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Adaptive tracking controller using BP neural networks for a class of nonlinear systems

Chinese Journal of Systems engineering and Electronics 2004年第4期000卷

An BP neural-network-based adaptive control (NNAC) design method is described whose aim is to control a class of partially unknown nonlinear systems. Making use of the online identification of BP neural networks, the results of the identification could be used into the parameters of the controller. Not only the strong robustness with respect to uncertain dynamics and nonlinearities can be obtained, but also the output tracking error between the plant output and the desired reference output can asymptotically converge to zero by Lyapunov theory in the process of this design *** a simulation example is also presented to evaluate the effectiveness of the design.

关键词： BP neural networks nonlinear systems robustness uncertain dynamics

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Relative entropy multilevel thresholding method based on genetic optimization

Relative entropy multilevel thresholding method based on gen...

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2003 International Conference on Neural Networks and Signal Processing, ICNNSP'03

作者： Yang, Zhao-Hua Pu, Zhao-Bang Qi, Zhen-Qiang Department of Automation Measurement and Control Harbin Institute of Technology Harbin 150001 China Department of Control Science and Engineering Harbin Institute of Technology Harbin 150001 China

ISBN: (纸本)0780377028

Traditional optimal thresholding methods are very computationally expensive when extended to multilevel thresholding for their exhaustively search mode. So their applications are limited. In this paper, a relative entropy multilevel thresholding method based on genetic algorithm (RE-GA) is developed. The proposed method makes use of GA's properties such as high efficiency, rapid convergence and global optimization. The relative entropy is treated as the fitness function. Applying the proposed method to process image, the computation speed is accelerated and the quality is improved. Simulation results verify the performance of the proposed method by comparison with the traditional optimal thresholding methods. © 2003 IEEE.

关键词： Global optimization

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Experiment study of magnetorheological fluid actuator performance

Experiment study of magnetorheological fluid actuator perfor...

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Proceedings of the International Symposium of Young Scholars on Mechanics and Material engineering for science and Experiments

作者： Guan, X.Ch. Ou, J.P. Res. Stn. Mat. Sci./Eng. P.F. Harbin Inst. of Technology Harbin China Department of Civil Engineering Harbin Inst of Technology Harbin China 700 Box Harbin University of Technology Second Domain Hai He road 202 Nan Gang Harbin China

ISBN: (纸本)1880132796

Magnetorheological fluid (MRF) actuator is one kind of new ideal semi-active control devices for civil engineering structures and vehicles anti-vibration. In this paper, firstly, the structure and mechanism of our MRF actuator is introduced. Secondly, the damping force of our MRF actuator is tested, the characteristic of the damping force is analyzed, and an improved Bouc-Wen model of damping force is built. Thirdly, the response time of our MRF actuator is tested. The testing results shows that the response time is about hundreds milliseconds, much bigger than theory results. Finally, a simplified method for analyzing the response time of MRF actuator is built, and it shows that it is the air bubbles in fluid that delay the response time of MRF actuator.

关键词： Rheology

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Relative entropy multilevel thresholding method based on genetic optimization

Relative entropy multilevel thresholding method based on gen...

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International Conference on Neural Networks and Signal Processing

作者： Zhao-hua Yang Zhao-bang Pu Zhen-qiang Qi Department of Automation Measurement and Control Harbin Institute of Technology Harbin China Department of Control Science and Engineering Harbin Institute of Technology Harbin China

ISBN: (纸本)0780377028

关键词： Entropy Optimization methods Image segmentation Histograms Optimal control Automatic control Genetic algorithms Acceleration Automation Computational modeling

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Flight guidance control using genetic algorithm combined with singular perturbation technique

Flight guidance control using genetic algorithm combined wit...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Zhen-Qiang Qi Guang-Da Hu Zhao-Hua Yang Fu-En Zhang Department of Control Science and Engineering Harbin Institute of Technology Harbin China Department of Automatic Measurement and Control Harbin Institute of Technology Harbin China

ISBN: (纸本)0780378652

An advanced midcourse guidance law based on genetic algorithm (GA) and singular perturbation technique (SPT) is proposed in this paper. The proposed midcourse guidance formulation minimizes the flight time and maximizes terminal energy subject to a terminal intercept condition. GA is used to search the optimal attack angle for the flight trajectory, and SPT is applied to approximate the terminal flight time. By combining GA and SPT, the optimal flight guidance law is obtained consequently. Meanwhile, the paper completely eliminates the need for solving two-point boundary-value problems (TBPVP), which is too complex for derivation and implementation. The simulation results show that the resulting guidance law is near-optimal and the proposed method is valid.

关键词： Genetic algorithms Perturbation methods Automatic control Nonlinear equations Missiles Sliding mode control Trajectory Aerospace engineering Genetic engineering Proportional control

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Robust filtering with l/sub 2/-l/sub /spl infin// performance for uncertain discrete-time systems with multiple state delays

Robust filtering with l/sub 2/-l/sub /spl infin// performanc...

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American control Conference (ACC)

作者： Huijun Gao Changhong Wang Department of Control Science and Engineering Harbin Institute of Technology Harbin China

ISBN: (纸本)0780378962

This paper deals with the robust l/sub 2/-l/sub /spl infin// filtering problem for discrete-time systems with multiple delays in the state and uncertain parameters residing in a polytope. Attention is focused on the design of robust full order and reduced order filters guaranteeing a prescribed energy-to-peak disturbance attenuation level. Sufficient conditions for the existence of admissible filters are formulated in terms of linear matrix inequalities, upon which both the delay-independent and dependent filtering problems are cast into convex optimization problems. These two approaches also incorporate a new parameter-dependent stability result into the filter designs, which greatly reduces the conservatism of the quadratic framework. The proposed filter design methods are applicable to systems either with or without known delay bounds. Illustrative examples are provided to demonstrate the effectiveness of the proposed filter design methodologies.

