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第32届中国控制与决策会议

作者： Kaixin Zhao Yaping Dai Ye Ji Jiayi Sun School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

Analytic Hierarchy Process（AHP） is a multi criteria decision-making method,which can describe and transform the qualitative problems quantitatively,and then get the quantitative analysis results in accordance with the causal relationship between decision *** this paper,a granular Analytic Hierarchy Process,which introduces the granularity mechanism,is proposed to solve the portfolio selection problem under the mean-risk *** the proposed method,the scale value of scheme layer is no longer limited to nine positive integers from 1 to 9,which gives granularity attributes to the comparison of advantages and disadvantages in a specific criterion layer between different *** proposed method reflects small differences between different alternative schemes through granularity attribute,so it can provide rich decision information for decision *** numeric examples from the real-world financial market（China Shanghai Stock Exchange） are provided to illustrate an essence of the proposed method.

关键词： Analytic Hierarchy Process（AHP） Portfolio Selection Information Granularity decision-making

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Data-driven predictive control for networked control systems

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Information Sciences 2013年 235卷 45-54页

作者： Yuanqing Xia Wen Xie Bo Liu Xiaoyun Wang School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081 China

This paper is concerned with the problem of data-driven predictive control for networked control systems (NCSs), which is designed by applying the subspace matrices technique, obtained directly from the input/output data transferred from networks. The networked predictive control consists of the control prediction generator and network delay compensator. The control prediction generator provides a set of future control predictions to make the closed-loop system achieve the desired control performance and the network delay compensator eliminates the effects of the network transmission delay. The effectiveness and superiority of the proposed method is demonstrated in simulation as well as experiment study.

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Optimal Blood Glucose Prediction based on Intermittent Data from Wearable Glucose Monitoring Sensors

Optimal Blood Glucose Prediction based on Intermittent Data ...

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第三十八届中国控制会议

作者： Lijun Hou Huipeng Zhang Junzheng Wang Dawei Shi State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology

Blood glucose prediction is to predict the glucose trend over time based on historical glucose data, and it plays a crucial role in the closed-loop control of artificial pancreas, which can reduce the risk of complications by regulating insulin dose and injection time. This paper proposes a Kalman-filter-based glucose prediction method through minimizing the mean square prediction error, which assumes that the data is sampled every 15 min from a wearable flash glucose monitoring sensor. This method calculates glucose estimates every 5 min and provides glucose predictions for the next 30 min. The method is evaluated on in-silico data generated from the 10-adult cohort of the US FDA-accepted UVA/Padova T1 DM simulator. The predicted results are compared with CGM data with 5-min sample-period through multiple metrics, including the mean square prediction error and the mean absolute relative deviation. The results show that the performance of the proposed approach with slow-rate glucose data(15 min) is close to that obtained based on fast-rate data(5 min).

关键词： Blood Glucose Prediction Wearable Devices Mean Square Prediction Error Sampled Data Kalman Filtering

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An Improved Part-based Compressive Tracking Method

An Improved Part-based Compressive Tracking Method

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第35届中国控制会议

作者： Qiwen Hou Wenjie Chen HuiLin Gao School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

ISBN: (纸本)9781509009107

In this paper,we propose an improved part-based tracking method based on compressive *** traditional compressive tracking can hardly deal with occlusion and scale variation,which is not robust enough in these *** our part-based method,the occluded image patches which are selected by K-means are not able to participate in determining the location of the target in order to increase tracking *** solve the problem of scale variation,an algorithm is proposed to estimate the size of target with the information of the whole *** addition,we also use the positions of every part to help us to get a precise size of the *** the combination of two methods,the scale of the target is *** compared with five state-of-the-arts have been done to prove the effectiveness and robustness of our method.

关键词： compressive sensing part-based tracking occlusion handling scale estimation

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The algorithm of MIMU/odometer integrated navigation system aided by nonholonomic constraints

The algorithm of MIMU/odometer integrated navigation system ...

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International Conference on Mechatronic Science, Electric Engineering and Computer

作者： Shi Peng Xiao Xuan State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

ISBN: (纸本)9781479925667

The navigation precision drops rapidly when MIMU (Micro Inertial Measurement Unit) works alone. Odometer data are easy to get on land vehicle, but the performance of integration system of MIMU/odometer is not enhanced obviously. In this work, a novel method is designed using nonholonomic constraints. When vehicle travels without slide and jump, the velocity in the plane perpendicular to forward direction is zero, as well as acceleration. Taking velocity constraint and acceleration constraint as measurement value, new measurement models are established. Integrated navigation algorithm is designed with the help of Kalman filter. With this method, the position error is 150m after 600s, and heading attitude error is 0.1°, comparing the result that the position error expands to 300m after 150s only aided by odometer.

