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International Conference on Micro/Nano Sensors for AI, Healthcare, and Robotics (NSENS)

作者： Hongyu Zhang Zhikun Zhan Yuliang Zhao Xiaopeng Sha Xiaodong Yu Hui Sun Lijia Gu Jiali Liu Lianqing Liu Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China School of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao China State key Laboratory of Robotics Chinese Academy of Sciences

ISBN: (纸本)9781538694091;9781538694084

This paper reports a novel electrochemical method for the detection of insulin in ultra-pure water. A screen printed electrode (SPE) modified by Nickel hydroxide was used as the working electrode, one with good activity of electro-catalytic oxidation-reduction for insulin. The SPE was modified by Nickel hydroxide using the electrodeposition method. The results showed that Nickel hydroxide was homogeneously electrodeposited on the surface of the working electrode. A coin-size electrolytic tank was fabricated with PDMS, which only requires 0.3ml of sample for the detection. The concentration of insulin was analyzed using the methods of Cyclic voltammetry (CV), Electrochemical impedance spectroscopy (EIS) and Chronoamperometry (i-t). The Nickel hydroxide used for detecting insulin showed good analytical characteristics, such as a high sensitivity of 14.797μA·μM -1 , a good linear detection range of 100nM-5μM, and a low detection limit of 93nM. This nickel hydroxide modified SPE electrode has a much smaller size and is easier to fabricate than traditional electrodes, making it a much more promising candidate for an insulin sensor.

关键词： Electrodes Insulin Nickel Oxidation Sensitivity Surface treatment Diabetes

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Path Planning of Humanoid Arm Based on Deep Deterministic Policy Gradient

Path Planning of Humanoid Arm Based on Deep Deterministic Po...

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IEEE International Conference on Robotics and Biomimetics

作者： Shuhuan Wen Jianhua Chen Shen Wang Hong Zhang Xueheng Hu department of Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China Department of Computing Science University of Alberta Edmonton Canada

ISBN: (纸本)9781728103785;9781728103778

The robot arm with multiple degrees of freedom and working in a 3D space needs to avoid obstacles during the grasping process by its end effector. Path planning to avoid obstacles is very important for accomplishing a grasping task. This paper proposes a new obstacle avoidance algorithm, based on an existing deep reinforcement learning framework called deep deterministic policy gradient (DDPG). Specifically, we propose to use DDPG to plan the trajectory of a robot arm to realize obstacle avoidance. The rewards are designed to overcome the difficulty in convergence of multiple rewards, especially when the rewards are antagonistic with respect to each other. Obstacle avoidance of the robot arm using DDPG is achieved by self-learning, and the convergence problem caused by the high dimension state input and multiple return values is solved. The simulation model of an arm of the Nao robot is built based on the MuJoCo simulation environment. The simulation demonstrates that the proposed algorithm successfully allows the robot arm to avoid obstacles.

关键词： Manipulators Neural networks Robot kinematics Planning Reinforcement learning Trajectory

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Open-closed-loop iterative learning control for a class of nonlinear systems with random data dropouts

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IOP Conference Series: Materials Science and engineering 2018年第1期359卷

作者： X Y Cheng H B Wang Y L Jia YH Dong The Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao 066004 China

In this paper, an open-closed-loop iterative learning control (ILC) algorithm is constructed for a class of nonlinear systems subjecting to random data dropouts. The ILC algorithm is implemented by a networked control system (NCS), where only the off-line data is transmitted by network while the real-time data is delivered in the point-to-point way. Thus, there are two controllers rather than one in the control system, which makes better use of the saved and current information and thereby improves the performance achieved by open-loop control alone. During the transfer of off-line data between the nonlinear plant and the remote controller data dropout occurs randomly and the data dropout rate is modeled as a binary Bernoulli random variable. Both measurement and control data dropouts are taken into consideration simultaneously. The convergence criterion is derived based on rigorous analysis. Finally, the simulation results verify the effectiveness of the proposed method.

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Adaptive finite time consensus control of multiple mechanical systems under a switching graph 35

Adaptive finite time consensus control of multiple mechanica...

