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A UHD MIPI CSI-2 image acquisition system based on FPGA

A UHD MIPI CSI-2 image acquisition system based on FPGA

引用

第40届中国控制会议

作者： Fuchun Liu Lei Wang Yang Yang College of Automation Science and Engineering The Key Laboratory of Autonomous Systems and Networked Control（ASNC） Ministry of Education South China University of Technology

With the development of information technology and the ultra high definition（UHD） video industry, the video’s resolution is continuously improving, from the standard definition（SD） era to the high definition（HD） era, and the UHD *** the field of biomedical engineering, the requirement of medical device endoscope for image resolution is higher and *** with the traditional HD endoscope system, the UHD endoscope image acquisition system designed in this article uses FPGA（Field Programmable Gate Array） as the processing center. The image resolution is increased from 1920*1080 to 3840*2160. Our system designed a physical layer and protocol layer of MIPI CSI-2 interface that can support 30 frame per second. It proves that our image acquisition system is practical and stable for medical endoscope image acquisition systems and also suitable for ultra-high-definition image systems in other fields.

关键词： FPGA MIPI CSI-2 D-PHY UHD image acquisition endoscope

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A Fast Conversion Method of Tube Coordinates

A Fast Conversion Method of Tube Coordinates

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作者： Hao Zhao Renbo Xia Yueling Chen Liming Tao Daixian Zhao Tianyu Zhang Key Laboratory of Networked Control System Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institute of Robotics and Intelligent Manufacturing Innovation Chinese Academy of Sciences University of Chinese Academy of Sciences

Inspired by the idea of the coordinate transformation of the robot arm, the tube structure is analogized to the robot arm structure, and the conversion method of the tube bend processing parameters LRA to the three-dimensional coordinate points is obtained. The method first regards the tube as a "mechanical arm";then, using the similarity of the LRA processing parameters and DH parameters, all the LRA parameters are converted into D-H parameters;finally, the D-H parameter method is applied to calculate the distance between each axis of the " mechanical arm ". If the first space coordinate point is defined as the origin of the base coordinate system (0, 0, 0), then the position of the origin of other coordinate systems in the base coordinate system can be obtained;It has been proved by experiments that this method fast and feasible.

关键词： Tube Coordinates Fast Conversion Method Mechanical Arm D-H Parameter Method

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Active Disturbance Rejection control Design for the Hydraulic Actuator on Weeding Machine

Active Disturbance Rejection Control Design for the Hydrauli...

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第40届中国控制会议

作者： Fuchun Liu Yang Yang Lei Wang School of Automation Science and Engineering The Key Laboratory of Autonomous Systems and Networked Control （ASNC） Ministry of Education South China University of Technology

A weeding machine can sometimes cause plant damage while working in the paddy field due to the seedling line bending phenomenon. Thus, we introduce a computer-vision-based automatic seedling avoidance system for the weeding machine, with a hydraulic cylinder actuator driving the weeding wheels according to the guidance information. This paper aims to study and design a Linear Active Disturbance Rejection control（LADRC） controller for the hydraulic system. The proportional directional valve has a large input dead zone, decreasing the controller’s performance and causing oscillation of the system output near the setpoint. We designed a nonlinear dead zone compensation module and proposed a residual dead zone compensation method, taking advantage of the Extended State Observer（ESO）. A well-behaved hydraulic position servo system was designed and tested in Simulink simulation and on an experimental platform based on the compensation method. The results show that the system performance meets the requirement with approximately no overshoot, response time within 0.7 s, and steady-state error within 0.7 mm on the experimental platform.

关键词： weeding machine hydraulic system dead zone compensation LADRC

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Dual-Level Trajectory Planning for Hypersonic Flight with Multiple No-fly Zones

Dual-Level Trajectory Planning for Hypersonic Flight with Mu...

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Chinese control Conference (CCC)

作者： Yuhuan Ran Ke Yi Zixuan Liang School of Aerospace Engineering Beijing Institute of Technology Beijing China Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration (Beijing Institute of Technology) Ministry of Industry and Information Technology Beijing China CSSC System Engineering Research Institute Beijing

A dual-level trajectory planning method is proposed for the trajectory planning of hypersonic vehicles with no-fly zone constraint. To improve the efficiency of the trajectory planning, the method is designed in two levels: the first level is the heading planning, and the second level is the trajectory planning. For the first level, a rapid heading planning method is proposed based on the graphical model of no-fly zones, and the evaluation of the avoidance heading is based on the simplified lateral dynamics equation. The second level introduces the avoidance heading constraint and the fitness with self-seeking, and thus the trajectory planning model can quickly generate a trajectory that satisfies the constraints. Finally, the proposed dual-level planning method is validated by simulations of hypersonic flight with multiple no-fly zones. The results show that the proposed method is capable to generate flight trajectories in high efficiency.

