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The Research on Sensorless Control of Permanent Magnet Synchronous using SMC and SMO

IOP Conference Series: Materials Science and engineering 2020年第1期717卷

作者： Li Daoqi Xiong Xinhong Zhang Guoqing Zhang Yanhui Zuo Rui Feng Wei School of Logistics Engineering Wuhan University of Technology Wuhan 430070 China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China CAS Key Laboratory of Human-Machine-Intelligence Synergic Systems Shenzhen Institutes of Advanced Technology Shenzhen 518055 China

This work proposes a way to achieve the sensorless control of permanent-magnet synchronous motor using sliding mode controller (SMC) and Sliding Mode Observer(SMO). In this Paper, the SMC is designed to replace the speed control loop PI controller from the original permanent magnet synchronous motor control system with the sliding mode variable structure control theory. Combined with the modified SMO, the 'SMC and modified SMO' motor control system is proposed. Compared with the 'PI and modified SMO' mode, the performance of the motor control is increased substantially, the interference torque speed attenuation is decreased by 87.5%, and the speed control error was also reduced by 67.7%. There is no overshoot with the reaction speed, and significant improvement in response speed, anti-interference performance, control accuracy and observation precision are achieved. Overall, both the system control and observation performance are significantly improved.

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Design of PI Controller for PMSM using Chaos Particle Swarm Optimization Algorithm

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IOP Conference Series: Materials Science and engineering 2020年第1期717卷

作者： Zuo Rui Xiong Xinhong Chen Lianbo Guo Shifeng Zhang Yanhui Li Daoqi Feng Wei School of Logistics Engineering Wuhan University of Technology Wuhan 430070 China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China CAS Key Laboratory of Human-Machine-Intelligence Synergic Systems Shenzhen Institutes of Advanced Technology Shenzhen 518055 China

The proportional-integral-derivative (PID) controller parameters tuning is critical for improving the performance of permanent magnet synchronous motor (PMSM) systems. To improve the performance of particle swarm optimization (PSO) in the PID parameters tuning, the chaos particle swarm optimization (CPSO) is adopted to tune PI parameters in this work. The PMSM vector control system is selected as the research object, and its speed loop PI controller using CPSO algorithm is implemented. The optimal PI controller parameters are obtained using the CPSO algorithm with ten iterations. The simulation is conducted using MATlab/Simulink to evaluate to the PI controller performance. Four performance indicators including overshoot, rise time, peak time and ITAE are used to evaluate the PI controller with CPSO, and the results suggest that the CPSO algorithm has better performance and stability compared with other tuning methods.

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Targeted Cancer Therapy: Sequential Magneto-Actuated and Optics-Triggered Biomicrorobots for Targeted Cancer Therapy (Adv. Funct. Mater. 11/2021)

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Advanced Functional Materials 2021年第11期31卷

作者： Jiehua Xing Ting Yin Shuiming Li Tiantian Xu Aiqing Ma Ze Chen Yingmei Luo Zhengyu Lai Yingnian Lv Hong Pan Ruijing Liang Xinyu Wu Mingbin Zheng Lintao Cai Guangdong Key Laboratory of Nanomedicine CAS-HK Joint Lab for Biomaterials Shenzhen Institutes of Advanced Technology (SIAT) Chinese Academy of Sciences Shenzhen 518055 P. R. China Guangdong Key Laboratory for Research and Development of Natural Drugs Key Laboratory for Nanomedicine Guangdong Medical University Dongguan 523808 P. R. China Shenzhen Key Laboratory Microbiology and Gene Engineering Shenzhen University Shenzhen 518060 P. R. China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 P. R. China Zhuhai Institute of Advanced Technology Chinese Academy of Sciences Zhuhai 519000 P. R. China The Third People's Hospital of Shenzhen Shenzhen 518114 P. R. China

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Research on Position Sensorless Control of PMSM Based on Improved SMO

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IOP Conference Series: Materials Science and engineering 2019年第1期533卷

作者： Zhang Guoqing Xiong Xinhong Zheng Yousheng Zhang Yanhui Chen Lianbo Wu Xinyu Feng Wei Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China CAS Key Laboratory of Human-Machine-Intelligence Synergic Systems Shenzhen Institutes of Advanced Technology Shenzhen 518055 China School of Logistics Engineering Wuhan University of Technology Wuhan 430070 China

The sliding mode observer (SMO) can effectively achieve the permanent magnet synchronous motor (PMSM) to perform position sensorless control, but there are still drawbacks of system chattering and high complexity. In this paper, an improved SMO is established based on hyperbolic tangent function and Kalman filter. The system chattering is effectively suppressed, and the accuracy of position and speed observation error is significantly improved without phase compensation. It is found that the convergence rate of the hyperbolic tangent function has a strong correlation with the system chattering degree and the speed observation error. When a is between 3 and 4, the speed error accuracy of the improved SMO is the optimum situation.

