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RAM POSITION CONTROL IN PLASTIC INJECTION MOLDING MACHINES WITH HIGHER-ORDER ITERATIVE LEARNING

CONTROL AND INTELLIGENT SYSTEMS 2006年第1期34卷 64-72页

作者： Li, X. Ouyang, G. Guan, X. P. Du, R. Institute of Electrical Engineering Yanshan University Qinhuangdao Hebei 066004 China Department of Automation and Computer Aided Engineering Chinese University of Hong Kong Hong Kong Hong Kong City University of Hong Kong Hong Kong Hanover University Germany University of Birmingham United Kingdom Institute of Electrical Engineering Yanshan University China Institute of Electrical Engineering Yanshan University Qinhuangdao China IEEE China Council of Chinese Automation Committee China Council of Chinese Artificial Intelligence Committee China Department of Automation and Computer Aided Engineering Chinese University of Hong Kong (CUHK) Hong Kong Institute of Precision Engineering CUHK Hong Kong

In plastic injection molding, the ram position plays an important role in production quality. This paper introduces a new method, which is a combination of the current cycle feedback control (a PI controller) and a feed-forward higher-order iterative learning control (ILC), to control the ram position in injection molding. The PI controller is used to stabilize the system, and the feed-forward higher-order ILC control is used to compensate for nonlinear/unknown dynamics and disturbances, thereby gaining the precision tracking to ram position. The simulation results indicate that the new method outperforms the conventional PI controller. In addition, it outperforms the conventional ILC in the convergence performance.

关键词： Plastic injection molding iterative learning control ram velocity

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Experimental implementations of adaptive self-organizing fuzzy slide mode control to a 3-DOF rehabilitation robot

Experimental implementations of adaptive self-organizing fuz...

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3rd International Conference on Innovative Computing Information and Control, ICICIC'08

作者： Chang, Ming-Kun Yuan, Tsan-Hsiu Department of Mechanical and Computer-Aided Engineering St. John's University Institute of Automation and Mechatronics St. John's University

ISBN: (纸本)9780769531618

Pneumatic muscle actuator has many advantages such as high power/weight ratio, high power/volume ratio, low price, little maintenance needed, great compliance, and inherent safety. Therefore, it can be suitably applied to rehabilitation engineering for persons with neuromuscular or musculoskeletal pathologies affecting extremity functions. However, excellent control performance can hardly be achieved by classical control methods because gas compression and nonlinear elasticity of bladder containers cause parameter variations. An adaptive self-organizing fuzzy sliding mode control (ASOFSMC) is developed in this study to improve control performance. Experimental results show that this control strategy can achieve excellent control performance. © 2008 IEEE.

关键词： Sliding mode control

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Thermal comfort control based on neural network for HVAC application

Thermal comfort control based on neural network for HVAC app...

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2005 IEEE International Conference on Control Applications, CCA

作者： Liang, Jian Du, Ruxu Department of Automation and Computer-Aided Engineering Chinese University of Hong Kong Shatin N.T. Hong Kong

ISBN: (纸本)0780393538

This paper describes the design of a thermal comfort controller for indoor thermal environment regulation. In this controller, Predicted Mean Vote (PMV) is adopted as the control objective and six variables are taken into consideration. Meanwhile, a kind of direct neural network (NN) control is designed, and a thermal space model for Variable-Air-Volume (VAV) application is developed. Based on the computer simulation, it is seen that this thermal comfort controller can maintain the indoor comfort level within the desired range under both heating / cooling modes. Furthermore, by combining the energy saving strategy with the VAV application, it also shows the potential for energy saving in future. © 2005 IEEE.

关键词： Heating

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REAL-TIME SURVEILLANCE BASED ON HUMAN BEHAVIOR ANALYSIS

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International Journal of Information Acquisition 2005年第4期2卷 353-365页

作者： YONGSHENG OU HUIHUAN QIAN XINYU WU YANGSHENG XU Department of Automation and Computer-Aided Engineering The Chinese University of Hong Kong China

This paper introduces a real-time video surveillance system which can track people and detect human abnormal behaviors. In the blob detection part, an optical flow algorithm for crowd environment is studied experimentally and a comparison study with respect to traditional subtraction approach is carried out. The different approaches in segmentation and tracking enable the system to track persons when they change movement unpredictably in occlusion. We developed two methods for the human abnormal behavior analysis. The first one employs Principal Component Analysis for feature selection and Support Vector Machine for classification of human behaviors. The proposed feature selection method is based on the border information of four consecutive blobs. The second approach computes optical flow to obtain the velocity of each pixel for determining whether a human behavior is normal or not. Both algorithms are successfully developed in crowded environments to detect the following human abnormal behaviors: (1) Running people in a crowded environment; (2) falling down movement while most are walking or standing; (3) a person carrying an abnormal bar in a square; (4) a person waving hand in the crowd. Experimental results demonstrate these two methods are robust in detecting human abnormal behaviors.

关键词： Surveillance tracking human behavior modeling learning

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Associative memories based on discrete-time cellular neural networks with one-dimensional space-invariant templates

Associative memories based on discrete-time cellular neural ...