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A PSO-RBF neural network for BOD multi-step prediction in wastewater treatment process

A PSO-RBF neural network for BOD multi-step prediction in wa...

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2021 China Automation Congress, CAC 2021

作者： Liu, Yonglei Li, Wenjing Faculty of Information Technology Beijing University of Technology Beijing Institute of Artificial Intelligence Beijing Laboratory of Smart Environmental Protection Beijing Key Laboratory of Computational Intelligence and Intelligent System Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing China

ISBN: (纸本)9781665426473

The single-step prediction of the effluent biochemical oxygen demand (BOD) in wastewater treatment process (WWTP) cannot provide the information for future trends, which will affect the decision-making for subsequent control strategies in WWTP. To solve this problem, a radial basis function (RBF) neural network soft-sensing model based on PSO algorithm (PSO-RBF) is proposed for multi-step prediction of the biochemical oxygen demand (BOD) in WWTP. First, we propose an RBF model for multi-step prediction based on MIMO strategy. Then, the PSO algorithm is used to optimize the RBF parameters. Finally, the proposed model is applied to a four-step BOD prediction in WWTP. Experimental results show that this model can better predict BOD in multiple steps compared to traditional models. © 2021 IEEE

关键词： Forecasting

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Multi-Objective Hybrid Energy Storage Optimization Configuration Model for Reducing Thermal Power Frequency Modulation Loss

Multi-Objective Hybrid Energy Storage Optimization Configura...

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International Conference on Power system Technology (POWERCON)

作者： JunHui Li ZhenZhuo Zhao ZhiQiang Zhao HaoJun Liu CuiPing Li Zhi Li CaiQi Jia XingXu Zhu Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China State Grid Hami Power Supply Company Hami City Xinjiang Uygur Autonomous Region China

The TPU (Thermal Power Unit) equipped with HESS (Hybrid Energy Storage system) can effectively increase of FM (Frequency Modulation) performance of the unit and decrease the FM loss of the thermal power unit. The difficulty of rational allocation of ES (Energy Storage) is how to improve the FM performance of TPU and reduce the life cycle cost of ES. Therefore, the paper establishes a multi-objective hybrid energy storage optimization configuration model aimed at reducing the FM loss of thermal power. Firstly, a double-layer control policy of thermal power-hybrid energy storage is proposed. The first layer is the thermal power-hybrid energy storage AGC instruction allocation strategy based on EMD (Empirical Mode Decomposition). The second layer is a hybrid energy storage control strategy with flywheel ES priority action and lithium battery second response. Then, a multi-objective optimal configuration model considering the difference between life cycle cost and benefit and AGC comprehensive evaluation index Kp is established. It uses the multi-objective PSO (Particle Swarm Optimization) algorithm based on TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) to solve the model, which can avoid contingency of traditional multi-objective PSO in determining optimum solution in the Pareto solution set. Finally, based on the simulation analysis of power plant operation data in North China, the results verify the availability and feasibility of the established model.

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Research on NLOS environmental ranging method based on gradient boosting tree

Research on NLOS environmental ranging method based on gradi...

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2024 8th International Conference on Electrical, Mechanical and Computer Engineering (ICEMCE)

作者： Wenyu Li Shun Cao Xianda Liu Minghao Wang Shuan Sheng School of Information Engineering Shenyang University of Chemical Technology Shenyang Liaoning China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang Liaoning China Key Laboratory of Networked Control System Chinese Academy of Sciences Shenyang Liaoning China Shenyang National Research Institute of Intelligent Robots Co. Ltd. Liaoning China

ISBN: (数字)9798331506230

ISBN: (纸本)9798331506247

Indoor distance measurement plays a critical role in positioning services. The complexity of indoor environments, coupled with a limited and small sample size, results in suboptimal distance accuracy. This paper proposes a method for non-line-of-sight distance measurement based on a gradient boosting tree model, effectively addressing the issue of sample size dependency. The random hyperparameter settings of the gradient boosting tree model lead to prolonged fitting times. Additionally, the model utilizes a fixed learning rate, which limits the analysis of features in small samples. To tackle these concerns, we develop a grid optimization algorithm that identifies the best hyperparameter combinations through a hyperparameter grid search. We also implement a weighted value approach and a cosine annealing algorithm to precisely update the learning rate according to training conditions, thus maximizing the learning of small sample features. Our proposed model significantly enhances distance accuracy in non-line-of-sight environments under constraints of training sample size and variety. Comparative experiments demonstrate that our model improves distance accuracy by 63% relative to other machine learning models, with a mean square error of only 0.168m.

