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6th International Conference on Spoken Language Processing, ICSLP 2000

作者： Wang, Chengfa Wang, Qiusheng Dept. of Computer Science and Engineering Harbin Institute of Technology Harbin150001 China Dept. of Automatic Measurement and Control Harbin Institute of Technology Harbin150001 China

ISBN: (纸本)7801501144

This paper presents a novel watermarking technique for digital audio signals. A visually recognizable binary image served as a watermark is embedded into an audio signal in discrete cosine transform domain. In order to enhance robustness and make good use of masking characteristics of the audio signal, the techniques of pseudo-random permutation and energy-based permutation are used during watermarking. The experimental results show that the proposed watermarking technique is robust to several signal manipulations, such as filtering, compression, and so on.

关键词： Binary images

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Robust fuzzy and recurrent neural network motion control among dynamic obstacles for robot manipulators

Robust fuzzy and recurrent neural network motion control amo...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： J.B. Mbede X. Huang M. Wang Robotics Laboratory Automatic Control Engineering Department Huazhong University of Science and Technology Wuhan China

An integration of a fuzzy controller and modified Elman neural networks (NN) approximation-based computed-torque controller is proposed for motion control of autonomous manipulators in dynamic and partially known environments containing moving obstacles. The navigation technique of robot control using artificial potential fields is based on the fuzzy controller. The NN controller can deal with unmodeled bounded disturbances and or unstructured unmodeled dynamics of the robot arm. The NN weights are tuned online, with no off-line learning phase required. The stability of the closed-loop system is guaranteed by the Lyapunov theory. The purpose of the controller, which is designed as a neuro-fuzzy controller, is to generate the commands for the servo-systems of the robot so it may choose its way to its goal autonomously, while reacting in real-time to unexpected events. The proposed scheme has been successfully tested. The controller also demonstrates remarkable performance in adaptation to changes in manipulator dynamics. Sensor-based motion control is an essential feature for dealing with model uncertainties and unexpected obstacles in real-time world systems.

关键词： Robust control Fuzzy control Fuzzy neural networks Recurrent neural networks Motion control Neural networks Manipulator dynamics Artificial neural networks computer networks Navigation

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Powertrain modeling with modelica

Powertrain modeling with modelica

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ASME 2000 International Mechanical engineering Congress and Exposition, IMECE 2000

作者： Tiller, Michael Davis, Cleon Tummescheit, Hubertus Trigui, Nizar Ford Motor Company Scientific Research Laboratory 2101 Village Road DearbornMI48197 United States School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332-0250 United States Department of Automatic Control Lund Institute of Technology Box 118 LundSE-22100 Sweden

ISBN: (纸本)9780791826645

In this paper we will describe the development of models for prediction of powertrain performance. Our goal is to develop a library of components to model combustion, gas dynamics and mechanical response. We will also demonstrate the ease with which we can replace traditional component models (e.g., mechanically actuated valves) with non-traditional component models (e.g., electro-mechanically actuated valves) without having to change or reformulate any of the other components in our system. The models were developed using the Modelica modeling language (Modelica Design Group, 1999) which allows component-based descriptions of behavior for complex engineering systems. Modelica is particularly well suited for creating behavioral models that are typical for powertrain plant models In addition to writing component models, the freely available Modelica Standard Library contains basic models from various engineering disciplines (e.g., resistors, shafts, springs). With this approach, models can be symbolically preprocessed to improve computational performance. In addition, code can be generated from the Modelica model which can be used as either a stand alone analysis tool, imported into Simulink1 as an S-function or downloaded for use in real-time hardware in the loop experiments. © 2000 by ASME

关键词： Gas dynamics

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Distributed modular computer-integrated surgical robotic systems: Implementation using modular software and networked systems 3rd

Distributed modular computer-integrated surgical robotic sys...

