检索结果-内蒙古大学图书馆

作者： Tao Zhang Hongyu Yan Danping Jia Hualiang Zhang Bingjie Zhao Xu Lu Yang Liu Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences School of Electrical Engineering Dalian University of Technology School of Artificial Intelligence Shenyang University of Technology School of Information Science and Engineering Shenyang University of Technology

X-Y precision plane motion stage is widely used in precision motion control fields such as lithography machine workpiece stage,CNC machine tool,Laser measuring system,etc.,which requires high accuracy of the position *** X-Y precision plane motion stage uses two permanent magnet linear synchronous motors(PMLSM) as drivers to drive the motion table to perform XY two-degree-of-freedom *** open-closedloop PD-type iterative learning controller(ILC) approach based on accelerated convergence was proposed to improve trajectory tracking performance of *** interval was changed by real-time correction of the exponential gain matrix in the interval to accelerate the convergence *** to the λ norm,the monotone convergence of the proportion differentiation(PD) was developed for the *** controller consists of two terms:a PID controller which enhances robustness to disturbances and system parameter variability and an ILC which generally improves the performance in the repetitive tasks by using the information from previous *** experimental results show that tracking precision and convergence speed of PMLSM can be effectively improved by the scheme.

关键词： X-Y precision plane motion stage Iterative learning control tracking precision convergence rate

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Solving the Problem of Runge Phenomenon by Pseudoinverse Cubic Spline

Solving the Problem of Runge Phenomenon by Pseudoinverse Cub...

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IEEE International Conference on Computational Science and Engineering, CSE

作者： Dechao Chen Tianjian Qiao Hongzhou Tan Mingming Li Yunong Zhang Ministry of Education Key Laboratory of Autonomous Systems and Networked Control Guangzhou China SYSU-CMU Shunde International Joint Research Institute Shunde China School of Information Science and Technology Sun Yat-sen University (SYSU) Guangzhou China

ISBN: (纸本)9781479979820

The Runge phenomenon illustrates that equidistant polynomial interpolation of the Runge function will cause wild oscillation near the endpoints of the interpolation interval as the order of the interpolation polynomial increases. In this paper, the pseudo inverse cubic spline (PCS) is presented to accurately approximate the Runge function at equidistant interpolation nodes and solve the problem of Runge phenomenon. PCS is constructed by employing the right pseudo inverse to figure out the minimum norm solution of the cubic spline's second-order derivatives. Thus, unlike the traditional cubic splines that additionally rely on endpoint constraints, PCS only employs the information of interpolation nodes. By PCS, the Runge function is effectively approximated without causing oscillation. Numerical experiments substantiate the efficacy and accuracy of PCS.

关键词： Splines (mathematics) Interpolation Polynomials Chebyshev approximation Oscillators

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Fault Diagnosis Based on Multi-scale LSTM-FCNs for Industrial Process

Fault Diagnosis Based on Multi-scale LSTM-FCNs for Industria...

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Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS), CAA Symposium on

作者： Shaojie Yang Peng Li Shuai Li Xiaofeng Zhou Shanghong Jiang Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China University of Chinese Academy of Sciences Beijing China Information Center of Ansteel Mining Limited Company Anshan China

ISBN: (纸本)9781665401166

Aiming at the characteristics of multi-scale, time series and nonlinear of the complex industrial process data, in order to extract process information more efficiently for improving the diagnosibility, a novel fault diagnosis method based on multi-scale long short term memory- fully convolutional networks (LSTM-FCNs) for industrial process is proposed. Firstly, variational mode decomposition (VMD) is used to obtain the multi-scale components of the process data. Then a parallel LSTM and FCNs optimized by batch normalization and random inactivation is built to extract features for each component. Finally, based on the fusion of multi-scale features, a fully connected layer is used for diagnosis. The LSTM-FCNs method is evaluated by the Tennessee Eastman (TE) benchmark industrial process, and compared with other methods, its effectiveness and superiority are verified.

关键词： Fault diagnosis Fault detection Time series analysis Benchmark testing Feature extraction Safety Data mining

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Fault Diagnosis Based on RseNet-LSTM for Industrial Process

Fault Diagnosis Based on RseNet-LSTM for Industrial Process

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IEEE Advanced Information Technology, Electronic and Automation control Conference (IAEAC)

作者： Peifu Yao Shaojie Yang Peng Li China Copper Co.LTD Kunming China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728180281

ISBN: (纸本)9781728180298

Aiming at the problems that conventional data-driven diagnosis methods are difficult to adaptively extract effective features from industrial process data, and do not make full use of the time series characteristics of process data, in this paper, a fault diagnosis method based on residual convolutional neural networks and long short-term memory networks (ResNet-LSTM) is developed. Firstly, the local spatial features of process data are captured by the deep residual convolution network. Then, the time series characteristics of process data are extracted by LSTM. Finally, the output of the fault category is performed through the softmax classifier. This method can extract features adaptively, more fully extract features in time series fault data, and effectively reduce the difficulty of deep neural network training. The benchmark Tennessee-Eastman (TE) process is used to validate performance of the proposed method. The ResNet-LSTM model is compared with the CNN, LSTM, ResNets, CNN-LSTM models, and the experiment results show that the ResNet-LSTM method achieves better performance.