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Parameter Tuning of PID Controller of Servo system Based on Particle Swarm Optimization Algorithm

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IOP Conference Series: Materials Science and engineering 2019年第1期533卷

作者： Chen Lianbo Xiong Xinhong Zheng Yousheng Zhang Yanhui Zhang Guoqing Wu Xinyu Feng Wei Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China CAS Key Laboratory of Human-Machine-Intelligence Synergic Systems Shenzhen Institutes of Advanced Technology Shenzhen 518055 China School of Logistics Engineering Wuhan University of Technology Wuhan 430070 China

In order to improve the control precision of permanent magnet synchronous motor servo drive, a Proportional-Integral-Differential (PID) control method based on particle swarm optimization (PSO) algorithm is proposed. Firstly, the mathematical model of the permanent magnet synchronous motor was established. Then the PSO algorithm was used to adjust the parameters of the PID controller. Finally, the simulation experiment was carried out under the MATlab/Simulink environment to test its performance. Compared with the traditional manual parameters tuning, the PID controller based on PSO algorithm had better performance and better stability.

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Running person detection from a community patrol robot

Running person detection from a community patrol robot

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International Conference on Information and Automation (ICIA)

作者： Huiwen Guo Shibo Cai Xinyu Wu Qingtian Wu Wei Feng Qingshi Gao Guangdong Provincial Key Lab of Robotics and Intelligent System Chinese Academy of Sciences Ministry of Education (Zhejiang University of Technology) China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong

ISBN: (纸本)9781509041039

In this paper, a running person detection method is proposed for the community patrol robot. The challenges include the diversity of movement direction and the ego-motion of camera. The diversity of movement direction means that it is difficult to gain high accuracy detection by only using appearance information. The ego-motion of camera means that the motion information contains high noise. To address these limitations, two-stream architecture of convolutional networks, spatial stream and motion stream, is proposed to capture the complementary information on appearance from still frames and motion between frames. In addition, simple but effective filtering based ego-motion elimination technique is applied in motion stream input calculation. We demonstrate the efficiency of the proposed method on the video captured from the community scene and the performance compared with existing methods, which validates that the proposed method detects running person more accurately.

关键词： Image motion analysis Computer vision Optical imaging Optical filters Cameras Training

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Multi-stage feature learning based object recognition and 3D pose estimation with kinect 6

Multi-stage feature learning based object recognition and 3D...

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6th International Conference on Information Science and Technology, ICIST 2016

作者： Zeng, Wei Liang, Guoyuan Guangdong, Can Wang Wu, Xinyu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Key Laboratory of Human-Machine-Intelligence Synergic Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen China Dept. Mechanical and Automation Engineering Chinese University of Hong Kong Shenzhen China

ISBN: (纸本)9781509012206

Impressive achievements have been achieved over the years in object recognition and 3D pose estimation while detecting objects and estimating their 3D poses reliably is still a very challenging problem, especially for texture-less objects in heavily cluttered scenes. In this paper, we introduce an improved approach based on multi-stage feature learning to identify object as well as their 3D orientation efficiently. Our approach is motivated by visual neuroscience models. Currently similar architectures have been successfully applied to pedestrian detection, traffic recognition, face representation, etc. We compute the feature descriptors by multi-stage convolutional neural networks (CNNs) which could map the object identity and 3D poses to the Euclidean distance space by evaluating the similarity between descriptors. By contrast with classical approaches, our method relies on fast and approximate Nearest Neighbor (NN) matching to solve the large scale problems instead of one classifier per object or multi-class classifiers whose complexity grows rapidly with the number of objects. The experiments of detecting poorly-textured objects in cluttered scenarios have been carried out to verify the effectiveness and efficacy of the proposed approach. © 2016 IEEE.

