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FISS GAN:A Generative Adversarial Network for Foggy Image Semantic Segmentation

IEEE/CAA Journal of Automatica Sinica 2021年第8期8卷 1428-1439页

作者： Kunhua Liu Zihao Ye Hongyan Guo Dongpu Cao Long Chen Fei-Yue Wang School of Computer Science and Engineering Sun Yat-sen UniversityGuangzhou 510006China State Key Laboratory of Automotive Simulation and Control and the Department of Control Science and Engineering Jilin University(Campus Nanling)Changchun 130025China Mechanical and Mechatronics Engineering Department at the University of Waterloo 200 University Avenue West WaterlooON N2L 3G1Canada State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China

Because pixel values of foggy images are irregularly higher than those of images captured in normal weather(clear images),it is difficult to extract and express their *** method has previously been developed to directly explore the relationship between foggy images and semantic segmentation *** investigated this relationship and propose a generative adversarial network(GAN)for foggy image semantic segmentation(FISS GAN),which contains two parts:an edge GAN and a semantic segmentation *** edge GAN is designed to generate edge information from foggy images to provide auxiliary information to the semantic segmentation *** semantic segmentation GAN is designed to extract and express the texture of foggy images and generate semantic segmentation *** on foggy cityscapes datasets and foggy driving datasets indicated that FISS GAN achieved state-of-the-art performance.

关键词： Edge GAN foggy images foggy image semantic segmentation GAN semantic segmentation

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Design and implementation for the information integration of mechanical manufacturing enterprises

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2012 3rd International Conference on Information Technology for Manufacturing Systems, ITMS 2012

作者： Jiang, Zhuoda Key Laboratory of Numerical Control of Jiangxi Province Jiujiang University 332005 China School of Mechatronics Engineering and Automation Shanghai University 200072 China

ISBN: (纸本)9783037855317

Mechanical manufacturing enterprises face numerous choices about information. In order to take full advantage of the information, the technologies and methods of implementing information integration should be carefully studied. Firstly, the developments of its standard protocols are analyzed. Secondly, the information integration of mechanical manufacturing enterprises is discussed. At last, an example is provided to illustrate the method of information integration. © (2012) Trans Tech Publications, Switzerland.

关键词： Information retrieval

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controller Dynamic Linearization Based Data-Driven Adaptive control for a Vapor-Compression Refrigeration System 13

Controller Dynamic Linearization Based Data-Driven Adaptive ...

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13th IEEE Data Driven control and Learning Systems Conference, DDCLS 2024

作者： Fang, Jingyu Yu, Xian Xiong, Shuangshuang College of Mechatronics and Control Engineering Shenzhen University Shenzhen518060 China School of Automation Beijing Information Science and Technology University Beijing100192 China

ISBN: (纸本)9798350361674

This paper applies a data-driven adaptive control method to a benchmark of vapor compression refrigeration system based on the controller dynamic linearization method. Two controllers, namely, a single-input single-output controller and an extended multiple-input multiple-output controller, are designed to track the exit temperature of the evaporator secondary flux and the refrigerant superheat at the evaporator exit, by controlling the valve opening of the evaporator, and the compressor speed. Both the controllers entirely rely on input-output data of the controlled system in the controller design. Comparative results between the applied data-driven adaptive control and the default PID control provided by the benchmark demonstrate the effectiveness of the two designed controllers. © 2024 IEEE.

关键词： Vapor compression refrigeration

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Implementation of input shaping control to reduce residual vibration in industrial network motion system 15

Implementation of input shaping control to reduce residual v...

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15th International Conference on control, automation and Systems, ICCAS 2015

作者： Ngo, Ha-Quang-Thinh Nguyen, Quoc-Chi Kim, Won-Ho Control and Automation Lab Department of Mechatronics Engineering Ho Chi Minh City University of Technology Viet Nam Department of Mechatronics Engineering Ho Chi Minh City University of Technology Viet Nam Department of Intelligent System Engineering Dong-Eui University Busan Korea Republic of

ISBN: (纸本)9788993215090

In this paper, a method to implement the input shaping control in Mechatrolink-III motion system is introduced. Firstly, the underdamped system is theoretically built by modeling. Then, the motion controller of Mechatrolink-III network is designed to apply the input shaper for reducing residual vibration in manufacturing machine. Later, the experimental beam is set-up to verify the effective performance of input shaping technique. The validity of the control strategy is practically performed by testing ZV, ZVD and ZVDD input shapers. Especially, the successful implementation provides an opportunity to apply the input shaper for multi-axes since Mechatrolink-III motion controller supports up to 32 axes. © 2015 Institute of control, Robotics and Systems - ICROS.