关键词： Fault diagnosis Training Time series analysis Neural networks Process control Feature extraction Data mining

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From Newton Fractals to Gradient Fractals in Addition to Zhang Fractals

From Newton Fractals to Gradient Fractals in Addition to Zha...

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IEEE International Conference on Computational Science and Engineering, CSE

作者： Yunong Zhang Tianjian Qiao Bolin Liao Long Jin Junwei Chen School of Information Science and Technology Sun Yat-sen University (SYSU) Guangzhou China SYSU-CMU Shunde International Joint Research Institute Shunde China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Guangzhou China

ISBN: (纸本)9781479979820

The paper employs gradient dynamics (GD), in addition to Zhang dynamics (ZD), to generate new fractals which are quite different from the conventional Newton fractals (NF). The proposed gradient fractals (GF) have three types. Specifically, via appropriate iterative formulas derived in complex domain, the first-type and second-type fractals are generated, i.e., 1GF and 2GF. By expanding the conventional gradient formula from real domain to complex domain, the third-type fractals are thus obtained, i.e., 3GF. Besides, Zhang fractals (ZF) are yielded via solving static and time-variant equations using ZD. Numerical experiments substantiate the effectiveness of complex-valued GD and ZD for generating new fractals. Connections and differences among NF, GF and ZF are also revealed.

关键词： Fractals Noise measurement Nonlinear equations Educational institutions Logic gates Conferences

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Power-Activated WASD Neuronet Based Russian Population Estimation, Correction, and Prediction

Power-Activated WASD Neuronet Based Russian Population Estim...

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IEEE International Conference on Computational Science and Engineering, CSE

作者： Yunong Zhang Jianxi Liu Dongsheng Guo Sitong Ding Hongzhou Tan School of Information Science and Technology Sun Yat-sen University (SYSU) Guangzhou China SYSU-CMU Shunde International Joint Research Institute Shunde China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Guangzhou China

ISBN: (纸本)9781479979820

In recent years, the serious situation of Russian population causes concerns of the government, which also attracts great attentions of researchers from all over the world. The research on Russian population can help the government to make positive policies for solving the crisis and boosting economic growth. In this paper, implicitly considering almost all factors that influence population development, we present a 3-layer feed forward power-activated neuronet (PAN) equipped with the weights-and-structure-determination (WASD) algorithm for the estimation, correction and prediction of Russian population. Many numerical tests are conducted via WASD-PAN using past 2013-year Russian population data. We estimate the Russian population from 1000AD to 1800AD, correct it around 1897AD, and further indicate several possibilities of Russian population in the future. With the most possibility, Russian population is predicted to decrease steadily in next decade, while it is still possible that Russian population will (finally) increase.

关键词： Sociology Statistics Market research Estimation Neurons Data models Educational institutions

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Practical fractional-order variable-gain super-twisting control with application to wafer stages of photolithography systems

arXiv

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arXiv 2021年

作者： Kuang, Zhian Sun, Liting Gao, Huijun Tomizuka, Masayoshi Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin150001 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China Mechanical Control System Lab Mechanical Engineering Department University of California BerkeleyCA94720 United States

In this paper, a practical fractional-order variable-gain super-twisting algorithm (PFVSTA) is proposed to improve the tracking performance of wafer stages for semiconductor manufacturing. Based on the sliding mode control (SMC), the proposed PFVSTA enhances the tracking performance from three aspects: 1) alleviating the chattering phenomenon via super-twisting algorithm and a novel fractional-order sliding surface (FSS) design, 2) improving the dynamics of states on the sliding surface with fast response and small overshoots via the designed novel FSS and 3) compensating for disturbances via variable-gain control law. Based on practical conditions, this paper analyzes the stability of the controller and illustrates the theoretical principle to compensate for the uncertainties caused by accelerations. Moreover, numerical simulations prove the effectiveness of the proposed sliding surface and control scheme, and they are in agreement with the theoretical analysis. Finally, practice-based comparative experiments are conducted. The results show that the proposed PFVSTA can achieve much better tracking performance than the conventional methods from various perspectives. Copyright © 2021, The Authors. All rights reserved.