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第35届中国控制会议

作者： WANG Hongbin ZHOU Zhen WANG Yueling Key Lab of Industrial Computer Control Engineering of Hebei Province Yansnan University

ISBN: (纸本)9781509009107

In this paper,adaptive finite time consensus control problem is investigated for multiple mechanical systems with *** adaptive distributed control algorithms are proposed for the multiple mechanical systems under a switching undirected graph,which is addressed through a novel Markov *** any detailed information of the system model,the adaptive distributed controller has a faster and higher precision tracking *** is shown that the states of the mechanical systems can reach a consensus within finite *** finally,an illustrative simulation on the multiple robotic manipulators is given to demonstrate the effectiveness of the proposed controller.

关键词： Finite time consensus Adaptive control Multiple mechanical system Markov chain

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Friction compensation control of space manipulator considering the effects of gravity 35

Friction compensation control of space manipulator consideri...

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第35届中国控制会议

作者： QIN Li JIA Xiao-jing LIU Cai-feng LIU Fu-cai Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University

ISBN: (纸本)9781509009107

All space manipulators are debugged on the ground and on-orbit serviced in space. Compared with in ground gravity environment their friction characteristics in space microgravity environment have great changes. For sake of tracking the desired trajectory, in both ground and space, considering these characteristics, a friction compensation control method based on an Active Disturbance Rejection control(ADRC) is proposed and its effectiveness is validated on a planar 2-DOF free-floating space manipulator. The friction models and the dynamic models under different gravity environment have been derived based on the torque balance, the Kane equation and the Lagrange method. Particle Swarm Optimization(PSO) is put forward to optimize parameters of ADRC so as to improve the efficiency of designing process. Compared with PD controller in tracking simulation under different gravity environment, the results verify the advantage of the proposed improved control method.

关键词： space manipulator gravity friction compensation ADRC Trajectory tracking PSO

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Self-Induced Backaction Optical Pulling Force

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Physical Review Letters 2018年第12期120卷 123901-123901页

作者： Tongtong Zhu Yongyin Cao Lin Wang Zhongquan Nie Tun Cao Fangkui Sun Zehui Jiang Manuel Nieto-Vesperinas Yongmin Liu Cheng-Wei Qiu Weiqiang Ding Department of Physics Harbin Institute of Technology Harbin 150001 China Department of Electrical and Computer Engineering National University of Singapore 4 Engineering Drive 3 Singapore 117583 Singapore Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province College of Physics and Optoelectronics Taiyuan University of Technology Taiyuan 030024 China Department of Biomedical Engineering Dalian University of Technology Dalian 116024 China Instituto de Ciencia de Materiales de Madrid Consejo Superior de Investigaciones Científicas Campus de Cantoblanco Madrid 28049 Spain Departments of Mechanical and Industrial Engineering and Electrical and Computer Engineering Northeastern University Boston Massachusetts 02115 USA

We achieve long-range and continuous optical pulling in a periodic photonic crystal background, which supports a unique Bloch mode with the self-collimation effect. Most interestingly, the pulling force reported here is mainly contributed by the intensity gradient force originating from the self-induced backaction of the object to the self-collimation mode. This force is sharply distinguished from the widely held conception of optical tractor beams based on the scattering force. Also, this pulling force is insensitive to the angle of incidence and can pull multiple objects simultaneously.

关键词： Electromagnetism Mechanical effects of light on material media Photonic crystals Optical microcavities Optical tweezers

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A Fast Channel State Information Feedback Scheme Based on Compressive Sensing for Underwater Acoustic MIMO Systems 35

A Fast Channel State Information Feedback Scheme Based on Co...

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第35届中国控制会议

作者： MA Hui JIAO Jianzhou CHEN Jianmei LI Xinbin Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University

ISBN: (纸本)9781509009107

In this paper,a compressive feedback scheme based on compressed sensing is investigated to reduce feedback load and enhance the sum throughput at low feedback rates for underwater acoustic MIMO ***,to avoid the outof-date channel state information at the transmitter under the high dynamic underwater channel,we present a modified SL0（M-SLO） algorithm to recover the CSI at the transmitter,which adopts more steep approximate hyperbolic tangent function to approximate the l norm in the *** minimization problem of the l norm canbe transformed into a convex optimization problem for the smoothed ***,in order to solve the problem of slow convergence and inaccuracy estimation caused by notched ejfect of the gradient method,hybrid optimization algorithm that combines the advantages of the gradient method and the revised Newton method is introduced to improve the accuracy of sparse *** simulations show that the recovery accuracy and speed are improved by the proposed M-SL0 algorithm comparing with SL0,OMP ***,CSI feedback based compressive sensing performs better than the feedback based on a vector quantitation codebook.

