Sch Mech Engn Wuhan Peoples R China Chongqing Univ Technol Coll Vehicle Engn Chongqing Peoples R China

The effectiveness of rehabilitation treatment with the Body Weight Support (BWS) system has been demonstrated in patients with stroke and spinal cord injury. Many recent studies used expensive force sensors to realize the force control, which plays an important role in a BWS system. To reduce the system cost and complexity, and overcome some shortcomings of force sensors like measurement noise and lag, a force sensorless admittance control method is proposed. Then, an active BWS platform has been designed to verify the effect of the sensorless control method. The robust stability of the BWS system was proved through the small gain theorem. Human walking experiments assisted by the BWS system were conducted. It turns out that the estimated force is in close agreement with the value measured by the force sensor. The proposed controller achieved a control deviation of less than 10% around a desired mass offload during the experiments. It was validated effective for the proposed controller in accurate force control.

关键词： BWS system force estimation admittance control stability analysis small gain theorem

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Indirect effects among biodiversity loss of mutualistic ecosystems

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National Science Open 2022年第2期1卷 8-18页

作者： Guangwei Wang Xueming Liu Guanrong Chen Hai-Tao Zhang School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent ControlHuazhong University of Science and TechnologyWuhan 430074China State Key Lab of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Department of Electrical Engineering City University of Hong KongHong KongChina

Drastic reduction in biodiversity has been a severe threat to ecosystems,which is exacerbated when losing few species leads to disastrous and even irreparable ***,revealing the mechanism underlying biodiversity loss is of uttermost *** this study,we show that abundant indirect interactions among mutualistic ecosystems are critical in determining species’*** topological and ecological characteristics,we propose an indicator derived from a dynamic model to identify keystone species and quantify their influence,which outperforms widely-used indicators like degree in realistic and simulated ***,we demonstrate that networks with high modularity,heterogeneity,biodiversity,and less intimate interactions tend to have larger indirect effects,which are more amenable in predicting decline of biodiversity with the proposed *** findings shed some light onto the influence of apposite biodiversities,paving the way from complex network theory to ecosystem protection and restoration.

关键词： biodiversity indirect effect complex network mutualism

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An enhanced fireworks algorithm and its application in fault detection of the displacement sensor

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Measurement: Sensors 2024年 34卷

作者： Hao, Tianlu Ma, Zhuang Wang, Yaping Computer Center of Tangshan University Tangshan063000 China Key Lab of Intelligent Data Information Processing and Control of Hebei Province Tangshan University Tangshan063000 China Tangshan No.1 Middle School in Hebei Province Tangshan063000 China

Regarding the fault detection problem of the displacement sensor, an enhanced fireworks algorithm with information crossover and conversion factor (EFWA-IC) is proposed in this paper. In EFWA-IC, an information crossover strategy is proposed to maintain population diversity. This strategy is based on the predatory behavior of carnivores in nature. In addition, a conversion factor is set to control whether the explosion operator is executed or not to provide a more reasonable search. To fully evaluate the performance of EFWA-IC, a range of tests are carried out based on the CEC2017 and 23 classical test functions. The results show that the performance of EFWA-IC is better than other state-of-the-art optimization algorithms in terms of solution accuracy, convergence speed, and stability. Finally, EFWA-IC is utilized to optimize the particle filter (PF) to establish a fault detection model of displacement sensor in the continuous casting mold. The simulation experiment result of field data manifests that EFWA–IC–PF can accurately detect faults in the displacement sensor. For bias faults, the RMSE of the EFWA–IC–PF model is 0.14468, and the false alarm rate (FAR) and missed detection rate (MDR) are 1 % and 0.5 %, respectively. For stuck faults, the RMSE is 1.00148, and the FAR and MDR are 0.88 % and 1 %, respectively. © 2024 The Authors

关键词： Fault detection

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Multistability of Fractional-Order Neural Networks With Unbounded Time-Varying Delays

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2021年第1期32卷 177-187页

作者： Zhang, Fanghai Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan 430074 Peoples R China Educ Minist China Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