关键词： Sliding mode control

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Acoustically Driven Micropipette for Hydrodynamic Manipulation of Mouse Oocytes

Acoustically Driven Micropipette for Hydrodynamic Manipulati...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Zhaofeng Zuo Xiaoming Liu Zhuo Chen Yuyang Li Xiaoqing Tang Dan Liu Qiang Huang Tatsuo Arai Beijing Advanced Innovation Center for Intelligent Robots and Systems and School of Mechatronical Engineering Key Laboratory of Biomimetic Robots and Systems Ministry of Education State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China Center for Neuroscience and Biomedical Engineering The University of Electro-Communications Tokyo Japan

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Micromanipulation techniques that can achieve controlled fine operations at the micro scale play an important role in biomedical fields including embryo engineering, gene engineering, drug screening, and cell analysis. However, micromanipulation of biological micro-objects, such as cells and micro tissues, suffers from mechanical damage and low efficiency. Several techniques have been introduced to manipulate cells more easily, but most of them are restricted by expensive devices, limited work area, and potential damage to cellular structure. Here we develop a hydrodynamic manipulation method to rotate and transport mouse oocytes, which utilizes acoustic waves and micropipette to generate acoustic radiation force and excite microstreaming. This method can accomplish rotational and translational operations precisely and controllably. We tested the process of trapping, rotation, and transportation of the mouse oocytes, and measured rotational and translational speed with a range of applied voltage. The method was able to shorten the cost time of delivery and posture adjustment before oocyte injection. Our study provides an easy-to-use technique for oocyte manipulation without contact, and it has the potential to be universally applied in many cellular studies.

关键词： Visualization Voltage measurement Three-dimensional displays Force Transportation Hydrodynamics Biology

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Application of Complementary Sliding Mode control with state Observer in Servo System of Voice Coil Motor

Application of Complementary Sliding Mode Control with State...

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第34届中国控制与决策会议

作者： Yang Liu Danping Jia Bingjie Zhao Tao Zhang Hualiang Zhang Hongyu Yan Xu Lu School of Artificial Intelligence Shenyang University of Technology School of Information Science and Engineering Shenyang University of Technology Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences School of Electrica l Engineering Dalian University of Technology

ISBN: (纸本)9781665478977

Due to the vulnerability of the voice coil motor(VCM) servo system to uncertain elements such as external disturbance,nonlinear friction,and inherent end impact,a dynamic model of the linear servo motor motion system with uncertainty is *** complementary sliding mode variable structure controller(CSMC) is built on the basis of the standard sliding mode control by merging the generalized sliding mode surface with the complimentary sliding mode *** study demonstrates that this controller can ensure the system's tracking error converges,suppresses uncertain factors,increases the system's transient reaction speed,and successfully reduces tracking ***,the saturation function is chosen as the switching function,which mitigates the sliding mode control chattering *** total interference is defined as the unmeasured and unknown interference in the mathematical model of the *** system's position and total disturbance are estimated using the nonlinear extended state observer(ESO).The estimated total disturbance is then feed-forward corrected to the control *** a result,a nonlinear extended state observer-based closed-loop complementary sliding mode position control technique is ***,the system experiment demonstrates the effectiveness and feasibility of the suggested control *** complimentary sliding mode control system with state observer offers a high degree of tracking accuracy and robustness,which considerably minimizes the system's tracking error.

关键词： Voice coil motor Complementary sliding mode control Extended state observer Servo system

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A Self-organizing Cooperative Hunting by Swarm Robotic systems Based on Loose-preference Rule

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Acta Automatica Sinica 2013年第1期39卷 57-68页

作者： Tian-Yun HUANG Xue-Bo CHEN Wang-Bao XU Zi-Wei ZHOU Zhi-Yong REN School of Control Science and Engineering Dalian University of Technology Dalian 116024 China School of Electronics and Information Engineering Liaoning University of Science and Technology Anshan 114051 China State Key Laboratory of Robotics System Harbin Institute of Technology Harbin 150080 China

A novel self-organizing approach to cooperative hunting by swarm robotic systems is put forward. Firstly, an individual autonomous motion planning is presented, and the cooperative hunting behaviors are mathematically described. According to decomposition of hunting behaviors, the loose-preference rule is established for the individuals to form the ideal hunting formation during the self-organizing process by the interaction between the target and individuals. Then, we employ the proposed rule to design the autonomous motion controller of the individuals. Finally, the stability of self-organizing system is analyzed by Lyapunov stability criteria. Simulations and experiments demonstrate the feasibility and effectiveness of the proposed approach to cooperative hunting by swarm robotic systems.

关键词： Swarm robotic systems self-organizing cooperative hunting loose preference leader emergence

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