关键词： compressive feedback compressed sensing M-SLO recovery algorithm channel state information

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Active Disturbance Rejection control for Vibration Displacement Tracking System of Continuous Casting Mold Driven by Servo Motor

Active Disturbance Rejection Control for Vibration Displacem...

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第36届中国控制会议

作者： ZHANG Wenbo FANG Yiming LI Jianxiong MA Zhuang Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University National Engineering Research Center for Equipment and Technology of Cold Strip Rolling Tangshan University

Active disturbance rejection control（ADRC） is applied in this paper to solve the problems of time-varying load torque disturbance,reduction ratio uncertainty and the initial deviation of the eccentric shaft mechanical zero,which exist in the continuous casting mold vibration displacement system driven by servo *** consists of three parts:tracking differentiator（TD）,extended state observer（ESO） and nonlinear state error feedback（NLSEF）.TD is responsible for the arrangement of the transition process of eccentric shaft angular displacement and extracts its differential signal,which makes eccentric shaft angular displacement change *** improve the tracking accuracy,a modified ESO is designed to estimate and compensate comprehensive disturbance of the control system,which enhances system anti-disturbance ability,And NLSEF is then developed to improve the rapidity and stability of the control ***,the simulation results are given to show that ADRC has the characteristics of fast response,high accuracy and strong robustness against the internal and external disturbances in the control system.

关键词： servo motor continuous casting mold vibration displacement system active disturbance rejection control

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Nonlinear Auto Disturbance Rejection control for Vibration Displacement System of Continuous Cast Mold Driven by Servo Motor 35

Nonlinear Auto Disturbance Rejection Control for Vibration D...

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第35届中国控制会议

作者： ZHENG Huicheng LIU Le FANG Yiming LI Qiang Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University National Engineering Research Center for Equipment and Technology of Cold Strip Rolling

ISBN: (纸本)9781509009107

Aiming at the problem about the nonlinear function and the mechanical zero offset in the vibration system of continuous casting mold driven by servo motor, a discrete auto disturbance rejection control（ADRC） with nonlinear function processing algorithm is proposed. Firstly, for the nonlinear multi solutions problem existing between rotation angle and displacement of mold, a nonlinear algorithm is proposed to get the practical phase difference of eccentric shaft. The algorithm is achieved by calculating the time difference between ideal time of arrival and actual time of arrival at the same position. Secondly, the mathematical model of vibration system is discretized by using the Euler method, and an ADRC is designed to estimate the eccentric shaft mechanical zero offset and load disturbance, and then compensate and weaken the position error. Finally, the simulation results demonstrate the feasibility of the proposed method.

关键词： Continuous casting mold Non-sinusoidal vibration Driven by servo motor Auto disturbance rejection control

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Modeling Based on BP Neural Network for Non-sinusoidal Vibration Displacement control System of Continuous Casting Mold Driven by Servo Motor 35

Modeling Based on BP Neural Network for Non-sinusoidal Vibra...

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第35届中国控制会议

作者： MA Zhuang FANG Yiming LIU Le KANG Kesong Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Tangshan University National Engineering Research Center for Equipment and Technology of Cold Strip Rolling

ISBN: (纸本)9781509009107

In order to improve the displacement control precision of continuous casting mold, the establishment of precise mathematical model of non-sinusoidal vibration displacement control system is important. The modeling method of BP neural network optimized by genetic algorithm is adopted, which can solve the problem of the mechanism modeling of various approximate treatments. Firstly the system model of BP neural network is constructed according to the measured data received from industrial field. Secondly, BP neural network model of genetic optimization is built. Then simulations are eventually performed, and then by comparing the error between the predicted displacement outputs of BP neural network optimized by genetic algorithm and the actual output displacement of the system, the simulation results show that the system error of the identified model is within 4%, and the identification method of BP neural network optimized by genetic algorithm is superior to the mechanism modeling.

关键词： continuous casting mold servo motor non-sinusoidal vibration BP neural network genetic algorithm

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