关键词： Vehicles Acceleration Global Positioning System Velocity measurement Noise Kalman filters

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Targetless Extrinsic Calibration of Camera and Low-resolution 3D LiDAR

TechRxiv

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TechRxiv 2023年

作者： Ou, Ni Cai, Hanyu Yang, Jiawen Wang, Junzheng The State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

Autonomous driving heavily relies on LiDAR and camera sensors, which can significantly improve the performance of perception and navigation tasks when fused together. The success of this cross-modality fusion hinges on accurate extrinsic calibration. In recent years, targetless LiDAR-camera calibration methods have gained increasing attention thanks to their independence from external targets. Nevertheless, developing a targetless method for low-resolution LiDARs remains challenging due to the difficulty in extracting reliable features from point clouds with limited LiDAR beams. In this paper, we propose a robust targetless method to solve this struggling problem. It can automatically estimate accurate LiDAR and camera poses and solve the extrinsic matrix through hand-eye calibration. Moreover, we also carefully analyze pose estimation issues existing in the low-resolution LiDAR and present our solution. Real-world experiments are carried out on a UGV-mounted multi-sensor platform containing a CCD camera and a VLP-16 LiDAR. For evaluation, we use a state-of-the-art target-based calibration approach to generate the ground-truth extrinsic parameters. Experimental results demonstrate that our method achieves low calibration error in both translation (3 cm) and rotation (0.59 ◦) [Figure presented]. © 2023, CC BY.

关键词： CCD cameras

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Fast adaptive robust control of electro-hydraulic servo system

Fast adaptive robust control of electro-hydraulic servo syst...

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Chinese control Conference (CCC)

作者： Yudong He Junzheng Wang Renjian Hao Key laboratory of intelligent control and decision of complex systems Beijing Institute of Technology Beijing Beijing CN

Electro-hydraulic servo systems (EHSSs) have been widely used in industrial and military applications for their high power-to-size ratio and the ability to supply huge force. However, precise control of EHSSs cannot be easily obtained due to their inner nonlinearity and parameter uncertainty. Variable load is another factor to decrease the tracking performance of EHSSs. Indirect adaptive robust control (IARC) was proposed to improve the tracking performance of EHSS, but due to the poor parameter adapting speed, IARC can be further improved to have better performance. Traditional projection type parameter estimation algorithm is redesigned to increase the adapting speed when parameter is changed. A fast adaptive robust control (FARC) is then proposed to speed up the parameter adapting speed, so that a better tracking performance of FARC is maintained. Simulation results show that the proposed FARC gives an improved tracking performance and a faster parameter adaptation.

关键词： Estimation Robust control Servomotors Force Valves Adaptive systems Load modeling

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Electric dual variable pump controlled hydraulic motor

Electric dual variable pump controlled hydraulic motor

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第42届中国控制会议

作者： Jianmin Yang Junzheng Wang Shanshuai Niu State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

The combined control of variable speed and variable displacement is a new type of volume control with high efficiency and fast ***,due to the inherent nonlinearity of multiplication,it brings certain difficulties to the *** electric double-variable pump[1] is a dual-input single-output system,and it is a nonlinear system[2].It is necessary to linearize the system or use a nonlinear control method to control and solve the control problem of the *** this paper,an intelligent control rule is proposed for the nonlinear problem of double input and single *** backstepping design[3],the nonlinear system is transformed into multiple linear *** the original system is turned into two independent subsystems with single input and single output,which are controlled *** co-simulation platform based on AMESIM and Simulink[4] has been verified and compared with a single PID control algorithm to simulate the step response and sinusoidal tracking performance of the *** results show that the response speed of the system has been greatly improved.

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DBFCM: a Density-Based Fuzzy C-Means with Self-Regulated Fuzzy Clustering Parameters

DBFCM: a Density-Based Fuzzy C-Means with Self-Regulated Fuz...

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第三十九届中国控制会议

作者： Jiayi Sun Yaping Dai Kaixin Zhao School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

As an interdisciplinary of fuzzy theory and clustering, Fuzzy C-Means（FCM） is widely applied for identifying categories with unlabeled data. However, its application to data which is hard to visualize rises the difficulty for users to determine the input parameters, especially for the number of clusters. In this paper, a kind of fuzzy clustering algorithm with self-regulated parameters named Density-Based Fuzzy C-Means（DBFCM） is proposed by integrating the idea of Density-Based Spatial Clustering of Application with Noise（DBSCAN） into FCM. Its advantage is using the inherit density characteristic of input data to self-determine the parameters of fuzzy clustering. The experimental results demonstrate that the proposed DBFCM can not only self-determine the proper parameters, but also accelerate the convergence process compared to the original FCM.

关键词： Machine Learning Fuzzy Clustering Fuzzy C-Means Parameter Self-Regulation

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Local Map Construction Based on 3D-LiDAR and Camera

Local Map Construction Based on 3D-LiDAR and Camera

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Chinese control Conference (CCC)

作者： Hui Qin Jing Li Junzheng Wang Qingbin Wu Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

The local map can update the local environment information in real time, which provides the environment information for the local dynamic planning of the robot. In this paper, a local cost map construction method based on 3D-LIDAR and camera is proposed. We use camera to detect lane lines in structured road and 3D-LIDAR to detect road boundaries in unstructured environment, and then use DS evidence reasoning to determine the current local road information. Dynamic obstacle information in the environment is obtained through 3D point cloud data segmentation, which is fused with the road information to get 3D point cloud information in the local range and generate local cost map according to it. Experiments show that the method in this paper can accurately extract the current road information whether in structured roads or unstructured roads. The fused local cost map can enable the robot to perform reasonable local planning and complete navigation on the current road.

关键词： Roads Three-dimensional displays Robots Planning Cameras Real-time systems Navigation

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