关键词： Object recognition

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Appearance of a robot affects the impact of its behaviour on perceived trustworthiness and empathy

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Paladyn 2016年第1期7卷 55-66页

作者： Zlotowski, Jakub Sumioka, Hidenobu Nishio, Shuichi Glas, Dylan F. Bartneck, Christoph Ishiguro, Hiroshi HIT Lab. NZ University of Canterbury Christchurch New Zealand Hiroshi Ishiguro Laboratory Advanced Telecommunications Research Institute International Kyoto Japan Intelligent Robotics and Communication Laboratories Advanced Telecommunications Research Institute International Kyoto Japan Department of System Innovation Graduate School of Engineering Science Osaka University Osaka Japan

An increasing number of companion robots have started reaching the public in the recent years. These robots vary in their appearance and behavior. Since these two factors can have an impact on lasting human-robot relationships, it is important to understand their effect for companion robots. We have conducted an experiment that evaluated the impact of a robot's appearance and its behaviour in repeated interactions on its perceived empathy, trustworthiness and anxiety experienced by a human. The results indicate that a highly humanlike robot is perceived as less trustworthy and empathic than a more machinelike robot. Moreover, negative behaviour of a machinelike robot reduces its trustworthiness and perceived empathy stronger than for highly humanlike robot. In addition, we found that a robot which disapproves of what a human says can induce anxiety felt towards its communication capabilities. Our findings suggest that more machinelike robots can be more suitable as companions than highly humanlike robots. Moreover, a robot disagreeing with a human interaction partner should be able to provide feedback on its understanding of the partner's message in order to reduce her anxiety. © 2016 Jakub Zlotowski et al., published by De Gruyter Open.

关键词： Human robot interaction

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Self-adaptive Control Strategy for Exoskeleton to Help Paraplegic Patients Stand Up and Sit Down

Self-adaptive Control Strategy for Exoskeleton to Help Parap...

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第35届中国控制会议

作者： Can Wu Ting Zhang Yongqiang Liao Can Wang Guizhong Wu Xinyu Wu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences School of Electro-mechanical Engineering Guangdong University of Technology Key Laboratory of Human-Machine-Intelligence Synergic Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences

ISBN: (纸本)9781509009107

This paper presents a practical control strategy used on lower limb exoskeleton to help paraplegic patients to stand up and sit *** can make the process more comfortable and stable no matter the crutches are pressed heavy or *** is particularly efficient to the robots without drivable ankle joints such SIAT *** space was configured to ensure that the real time-generated trajectory won't break the balance of human-robot *** speed of each joint adjusts to the pressure under the crutches so as to relieve the impact from *** result of experiments shows that the self-adaptive control strategy can not only ensure the stability and fitness,but also form an incentive- "more effort paid,more time saved".

关键词： Exoskeleton Stable space Self-adaptive control Standing up process

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Obstacle Avoidance for Kinematically Redundant Robot

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IFAC-PapersOnLine 2015年第28期48卷 490-495页

作者： WANG, Xinyu YANG, Chenguang CHEN, Junshen MA, Hongbin LIU, Feng School of Automation Beijing Institute of Technology Beijing China State Key Lab of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China Centre for Robotics and Neural Systems Plymouth University Plymouth United Kingdom College of Automation Science and Engineering South China University of Technology Guangzhou China Beijing Jiaotong University Beijing China

Manipulator's obstacle avoidance is always a challenging topic in robotics. With the concern of the safety problems in human working environment, an improved obstacle avoidance method is proposed based on the general solution of the inverse kinematic problem of a redundant manipulator. A new obstacle detection method using Kinect R sensor is designed to give a robust obstacle information. By designing a parallel system of the manipulator, the proposed control method is not only to achieve the goal of moving away from the obstacle, but also able to guarantee the robot move back to its original pose. The stability of the closed-loop system is established using Lyapunov direct method to ensure the asymptotic stability of the system. The performance of the simulation results verifies the effectiveness of the proposed obstacle detection algorithm and the obstacle avoidance method. © 2015

关键词： Inverse problems Asymptotic stability Closed loop systems Collision avoidance Inverse kinematics Obstacle detectors Redundant manipulators system stability General solutions Inverse kinematic problems Kinematically Redundant Lyapunov direct method Obstacle detection Parallel system Redundant robot Working environment

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