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3rd International Conference on Medical Image Computing and computer-Assisted Intervention, MICCAI 2000

作者： Bzostek, Andrew Kumar, Rajesh Hata, Nobuhiko Schorr, Oliver Kikinis, Ron Taylor, Russell H. Department of Computer Science Johns Hopkins University BaltimoreMD United States Surgical Planning Laboratory Brigham and Women’s Hospital and Harvard Medical School BostonMA United States Institute of Process Control and Robotics University of Karlsruhe Germany Engineering Research Center for Computer Integrated Surgical Systems and Technology Germany

ISBN: (纸本)3540411895

We seek to build CIS research systems within a flexible, open architecture. In this paper, we outline our solutions to the problems of system design, construction, and integration in this environment: building distributed, modular systems for sensing, control, and processing. Based on our experience building these systems, we utilize distributed network architectures, modular software components, and intelligent object distribution to maximize flexibility while complying with the particular needs and interfaces of specific components. While a work in progress, these approaches have been integrated into several systems in development and have demonstrated significant utility, based on construction time and system flexibility. This paper will discuss the first two aspects: modular software and basic network architectures, while intelligent object distribution is presented in a companion paper. Based on the applications we have targeted and technologies we have used, this paper introduces our architecture and its components. It then presents the system’s current state and finally, discusses plans for future improvements and extensions. © Springer-Verlag Berlin Heidelberg 2000.

关键词： Network architecture

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An effective uniform genetic algorithm for hard optimization problems

An effective uniform genetic algorithm for hard optimization...

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World Congress on Intelligent control and Automation (WCICA)

作者： Wang Yuping Liu Hailin Yiu-Wing Leung Faculty of Science Xidian University Xi'an China Department of Automatic Control Engineering South China University of Technology Guangzhou China Department of Computer Scienc Hong Kong Baptist University Hong Kong China

Genetic algorithms are one of the effective algorithms for hard optimization problems. They can escape from the local minima, however, the amount of their computation is often large. To decrease the amount of the computation and enhance the algorithms, the uniform design is combined into the genetic algorithm. The new genetic operator has the local-search property similar to that in traditional optimization techniques and needs a minimal amount of computation in certain meanings. Thus the new genetic algorithm can generate a diversity of population and explore the search space effectively. Moreover, the new algorithm is globally convergent. The numerical results also show the effectiveness of the new algorithm with its less computation, and higher convergent speed for all test functions.

关键词： Genetic algorithms Algorithm design and analysis Space exploration Scattering Optimization methods automatic control Genetic engineering Testing engineering management Operations research

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On-line Reconfiguration of Real-Time Robot Motion and Force control

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IFAC Proceedings Volumes 2000年第27期33卷 171-176页

作者： A. Robertsson A. Valera K. Nilsson R. Johansson Dept. of Automatic Control Lund University SE-22100 Lund Sweden Dept. of Systems Engineering & Automation Valencia Technical University ES-46022 Valencia Spain Dept of Computer Science Lund Institute of Technology Lund University SE-22100 Lund Sweden

Combining position and force control is highly desirable in many robot applications. Many years of extensive research has resulted in a number of promising control approaches, but often too much engineering effort is required in order to evaluate a low level (high performance) control scheme on a real manipulator. The new control system we have obtained has two main advantages: first it provides a total open control architecture, and second it is the simplicity and the interactivity of the platform developed. Using this new control architecture, any force and motion control strategy can be programmed and implemented in a graphical and easy way.

关键词： Robot control Force control Embedded systems Rapid prototyping Non-linear control

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Chaotification of continuous-time systems via time-delay feedback

Chaotification of continuous-time systems via time-delay fee...

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International Conference on control of Oscillations and Chaos

作者： Xiao Fan Wang Guanrong Chen Xinghuo Yu Department of Automatic Control Nanjing University of Science and Technology of PLA Nanjing China Department of Electrical and Computer Engineering University of Houston Houston TX USA Department of Information and Communication Central Queensland University Rockhampton QLD Australia

ISBN: (纸本)0780364341

In this paper, a systematic design approach based on time-delay feedback is developed for chaotification of a continuous-time, feedback linearizable system. The chaotification is accomplished based on nonlinear control theory and an approximate relationship between a time-delay differential equation and a discrete map. An example is given to illustrate the systematic design procedure.