关键词： Motion control

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The Design and Its Application of Cross-Coupled controller in X-Y Table

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武汉理工大学学报 2006年第S3期28卷 783-787页

作者： XI Lei~1 WANG Xin~2 ZHANG Yi~1 (1.Division of control and mechatronics engineering,Harbin Institute of Technology Shenzhen Graduate,Shenzhen 518055,China, 2.Division of Mechanical engineering & automation,Harbin Institute of Technology Shenzhen Graduate,Shenzhen 518055,China) Division of Control and Mechatronics Engineering Harbin Institute of Technology Shenzhen GraduateShenzhen 518055China Division of Mechanical Engineering & Automation Harbin Institute of Technology Shenzhen GraduateShenzhen 518055China

In conventional cross-coupled controller design,the method usually ignored the inherent characteristic of time-vary- ing parameters and model uncertainties in *** this paper,a cross-coupled controller(CCC)using an H~∞control scheme has been proposed to reduce the contouring error for an X-Y ***,the proposed CCC design,which is a typical Multi- Input Multi-Output(MIMO)system with linear time varying(LTV)characteristics,has been verified as being internally stable. The simulations are carried on Matlab simulink to verify the proposed method,and the results showed that the proposed method can reduce the contouring error significantly compared with the conventional one.

关键词： motion control cross-coupled control contour error H∞control

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Indoor 3D scene reconstruction for mobile robots using Microsoft kinect sensor 35

Indoor 3D scene reconstruction for mobile robots using Micro...

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第35届中国控制会议

作者： LI Jiang-Wei ZHENG Ding-Fu GUAN Zhi-Hong CHEN Chao-Yang JIANG Xiao-Wei ZHANG Xian-He College of Automation Huazhong University of Science and Technology The Key Laboratory of Ministry of Education for Image Processing and Intelligent Control (Huazhong University of Science and Technology) School of Information and Electrical Engineering Hunan University of Science and Technology College of Mechatronics and Control Engineering Hubei Normal University

ISBN: (纸本)9781509009107

3D mapping for unknown environments is a crucial issue for mobile service robots,which has many important applications in navigation and path *** this paper,we use Microsoft kinect sensor mounted on a mobile robot to obtain3 D *** the process,consistent frames of RGB-D data are captured and *** Closest Point(ICP)algorithm and incremental registration method are employed to perform the fine ***,we use OctoMap to store 3D map of octree representation,an efficient data ***,our results demonstrate the practical applicability and effectiveness of the proposed approach.

关键词： 3D mapping Kinect OctoMap Mobile Robots

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Surface reconstruction based on radial basis functions network

Surface reconstruction based on radial basis functions netwo...

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3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks

作者： Liu, Han-Bo Wang, Xin Wu, Xiao-Jun Qiang, Wen-Yi Department of Control and Mechatronics Engineering Harbin Institute of Technology Shenzhen Graduate School Shenzhen China Department of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Graduate School Shenzhen China Department of Control Science and Engineering Harbin Institute of Technology Harbin China

ISBN: (纸本)3540344829

A new method for arbitrary 3d-object reconstruction in unknown environment is proposed in this paper. The implicit surface is reconstructed based on radial basis functions network from range scattered data. For the property of locality of radial basis function, the method is fast and robust with respect to large data. Furthermore, an adapted K-Means algorithm is used to reduce RBF centers for reconstruction. Experiment results show that the presented approach is helpful in speed improvement and is a good solution for large data reconstruction. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Radial basis function networks

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Parallel Planning:A New Motion Planning Framework for Autonomous Driving

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IEEE/CAA Journal of Automatica Sinica 2019年第1期6卷 236-246页

