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Structural Topology Optimization Using Level Set Method

Structural Topology Optimization Using Level Set Method

引用

The 10th EPMESC

作者： Michael Yu Wang Department of Automation & Computer-Aided Engineering The Chinese University of Hong Kong Shatin NT Hong Kong China

In this paper, we specifically put forth the level set method, in which the shape of a structure is employed and modified directly such that certain design objectives are obtained. It yields a complet

关键词： topology optimization, level-set method, bridge type structure

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Semi-global robust stabilization of a class of feedforward systems

Semi-global robust stabilization of a class of feedforward s...

引用

American Control Conference (ACC)

作者： Minghui Zhu Jie Huang Department of Automation and Computer-Aided Engineering Chinese University of Hong Kong New Territories Hong Kong China

This paper studies the robust stabilization of a class of nonlinear systems in feedforward form that is subject to both dynamic uncertainty and time-varying static uncertainty. For this purpose, a nonlinear small gain theorem with restrictions for time-varying nonlinear systems is established first. Then the small gain theorem is applied to achieve semi-global robust stabilization for the class of feedforward systems in the presence of both dynamic and static uncertainties

关键词： Robustness Feedforward systems Uncertainty Nonlinear systems Nonlinear dynamical systems Time varying systems Automatic control State feedback Councils automation

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A Recurrent Neural Network for Solving Nonconvex Optimization Problems

A Recurrent Neural Network for Solving Nonconvex Optimizatio...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Xiaolin Hu Jun Wang Department of Automation and Computer-Aided Engineering Chinese University of Hong Kong New Territories Hong Kong China

An existing recurrent neural network for convex optimization is extended to solve nonconvex optimization problems. One of the prominent features of this neural network is the one-to-one correspondence between its equilibria and the Karush-Kuhn-Tucker (KKT) points of the nonconvex optimization problem. The conditions are derived under which the neural network (locally) converges to the KKT points. It is desired that the neural network is stable at minimum solutions, and unstable at maximum solutions or saddle solutions. It is found in the paper that most likely the neural network is unstable at the maximum solutions. Moreover, we found that if the derived conditions are not satisfied at minimum solutions, by transforming the original problem into an equivalent one with the p-power (or partial p-power) method, these conditions can be satisfied. As a result, the neural network will locally converge to a minimum solution. Finally, two illustrative examples are provided to demonstrate the performance of the recurrent neural network.

关键词： Recurrent neural networks Neural networks Hopfield neural networks Convergence Annealing Stability Equations Councils automation Parallel algorithms

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A Remark on Stabilization of Chua's Circuit

A Remark on Stabilization of Chua's Circuit

引用

Chinese Control Conference (CCC)

作者： Lu Liu Jie Huang Department of Automation and Computer-Aided Engineering Chinese University of Hong Kong New Territories Hong Kong China

Chua's circuit has been a test-bed for studying various control problems such as chaos cancellation, synchronization, or stabilization. The circuit has been viewed as a lower triangular system and controlled as such by various state feedback control methods. In this note, we first point out that Chua's circuit can be viewed as a nonlinear system in output feedback form. Therefore, it can be controlled by output feedback control law using some well established control techniques for output feedback systems. As an illustration, we have designed a simple adaptive robust output feedback control law to globally stabilize the circuit with arbitrary variations of the parameters of the circuit.

关键词： Control systems Feedback circuits Output feedback Circuit testing Chaos State feedback Nonlinear systems Programmable control Adaptive control Robust control

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Haptic modeling and experimental validation for interactive endodontic simulation

Haptic modeling and experimental validation for interactive ...

引用

IEEE International Conference on Robotics and automation (ICRA)

作者： Min Li Yun-Hui Liu Department of Automation and Computer-Aided Engineering Chinese University of Hong Kong Sha Tin Hong Kong China

To facilitate training of endodontic operations, we have developed an interactive virtual environment to simulate endodontic shaping. This paper presents methodologies for haptic modeling, display and validation of endodontic shaping. We first investigate the forces generated in the course of shaping operations and discuss the challenging issues in their modeling. Based on the special properties and constraints associated with both pulpal tissue and endodontic files, we propose a haptic model to simulate endodontic shaping operations, which is a smoothed particle based dynamic model derived for the pulpal tissue coupled with a finite element model for the endodontic files. Furthermore, the effectiveness of the proposed model has been validated by experimental results through a novel robotic endodontic measurement system

关键词： Haptic interfaces Irrigation Computational modeling Dentistry Medical simulation Deformable models Virtual environment Finite element methods Teeth Accidents

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Uncalibrated visual tracking control without visual velocity

Uncalibrated visual tracking control without visual velocity

引用

IEEE International Conference on Robotics and automation (ICRA)

作者： Hesheng Wang Yun-Hui Liu Department of Automation and Computer Aided Engineering Chinese University of Hong Kong Sha Tin Hong Kong China

