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检索条件"机构=Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System"

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Design of a Novel Autonomous Docking system With a Supporting Robotic Fish

Design of a Novel Autonomous Docking System With a Supportin...

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2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023

作者： Dong, Huijie Zhao, Chunyang Qiao, Tiezhu Wang, Jian Chen, Di Meng, Yan Yu, Junzhi Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan030024 China Chinese Academy of Sciences Laboratory of Cognitive and Decision Intelligence for Complex System Institute of Automation Beijing100190 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Beijing100871 China Guangdong Ocean University College of Electronics and Information Engineering Zhanjiang524088 China

ISBN: (纸本)9798350327182

Underwater supporting robots serving as a relay of energy supplements and communication for other underwater equipment are promising for ocean exploration, development, and protection. This paper proposes a novel autonomous docking system centered on a designed supporting robotic fish named 'CourierFish'. Specifically, CourierFish is capable of docking with a surface dock station for supplying itself and docking with a seafloor platform for supporting equipment in the platform. A visual navigation scheme integrating LED and ArUco markers is presented for accurate localization. The control approach for docking motion is also illustrated. Simulations and aquatic experiments are performed to verify the feasibility of the proposed docking system. The obtained results lay a solid foundation for the construction of various underwater equipment and robot networks. © 2023 IEEE.

关键词： Fish

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Trajectory-prediction-based Dynamic Tracking of a UGV to a Moving Target under Multi-disturbed Conditions

Trajectory-prediction-based Dynamic Tracking of a UGV to a M...

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IEEE International Conference on Robotics and automation (ICRA)

作者： Jinge Si Bin Li Yongkang Xu Liang Wang Chencheng Deng Shoukun Wang Junzheng Wang State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology School of Automation Beijing China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Tracking dynamic targets poses a significant challenge for Unmanned Ground Vehicles (UGVs). Existing methods often lack research on multi-disturbed conditions. To address this issue, we propose a trajectory-prediction-based dynamic tracking scheme, which includes target localization, trajectory prediction, and UGV control. Firstly, an estimation algorithm based on the Extended Kalman Filter (EKF) is employed to mitigate noise and estimate the absolute states of the target accurately. To enhance robustness, we present an Adaptive Trajectory Prediction (ATP) algorithm based on prediction anchors. In this method, a quantization standard for trajectory disturbance is designed for adaptive control. Subsequently, we iteratively solve prediction anchor points based on two motion models to robustly predict the target trajectory even in the presence of unknown disturbances. Finally, the Linear Time-Varying Model Predictive control (LTV-MPC) is utilized in the UGV controller for dynamic tracking. Experimental results demonstrate that the ATP exhibits superior prediction robustness and accuracy in perturbed environments compared to other prediction algorithms. In addition, the proposed scheme effectively achieves dynamic tracking of the Unmanned Aerial Vehicle (UAV) by the UGV under multi-disturbed conditions. Specifically, when the target moves at a speed of 1.0 m/s, the UGV can maintain a tracking error within 0.346 m.

关键词： Target tracking Accuracy Heuristic algorithms Noise Prediction algorithms Autonomous aerial vehicles Robustness

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Model Predictive control of Decomposition Furnace Based on Equivalent-Input-Disturbances

Model Predictive Control of Decomposition Furnace Based on E...

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Chinese automation Congress (CAC)

作者： WeiKang Wu Gang Yu Wangyong He Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Automation China University of Geoscience Wuhan China Huaxin Cement Technology Management(Wuhan) Wuhan China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

In the cement production process, the decomposer outlet temperature control faces challenges such as large time delay and multiple disturbances. A general control system cannot handle time delay and disturbances effectively at the same time. Therefore, in this paper, we consider the problem of disturbances in time-delay systems and suppress the disturbances present in the outlet temperature control of the decomposer by combining equivalent-input-disturbance (EID) and Model Predictive control (MPC), where EID can estimate the disturbances and apply them to the input channels of the system, which do not require any information about the disturbances. Finally simulations are carried out in the catabolizer system and the results indicate that this system is able to suppress the perturbations effectively in time delay systems.