关键词： Chaos Chaotic communication Differential equations control systems control theory State feedback Delay Difference equations Ear Feedback control

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Application of a genetic algorithm in triangulation of a 3-D object surface

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International Journal of computers and Applications 2000年第2期22卷 73-77页

作者： Zhenyu, Chen Mbede, J.B. Yan, Zhou Dehua, Li Hanping, Hu State Commn. Res. Open Lab. Image P. Inst. Pattern Recog. Artif. Intell. Huazhong Univ. of Sci. and Technol. 430074 Wuhan China Intelligent Contr. and Robotics Lab. Dept. of Contr. Sci. and Engineering Huazhong Univ. of Sci. and Technol. 430074 Wuhan China Second Artillery Institute Huazhong Univ. of Sci. and Technol. Inst. Pattern Recog. Artif. Intell. Huazhong Univ. of Sci. and Technol. Second Artillery Institute China Wuhan University China Artificial Intelligence Department University of Edinburgh Inst. of AI and Pattern Recognition Huazhong Univ. of Sci. and Technol. China Cogn. Sci. Natl. Key Found. Res. P. Douala University Cameroon Tübingen University Germany Automatic Control Laboratory Darmstadt University Department of Service Cameroon Min. of National Education Robotics Laboratory Huazhong Univ. of Sci. and Technol. Wuhan China Assoc. Connectionnistes These-ACTH Rennes France IEEE Soc. of Robotics and Automation IEEE Society of Control Systems IASTED Assoc. Jeunes Chercheurs Robotique France Navy University of Engineering China Huazhong Univ. of Sci. and Technol. China Department of Computer Science Airforce Radar Acad. of Engineering China Inst. of P.R and AI Huazhong Univ. of Sci. and Technol.

This paper proposes a genetic-based algorithm for surface reconstruction of three-dimension (3-D) objects from a group of contours representing its section plane lines. The algorithm can optimize the triangulation of the surface of 3-D objects with a multi-objective optimization function to meet the needs of a wide range of applications. Further, a new crossover operator for triangulation and a new 3-D quadrilateral mutation operator are also introduced.

关键词： Object recognition

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Generalised nonlinear PID controller based on neural networks

Generalised nonlinear PID controller based on neural network...

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1999 Information, Decision and control, IDC 1999

作者： Tan, Yonghong Dang, Xuanju Van Cauwenberghe, A. School of Computer Science Guilin Institute of Electronic Technology Guilin541004 China Automatic Control Laboratory University of Ghent Technologiepark 9 GhentB-9052 Belgium

ISBN: (纸本)0780352564

In this paper, a nonlinear controller is proposed to handle some nonlinear control problems. In this scheme, the controller uses the system error, the integral of the system error, and the derivative of the system error as its inputs, but the mapping from the inputs to the output is nonlinear. The corresponding nonlinear mapping may be specified based on the control requirement. Therefore, the proposed controller is defined as a generalized nonlinear PID controller (GNPIDC). The GNPIDC strategy is realized using neural networks. For online training of the neural network based GNPIDC, a PID gradient descent optimizing algorithm with momentum term is proposed. Then, the convergent characteristic of the algorithm is presented. Finally, simulation study of applying the neural GNPIDC strategy to a continuous-stirred-Tank-reactor and a van de Vusse reactor is illustrated. © 1999 IEEE.

关键词： controllers

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Generalised nonlinear PID controller based on neural networks

Generalised nonlinear PID controller based on neural network...

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Information, Decision and control (IDC)

作者： Yonghong Tan Xuanju Dang A. van Cauwenberghe School of Computer Science Guilin Institute of Electronic Technology Guilin China Automatic Control Laboratory University of Ghent Ghent Belgium

In this paper, a nonlinear controller is proposed to handle some nonlinear control problems. In this scheme, the controller uses the system error, the integral of the system error, and the derivative of the system error as its inputs, but the mapping from the inputs to the output is nonlinear. The corresponding nonlinear mapping may be specified based on the control requirement. Therefore, the proposed controller is defined as a generalized nonlinear PID controller (GNPIDC). The GNPIDC strategy is realized using neural networks. For online training of the neural network based GNPIDC, a PID gradient descent optimizing algorithm with momentum term is proposed. Then, the convergent characteristic of the algorithm is presented. Finally, simulation study of applying the neural GNPIDC strategy to a continuous-stirred-tank-reactor and a van de Vusse reactor is illustrated.

关键词： Three-term control Neural networks Proportional control Process control automatic control Error correction Inductors control systems Nonlinear control systems computer errors

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