This paper presents a new adaptive controller for dynamic tracking of a robot manipulator without visual velocity when the intrinsic and extrinsic parameters of the camera are not calibrated. Most controllers in the past require the measurement of the visual velocity or differentiation of the visual position. The measurement of the visual velocity is subject to big noises in general due to low sampling rates of the vision loop. To avoid performance decaying caused by measurement errors of the visual velocity, the controller we developed requires estimated visual velocity only. With a full consideration of dynamic responses of the robot manipulator, we employed the Lyapunov method to prove the convergence of the image errors of the trajectory to zero and the convergence of the estimated parameters to the real values up to a scale. Experiments have been conducted to demonstrate good convergence of the trajectory errors of the robot under the control of the proposed method

关键词： Velocity control Manipulator dynamics Convergence Velocity measurement Programmable control Adaptive control Robot vision systems Cameras Position measurement Noise measurement

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Multi-agent Based Surveillance

Multi-agent Based Surveillance

引用

2006 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Yufeng Chen Zhi Zhong Ka Keung Lee Yangsheng Xu Department of Automation and Computer-Aided Engineering Chinese University of Hong Kong Hong Kong China Department of Automation Shanghai JiaoTong University Shanghai China

Taking as reference the concept of agent in the artificial intelligence, this paper proposes a new multi-agent approach which can be employed in the surveillance for a people group in public places rather than a single person. The agent embodies the state and logic relationship between the person which the agent represents and the others in the same group. It does not merely stand for such individual information of persons as given by the existing surveillance systems. The results of experiments show that by using our multi-agent approach to compute and analyze the relationship between a number of agents, we can well perform real-time surveillance for the group and the related events so as to enhance the applicability and intelligence level of surveillance systems

关键词： Surveillance Security Humans Cameras Robotics and automation Artificial intelligence computer vision Target tracking Intelligent robots Logic

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Global stability of a recurrent neural network for solving pseudomonotone variational inequalities

Global stability of a recurrent neural network for solving p...

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Xiaolin Hu Jun Wang Department of Automation and Computer-Aided Engineering Chinese University of Hong Kong New Territories Hong Kong China

Solving variational inequality problems by using neural networks are of great interest in recent years. To date, most work in this direction focus on solving monotone variational inequalities. In this paper, we show that an existing recurrent neural network proposed originally for solving monotone variational inequalities can be used to solve pseudomonotone variational inequalities with proper choice of a system parameter. The global convergence, global asymptotic stability and global exponential stability of the neural network are discussed under various conditions. The existing stability results are thus extended in view of the fact that pseudomonotonicity is a weaker condition than monotonicity

关键词： Recurrent neural networks Neural networks Asymptotic stability computer networks Jacobian matrices Convergence automation Circuit stability Piecewise linear techniques Telecommunication traffic

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Crowd Density Estimation Using Texture Analysis and Learning

Crowd Density Estimation Using Texture Analysis and Learning

引用

IEEE International Conference on Robotics and Biomimetics

作者： Xinyu Wu Guoyuan Liang Ka Keung Lee Yangsheng Xu Department of Automation and Computer-Aided Engineering Chinese University of Hong Kong New Territories Hong Kong China

This paper presents an automatic method to detect abnormal crowd density by using texture analysis and learning, which is very important for the intelligent surveillance system in public places. By using the perspective projection model, a series of multi-resolution image cells are generated to make better density estimation in the crowded scene. The cell size is normalized to obtain a uniform representation of texture features. In order to diminish the instability of texture feature measurements, a technique of searching the extrema in the Harris-Laplacian space is also applied. The texture feature vectors are extracted from each input image cell and the support vector machine (SVM) method is utilized to solve the regression problem of calculating the crowd density. Finally, based on the estimated density vectors, the SVM method is used again to solve the classification problem of detecting abnormal density distribution. Experiments on real crowd videos show the effectiveness of the proposed system.

关键词： Surveillance Support vector machines Videos Support vector machine classification Image texture analysis Machine learning Magnetic heads Disaster management Image edge detection Image segmentation

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Quantum optimal control of nonlinear dynamics systems described by Klein-Gordon-Schrodinger equations

Quantum optimal control of nonlinear dynamics systems descri...

引用

American Control Conference (ACC)

作者： Quan-Fang Wang Department of Automation and Computer-Aided Engineering Chinese University of Hong Kong New Territories Hong Kong China

This paper is to develop a theoretical and computational framework for the analysis of quantum optimal control systems given by Klein-Gordon-Schrodinger (K-G-S) equations. In the case of one dimensional spatial and continuous time, a semi-discrete numerical algorithm is constructed to find optimal control of the nonlinear dynamics system. Furthermore, numerical experiments are implemented to show the effectiveness and convergency of proposed scheme for different parameters

关键词： Optimal control Nonlinear equations Control systems Quantum mechanics Quantum computing Open loop systems Control theory Noise reduction Laser theory Optical control

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