关键词： Delay effects Perturbation methods Optimal control Production Predictive models Aerospace electronics Mathematical models Temperature control State estimation Predictive control

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Auto-Regressive with Exogenous Input Modelling Based Model Predictive control of Cement Grate Cooler

Auto-Regressive with Exogenous Input Modelling Based Model P...

引用

Chinese automation Congress (CAC)

作者： Tian Zhang Gang Yu Wangyong He Renjie Gui Weikang Wu Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Automation China University of Geoscience Wuhan China Huaxin Cement Technology Management(Wuhan) Wuhan China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

In the cement production process, the speed of grate coolers directly affects the residence time and cooling effect of cement clinker. Its effective control is of great significance to ensuring cement quality. But the adjustment of grate speed is a complex process, involving moderate cooling air, uniform clinker thickness, regulated output and other constraints. In this study, an Auto-Regressive with exogenous input (ARX) grate cooler prediction model is developed using a data-driven approach based on a company's cement production line, a model predictive control (MPC) approach is employed for the purpose of optimising the speed of the grate cooler based on the ARX model. The results demonstrate that the method of MPC exhibits greater stability than the method of PID, and that MPC technology has good efficacy and superiority in the adjustment of grate speed.

关键词： Kilns Cooling Cement industry Velocity control Production Switches Predictive models control systems Stability analysis Predictive control

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Identification and Prediction of Microvascular Invasion in Hepatocellular Carcinoma Based on Multiple Sequence Fusion Images

Identification and Prediction of Microvascular Invasion in H...

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Chinese control Conference (CCC)

作者： Mingguang Lu Yuan Zhu School of Automation China University of Geosciences Wuhan Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Hepatocellular carcinoma (HCC) is one of the most difficult diseases to be treated fundamentally in the medical field in today’s world, and the recurrence rate of HCC has been increasing year by year in recent years. The study on the identification and prediction of microvascular invasion phenomenon (MVI) in hepatocellular carcinoma is beneficial to the postoperative prevention of hepatocellular carcinoma patients, which can greatly improve the survival probability of patients after surgery. In this study, a new MVI prediction method (MSF-GWO-GPR) was proposed, which combines the multi-sequence image features of imaging histology, sifts out the unimportant features through the T-test method and the dimensionality reduction of Lasso regression, and establishes the multi-sequence Gaussian process regression (GPR) prediction model for data fusion, and combined with the Gray Wolf Optimization (GWO) algorithm to design a suitable optimization objective function to optimize the hyper-parameters in the GPR, in order to get better prediction results. Compared with the existing methods, the data from different sequences of MRI images are selected for fusion in this study, which makes the feature data richer and more complete, and the model applicability is better; moreover, by optimizing the hyperparameters in the model through the GWO, the model can be made more accurate, reduce the risk of misidentified prediction, and improve the accuracy rate. The experimental results show that MSF-GWO-GPR outperforms widely used machine learning methods in terms of accuracy, F1 score, precision, recall and AUC metrics. This may provide a new idea for the identification and prediction of MVI in hepatocellular carcinoma.

关键词： Liver cancer Accuracy Magnetic resonance imaging Prevention and mitigation Surgery Predictive models Feature extraction

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Investigation of a tunnel magnetoresistance based vector magnetometer for magnetic anomaly detection 2

Investigation of a tunnel magnetoresistance based vector mag...

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2022 2nd International Conference on advanced Materials and Mechatronics, ICAMM 2022

作者： Wang, Hongpeng Yang, Ruiping Luo, Wang Ge, Jian Liu, Huan Dong, Haobin School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

The development of high-performance and miniaturized magnetometers is important for small-scale target magnetic anomaly detection. In this work, a miniaturized three-axis vector magnetometer based on the tunnel magnetoresistance (TMR) technique is investigated for magnetic anomaly detection. First, the miniaturized three-axis TMR vector magnetometer is constructed, and then, the limit of detection tests and the magnetic anomaly detection tests are performed. The indoor experimental results show that the proposed magnetometer can capture the magnetic anomalies higher than 3.9 nT, with the low-frequency equivalent magnetic noise of 46.89 pT/√Hz@1Hz. The outdoor experimental results show that the proposed magnetometer can effectively detect small-scale magnetic targets such as hammers at a distance of about 1.5 m. With the advantages of small size, low power consumption, and high magnetic measurement sensitivity, the TMR magnetometer has great application prospects for long-term magnetic anomaly monitoring, high-density magnetic imaging, and other fields. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Magnetometers

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Fixed-Time and Preassigned-Time Synchronization of Delayed Inertial Neural Networks 36

Fixed-Time and Preassigned-Time Synchronization of Delayed I...