关键词： Robustness Filtering Filters Delay effects Delay estimation Noise level Attenuation Erbium Noise measurement Time measurement

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An immunity-based optimization algorithm for tuning neuro-fuzzy controller

An immunity-based optimization algorithm for tuning neuro-fu...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Xing-Quan Zuo Shi-Yong Li Xiao-Jun Ban Department of Control Science and Engineering Harbin Institute of Technology Harbin China

ISBN: (纸本)0780378652

Immune evolutionary algorithm is proposed based on the evolutionary principle in the immune system. In the algorithm, two new parameters of expansion radius and mutation radius are defined to construct a small neighborhood and a large neighborhood. Then expansion and mutation operations are designed to perform local and global search respectively by using the two neighborhoods, thus, two-level neighborhood search mechanism is realized. The results of multi-modal function optimization show that the algorithm has nice global and local searching performances. The algorithm is employed to design a neuro-fuzzy controller for real-time control of an inverted pendulum. In order to avoid the combinatorial explosion of fuzzy rules due to multivariable inputs, state variable synthesis scheme is suggested to reduce the number of fuzzy rules. Experimental results show that the designed controller can control actual inverted pendulum successfully.

关键词： Immune system Evolutionary computation Genetic algorithms Shape Genetic mutations Algorithm design and analysis control systems Humans Body sensor networks Explosions

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Novel edge preserving multiscale filtering method based on mathematical morphology

Novel edge preserving multiscale filtering method based on m...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Zhao-Hua Yang Zhao-Bang Pu Zhen-Qiang Qi Department of Automation Measurement and Control Harbin Institute of Technology Harbin China Department of Control Science and Engineering Harbin Institute of Technology Harbin China

ISBN: (纸本)0780378652

During the course of conventional multiscale morphological filtering, when the noise is filtered, the signals which are smaller than the structuring elements (SE) may be also removed. In this paper, a novel edge preserving multiscale filtering (EPMF) method based on mathematical morphology is proposed. The EPMF method adds the multiscale top-hat transformation and bottom-hat transformation to the conventional multiscale morphological opening and closing filtering. The two added transformations are used to extract and smooth the features which are smaller than the current scale. It is also found that the smaller features have greater possibilities to contain noise particles. Accordingly, the coefficients of top-hat transformation and bottom-hat transformation are modified. Simulation results on the standard gray-level images show that the proposed EPMF method can effectively remove noise and completely preserve the edge of images. It demonstrates better performance than the conventional filtering methods.

关键词： Morphology Filtering theory Automatic control Image recognition Image analysis Inspection Image processing Morphological operations Automation Noise measurement

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Speed control of a DC motor using BP neural networks

Speed control of a DC motor using BP neural networks

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IEEE Conference on control technology and Applications (CCTA)

作者： Zilong Liu Xianyi Zhuang Shuyi Wang Department of Control Science and Engineering Harbin Institute of Technology Harbin China

ISBN: (纸本)078037729X

In tackling the problem of the speed control of a DC motor, the conventional constant gain feedback controller fails to maintain the performance of the system at acceptable levels under unknown in dynamics load torque. Meanwhile, artificial neural networks, so far acting as the effective tools to implement the model and adaptive control in a complicated nonlinear system, have got extensive applications. Thus in order to shun the drawbacks of the conventional constant gain feedback controller, this paper makes use of the power of feedforward artificial neural networks to identify and control online, and therefore modulate a rational control rate. Finally, this method is proven to be feasible by virtue of the simulation results.

关键词： Velocity control DC motors Neural networks Artificial neural networks Adaptive control Nonlinear dynamical systems Feedforward neural networks Motor drives Difference equations Rotors

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A fast approach to building rough data model through G-K fuzzy clustering

A fast approach to building rough data model through G-K fuz...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Jin-Jie Huang Shi-Yong Li Xiao-Jun Ban Department of Control Science and Engineering Harbin Institute of Technology Harbin China

ISBN: (纸本)0780378652

A new method to fast build the rough data model (RDM) by means of fuzzy clustering is proposed. The scheme is contrived by Gustafson-Kessel (GK) algorithm, which is of many good properties and is demonstrated in the data-mining context. In this paper, first we investigate how to integrate the RDM's classification quality performance index into the GK clustering algorithm in the product space of input and output variables. Then we suggest the way to convert the fuzzy cluster models to rough data models. Hence, we work out an efficient algorithm that can obtain RDMs by just iteratively computing two necessary condition equations, which can minimize the objective function, and turn the multi-dimensional search process of Kowalczyk's method to one dimensional search strategy (in terms of the number of clusters). This technique reduces the searching time greatly. Moreover, by introducing the concept of the fuzzy degree of fulfillment (DoF) to a cluster rule, our approach seems to be much more flexible and more powerful ability in handling data contaminated by noise, with better generalization ability compared with the traditional rough set theory and the Kowalczyk's method. Finally, two examples illustrate the effectiveness of our approach.

关键词： Data models Clustering algorithms Pollution measurement Fuzzy control Iterative algorithms Set theory Machine learning Body sensor networks Data engineering Performance analysis

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