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

作者： Zeng, Zhigang Wang, Jun School of Automation Wuhan University of Technology Wuhan Hubei 430070 China Department of Automation and Computer-Aided Engineering Chinese University of Hong Kong Shatin New Territories Hong Kong

ISBN: (纸本)354034439X

In this paper, discrete-time cellular neural networks with one-dimensional space invariant are designed to associative memories. The obtained results enable both heteroassociative and autoassociative memories to be synthesized by assuring the global asymptotic stability of the equilibrium point and the feeding data via external inputs rather than initial conditions. It is shown that criteria herein can ensure the designed input matrix to be obtained by using one-dimensional space-invariant cloning template. Finally, one specific example is included to demonstrate the applicability of the methodology. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Neural networks

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Measuring path without tool center point function for B-type five-axis machine tool

Measuring path without tool center point function for B-type...

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2nd International Conference on engineering and Technology Innovation 2012, ICETI 2012

作者： She, Chen-Hua Jywe, Wen-Yuh Huang, Jheng-Jie Department of Mechanical and Computer Aided Engineering National Formosa University Taiwan Department of Automation Engineering National Formosa University 64 Wen-Hua Road Huwei Yunlin 632 Taiwan

ISBN: (纸本)9783037856123

Five-axis machine tools with three linear axes and two rotary axes can produce complex products with free-form surfaces requiring a high degree of precision. However, motion errors of each axis and its assembly error are accumulated in the positioning error of the cutting tool relative to a workpiece. There are many devices reported in the literature on the identification of kinematic errors based on the measurement of the motion error. According to the measurement paths in the ISO draft, ISO/CD 10791-6, the kinematic tests can be applicable to different configurations of five-axis machine tools. However, the advanced controller with tool center point (TCP) function is required while performing kinematic tests. This paper proposed the methodology of generating measurement path without TCP function for B-type five-axis machine tool. The developed module can transform the measuring path into an NC program used for lower hand controller. Verification using VERICUT? solid cutting simulation software demonstrated the veracity of the generated five-axis NC code. The proposed methodology is applicable in a wide range of five-axis machine tool configurations;however, further testing with actual measuring applications will be required for further verification. © (2013) Trans Tech Publications, Switzerland.

关键词： Kinematics

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Experimental studies on carbon nanotube composites for vibration damping

Experimental studies on carbon nanotube composites for vibra...

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17th International Conference on Adaptive Structures and Technologies, ICAST 2006

作者： Dai, R.L. Liao, W.H. Smart Materials and Structures Laboratory Department of Automation and Computer-Aided Engineering Chinese University of Hong Kong Shatin N.T. Hong Kong

ISBN: (纸本)9781605601250

It has been found that the composites of carbon nanotubes (CNTs) and epoxy resin could greatly enhance damping ability while the stiffness is kept at a very high level. In this research, carbon nanotube enhanced epoxy resin is fabricated. The dynamic properties of the nanotube composites are experimentally studied. A testing apparatus for obtaining material properties is set up and measurement procedures are given. Multiple groups of specimens are made for investigations. In particular, the material loss factors together with dynamic stiffness are measured for the specimens with different CNT weight ratio. Experimental results show that CNT additive can provide the composite with significant damping without easily undergoing large strain as compared to traditional damping materials, and the dynamic stiffness of the nanotube composite could be even higher than the pure epoxy. It is promising that the nanotube composites could be used in the structural vibration applications when both damping and stiffness are important.

关键词： Carbon nanotubes

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Robust stabilizing controller by grid point design and composite SVD consolidation 4

Robust stabilizing controller by grid point design and compo...

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4th IFAC Symposium on Robust Control Design, ROCOND 2003

作者： Yam, Yeung Baranyi, Peter Department of Automation and Computer-Aided Engineering Chinese University of Hong Kong Shatin Hong Kong Department of Telecommunications and Telematics Budapest University of Technology and Economics Budapest Hungary

This work introduces a computational based approach to design stabilizing controllers for a class of uncertain nonlinear plant. The approach calls for generating the plant's linear approximations over a set of grid points and then obtaining robust stabilizing controllers for the grid point models. The composite sets of models and controllers are then consolidated jointly using a recent singular value-based method, resulting in an unified fuzzy structure. Necessary and sufficient test for global stability can then be applied on the consolidated closed loop system. The present approach improves certain aspects over a previous one, which bases its control system design on the inherent fuzzy structure of the plant. © 2003 IFAC.

关键词： Robust control

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Asymptotic Tracking of a Class of Uncertain Nonlinear Systems in Strict-Feedback Form

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IFAC Proceedings Volumes 2001年第13期34卷 603-607页

作者： Dan Wang Jie Huang Department of Automation and Computer-Aided Engineering The Chinese University of Hong Kong

Recently adaptive neural network controllers for a class of high uncertain nonlinear systems in strict-feedback form have been developed using the backstepping technique. The resulting closed-loop system is shown to be ultimately uniformly stable with bounded tracking error. In this paper, we will present a modified design technique, which guarantees the convergence of the tracking error to zero.

关键词： adaptive control neural networks nonlinear control strict-feedback systems

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A delayed lagrangian network for solving quadratic programming problems with equality constraints

A delayed lagrangian network for solving quadratic programmi...

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

作者： Liu, Qingshan Wang, Jun Cao, Jinde Department of Automation and Computer-Aided Engineering Chinese University of Hong Kong Shatin New Territories Hong Kong Department of Mathematics Southeast University Nanjing 210096 China

ISBN: (纸本)354034439X

In this paper, a delayed Lagrangian network is presented for solving quadratic programming problems. Based on some known results, the delay interval is determined to guarantee the asymptotic stability of the delayed neural network at the optimal solution. One simulation example is provided to show the effectiveness of the approach. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Lagrange multipliers

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