关键词： Training Analytical models Accuracy Stability criteria Fitting Power system stability Boosting Distance measurement Data models Optimization

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Design of echo state network with multi-objective optimization algorithm and l1 regularization

Design of echo state network with multi-objective optimizati...

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Chinese control and Decision Conference, CCDC

作者： Zhanhong Wu Cuili Yang Faculty of Information Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing University of Technology Beijing

ISBN: (纸本)9781665478977

In this paper, a new approach for optimizing the structure and prediction error of echo state network (ESN) is proposed. ESN is a kind of recurrent neural network with simple training and strong generalization ability. Reservoir is an important structure of ESN, which determine network performance. Thus, multi-objective optimization algorithm is used to optimize network structure and training error simultaneously. Moreover, a local search algorithm based on l 1 regularization is used to accelerate convergence. The experiment results of time series prediction and standard classification show that MESN can improve the network prediction performance while sparse network structure.

关键词： Training Recurrent neural networks Time series analysis Benchmark testing Prediction algorithms Reservoirs Classification algorithms

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Remote Sensing Inversion for River Turbidity Estimation Based on Noise Injection and Ensemble Learning

Remote Sensing Inversion for River Turbidity Estimation Base...

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2021 China Automation Congress, CAC 2021

作者： Zhou, Yazhen Shi, Shuang Liu, Hongyan Zhang, Yonghui Gu, Ke Qiao, Junfei Faculty of Information Technology Beijing University of Technology Beijing 100124 China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing Laboratory of Smart Environmental Protection Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing Artificial Intelligence Institute

ISBN: (纸本)9781665426473

Turbidity is one main indicator of quality typically used for monitoring water pollution and water eutrophication. The monitoring technology of river water quality can be divided into contact monitoring technology based on physical sensors and non-contact monitoring technology based on remote sensing satellites. The traditional contact monitoring technology has limited monitoring spatial resolution. As a new technology, the remote sensing monitoring technology of the river can conveniently solve the above-mentioned shortcomings and realize the coverage of the whole river basin. However, due to the scarcity of remote sensing data and the measurement errors of remote sensing satellites themselves, learning-based turbidity measurement methods have weak generalization ability and thus are easily prone to produce large deviations. To effectively address such difficulty, a noise injection method is introduced into a river turbidity measurement model based on ensemble learning. To be specific, we randomly generate many noise sets and add them to the remote sensing data to make it closer to the real application scene, and then adopt the ensemble learning model to estimate river turbidity. Experiments validate that the random noise injection strategy can effectively improve the generalization performance of river turbidity measurement. © 2021 IEEE

关键词： Rivers

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Evaluating Image Quality of DIBR-synthesized Views in Texture and Depth Domains

Evaluating Image Quality of DIBR-synthesized Views in Textur...

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2021 China Automation Congress, CAC 2021

作者： Wang, Guangcheng Guo, Nan Liu, Hongyan Zhang, Yonghui Zhou, Yazhen Gu, Ke Faculty of Information Technology Beijing University of Technology Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing Laboratory of Smart Environmental Protection Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing Artificial Intelligence Institute Beijing100124 China

ISBN: (纸本)9781665426473

Accurately predicting the quality of depth-image-based-rendering (DIBR) synthesized images is of great significance in promoting DIBR techniques. Recently, Many DIBR-synthesized image quality assessment (IQA) algorithms based on quantifying the distortion existed in texture images have been proposed. However, these methods ignore the damage of DIBR algorithms on the depth structure of DIBR-synthesized images and thus fail to evaluate the visual quality of DIBR-synthesized images accurately. To this end, we present a DIBR-synthesized image quality assessment metric with multi-modal information (i.e. integrating texture and depth information), dubbed as MMI. MMI predicts the quality of DIBR-synthesized images by jointly measuring the texture structure and depth structure of the synthesized image. The design principle of our MMI is that the local geometric distortion, introduced by DIBR techniques in the hole-filling process, destroys the texture structure and the depth structure of DIBR-synthesized images. Thus, we can accurately evaluate DIBR-synthesized image quality by a joint representation of texture structure and depth structure. Experiments show that our MMI is better than the competing state-of-the-art IQA algorithms in predicting DIBR-synthesized image quality. © 2021 IEEE

关键词： Textures

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