This article addresses the multistability and attraction of fractional-order neural networks (FONNs) with unbounded time-varying delays. Several sufficient conditions are given to ensure the coexistence of equilibrium points (EPs) of FONNs with concave-convex activation functions. Moreover, by exploiting the analytical method and the property of the Mittag-Leffler function, it is shown that the multiple Mittag-Leffler stability of delayed FONNs is derived and the obtained criteria do not depend on differentiable time-varying delays. In particular, the criterion of the Mittag-Leffler stability can be simplified to M-matrix. In addition, the estimation of attraction basin of delayed FONNs is studied, which implies that the extension of attraction basin is independent of the magnitude of delays. Finally, three numerical examples are given to show the validity of the theoretical results.

关键词： Delays Stability criteria Biological neural networks Asymptotic stability Numerical stability Attraction fractional-order neural networks (FONNs) Mittag-Leffler stability multistability unbounded time-varying delays

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Self-supervised Multi-frame Monocular Depth Estimation with Pseudo-LiDAR Pose Enhancement

Self-supervised Multi-frame Monocular Depth Estimation with ...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Wenhua Wu Guangming Wang Jiquan Zhong Hesheng Wang Zhe Liu MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University Shanghai China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Insititute of Medical Robotics Shanghai Jiao Tong University Shanghai China

Depth estimation is one of the most important tasks in scene understanding. In the existing joint self-supervised learning approaches of depth-pose estimation, depth estimation and pose estimation networks are independent of each other. They only use the adjacent image frames for pose estimation and lack the use of the estimated geometric information. To enhance the depth-pose association, we propose a monocular multi-frame unsupervised depth estimation framework, named PLPE-Depth. There are a depth estimation network and two pose estimation networks with image input and pseudo-LiDAR input. The main idea of our approach is to use the pseudo-LiDAR reconstructed from the depth map to estimate the pose of adjacent frames. We propose depth re-estimation with a better pose between the image pose and the pseudo-LiDAR pose to improve the accuracy of estimation. Besides, we improve the reconstruction loss and design a pseudo-LiDAR pose enhancement loss to facilitate the joint learning. Our approach enhances the use of the estimated depth information and strengthens the coupling between depth estimation and pose estimation. Experiments on the KITTI dataset show that our depth estimation achieves state-of-the-art performance at low resolution. Our source codes will be released on https://***/IRMVlabIPLPE-Depth.

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3D Instances as 1D Kernels

arXiv

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arXiv 2022年

作者： Wu, Yizheng Shi, Min Du, Shuaiyuan Lu, Hao Cao, Zhiguo Zhong, Weicai Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of AIA Huazhong University of Science and Technology China Huawei CBG Consumer Cloud Service Search & Maps BU China

We introduce a 3D instance representation, termed instance kernels, where instances are represented by one-dimensional vectors that encode the semantic, positional, and shape information of 3D instances. We show that instance kernels enable easy mask inference by simply scanning kernels over the entire scenes, avoiding the heavy reliance on proposals or heuristic clustering algorithms in standard 3D instance segmentation pipelines. The idea of instance kernel is inspired by recent success of dynamic convolutions in 2D/3D instance segmentation. However, we find it non-trivial to represent 3D instances due to the disordered and unstructured nature of point cloud data, e.g., poor instance localization can significantly degrade instance representation. To remedy this, we construct a novel 3D instance encoding paradigm. First, potential instance centroids are localized as candidates. Then, a candidate merging scheme is devised to simultaneously aggregate duplicated candidates and collect context around the merged centroids to form the instance kernels. Once instance kernels are available, instance masks can be reconstructed via dynamic convolutions whose weights are conditioned on instance kernels. The whole pipeline is instantiated with a dynamic kernel network (DKNet). Results show that DKNet outperforms the state of the arts on both ScanNetV2 and S3DIS datasets with better instance localization. Code is available: https://***/W1zheng/DKNet. Copyright © 2022, The Authors. All rights reserved.

关键词： Pipelines

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