作者： Long Chen Xuemin Hu Wei Tian Hong Wang Dongpu Cao Fei-Yue Wang IEEE School of Data and Computer Science Sun Yat-sen University the School of Computer Science and Information Engineering Hubei University Institute of Measurement and Control Systems Karlsruhe Institute of Technology Department of Mechanical and Mechatronics Engineering University of Waterloo the State Key Laboratory of Management and Control for Complex Systems.Institute of Automation Chinese Academy of Sciences the Research Center for Military Computational Experiments and Parallel Systems Technology National University of Defense Technology

Motion planning is one of the most significant technologies for autonomous driving. To make motion planning models able to learn from the environment and to deal with emergency situations, a new motion planning framework called as"parallel planning" is proposed in this paper. In order to generate sufficient and various training samples, artificial traffic scenes are firstly constructed based on the knowledge from the reality.A deep planning model which combines a convolutional neural network(CNN) with the Long Short-Term Memory module(LSTM) is developed to make planning decisions in an end-toend mode. This model can learn from both real and artificial traffic scenes and imitate the driving style of human ***, a parallel deep reinforcement learning approach is also presented to improve the robustness of planning model and reduce the error rate. To handle emergency situations, a hybrid generative model including a variational auto-encoder(VAE) and a generative adversarial network(GAN) is utilized to learn from virtual emergencies generated in artificial traffic scenes. While an autonomous vehicle is moving, the hybrid generative model generates multiple video clips in parallel, which correspond to different potential emergency scenarios. Simultaneously, the deep planning model makes planning decisions for both virtual and current real scenes. The final planning decision is determined by analysis of real observations. Leveraging the parallel planning approach, the planner is able to make rational decisions without heavy calculation burden when an emergency occurs.

关键词： Autonomous driving artificial traffic scene deep learning emergencies motion planning parallel planning

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Improved integral fuzzy sliding mode control for a class of nonlinear uncertain systems

Improved integral fuzzy sliding mode control for a class of ...

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作者： Li, Wen-Qiang Li, Peng Li, Lian Zhang, Yi Department of Control Engineering Naval Aeronautical and Astronautical University Yantai 264001 China College of Mechatronics Engineering and Automation National University of Defense Technology Changsha 410073 China

ISBN: (纸本)9789881725592

For the conventional sliding mode control of a class of nonlinear uncertain systems, the ranges of sliding mode error and steady-state error are deduced. In order to reduce the steady-state error while anti-windup, an improved integral sliding surface is designed, and an improved integral fuzzy sliding mode control approach is proposed based on this sliding surface. In this approach, the integral action is reduced through adjust factor when the sliding variable outside the boundary layer. Then, the large overshoots due to the large initial errors can be avoided. When sliding variable inside the boundary layer, the integral action is conventional in order to reduce the steady-state error. The adjust factor is automatically tuned by real time fuzzy inference. Finally, an inverted pendulum control is used to illustrate the effectiveness and robustness of the proposed approach. © 2011 Chinese Assoc of automation.

关键词： Boundary layers

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Online Identification of Multivariable Nonlinear Processes with Iterative Structure Learning and Application to a Diesel Engine

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IFAC Proceedings Volumes 2014年第3期47卷 9216-9222页

作者： Marek Kowalczyk Boliang Yi Rolf Isermann Institute of Automatic Control and Mechatronics Laboratory of Control Engineering and Process Automation Technical University Darmstadt Germany

This contribution presents a new methodology for the online identification, which allows the modeling of the stationary and dynamic behavior of nonlinear combustion engines with many input and output variables in short time with an appropriate model structure. The used models are local polynomial model trees. The necessary enhancements and adaptations of the identification algorithm for local polynomial model trees for the online methodology are presented. To enable an online identification, not only the parameters but also the structure of the models has to be adapted to the ongoing measuring procedure at a test bench. This structure adaptation methods use iteratively recorded measured data for the determination of an optimized model partition and regressor selection regarding the quality and complexity of the model. This maximizes the iterative improvement of the mathematical model, leading to a reduced test bench time. The applicability of the developed methodology is shown for the identification of a model from both, an artificial test function as well as a real diesel engine.

关键词： Engine modeling Mechatronic combustion engine Iterative measurements Identification methods Online identification Model structure adaptation

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