引用

36th Youth Academic Annual Conference of Chinese Association of automation, YAC 2021

作者： Zeng, Kan Wang, Leimin Cheng, Jiajun China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Automation Wuhan430074 China

ISBN: (纸本)9781665437127

This paper investigates the fixed-Time synchronization (FXTS) and the preassigned-Time synchronization (PATS) of inertial neural networks (INNs) by improved control strategies. Firstly, using the order-reduce method, a proper Lyapunov function is constructed and a FXTS controller is designed. Then, some novel conditions for TXTS of INNs are derived and a more precise estimate for the settling time are provided. Moreover, depending on the FXTS, another PATS controller is proposed, with which the PATS of INNs is also achieved. Finally, the correctness and validity of the FXTS and PATS results are illustrated by a numerical example. © 2021 IEEE.

关键词： Lyapunov functions

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Fabrication and Path Following control of a Magnetic Soft Microrobot 8

Fabrication and Path Following Control of a Magnetic Soft Mi...

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8th International Conference on control Science and systems Engineering, ICCSSE 2022

作者： Tang, Jianhui Zhang, Pan Wu, Jundong Wang, Yawu School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9781665484138

Magnetically-controlled soft microrobots have great application prospects because of small size, flexible motion and wireless control. In this paper, a magnetically-controlled soft microrobot is designed and fabricated. In order to achieve its path-following control, two open-loop control strategies and a closed-loop one are developed. Especially, for the closed-loop control strategy, we present the image processing method and the pure pursuit algorithm, where the former is used to obtain the position and posture of the microrobot required for the latter. Finally, the developed open-loop and closed-loop control strategies are verified by carrying out the experiments. These methods are promising in numerous applications because of the ease of implementation. © 2022 IEEE.

关键词： Image processing

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Speech Emotion Recognition Based on Clustering Assistance

Speech Emotion Recognition Based on Clustering Assistance

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2022 Chinese automation Congress, CAC 2022

作者： Peng, Zhi-Kun Liu, Zhen-Tao Han, Meng-Ting China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9781665465335

Speech emotion recognition (SER) is a key technology to achieve natural human-computer interaction. The development of SER is significantly influenced by the scale of the sample. In recent years, the study of SER has been intensified by introducing data augmentation methods. However, most of these methods directly augment the sample data scale, neglecting the rational analysis and utilization of the feature distribution of samples. In this paper, we propose a new framework for SER based on clustering assistance, which can utilize the feature distribution information of the sample data directly and effectively. It considers the sample proportion of each emotion category in the clusters obtained by clustering, converts it into a probability score, which is called the clustering emotion probability score, and fuses it with the emotion probability score from the simple classification model according to different fusion weighting factors. We evaluated the proposed method with the baseline model on the IEMOCAP dataset. Experimental results show that our method achieves better results than the baseline model in terms of both weighted and unweighted accuracy. © 2022 IEEE.

关键词： K-means clustering

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Fixed-/Preassigned-Time Stabilization of Memristive Neural Networks with Discontinuous Activations

Fixed-/Preassigned-Time Stabilization of Memristive Neural N...

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2021 International Conference on Neuromorphic Computing, ICNC 2021

作者： Li, Haoyu Wang, Leimin School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China

ISBN: (纸本)9781665412872

In this paper, the fixed-time stabilization (FTS) and preassigned-time stabilization (PTS) problems for memristive neural networks (MNNs) with discontinuous activation functions (DAF) is investigated by designing a unified controller. In addition, less conservative stabilization criteria are derived to ensure the FTS and PTS of MNNs. Besides, a more accurate estimate of settling time is obtained based on Lyapunov stability theory. Finally, a numerical simulation is illustrated to verify the validity of theoretical results. © 2021 IEEE.

关键词： Stabilization

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