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Fault Detection and Diagnosis of a Linear Hydraulic Servo Axis

IFAC Proceedings Volumes 2004年第6期37卷 861-866页

作者： Marco Muenchhof Rolf Isermann Institute of Automatic Control Laboratory of Control Engineering and Process Automation Darmstadt University of Technology Landgraf-GeorgrStr. 4 D-64283 Darmstadt Germany Phone: + 49 6151 16-7406 FAX: +49 6151 16-74 21

process model based methods to detect faults in a hydraulic linear servo axis by measurement of up to five variables are presented. The faults that are detected include gas enclosures in the hydraulic fluid, such as air, vapour and foam. The control edges and the valve spool are also monitored in order to detect faults such as erosion of the control edges and grooving of the valve spool. Furthermore, the leakage flow between the cylinder chambers and to the surroundings are monitored, which allows to detect damages of the sealing between the cylinder chambers and between the cylinder and the pushrod. The external mechanical load and the valve spool dynamics are also included in the fault detection and diagnosis approach.

关键词： Fault Detection Fault Diagnosis Hydraulic Actuator Parameter Estimation

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Temperature prediction control based on least squares support vector machines

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control Theory and Technology 2004年第4期2卷 365-370页

作者： Bin LIU, Hongye SU, Weihua HUANG, Jian CHU (National laboratory of Industrial control Technology, institute of Advanced process control, Zhejiang University, Yuquan Campus,Hangzhou Zhejiang 310027,China Department of automation, College of Information Science and engineering, Wuhan University of Saence and Technology, Wuhan Hubei 430081, China) National Laboratory of Industrial Control Technology Institute of Advanced Process Control Zhejiang University Yuquan Campus Hangzhou Zhejiang China Department of Automation College of Information Science and Engineering Wuhan University of Science and Technology Wuhan Hubei China

A prediction control algorithm is presented based on least squares support vector machines (LS-SVM) model for a class of complex systems with strong nonlinearity. The nonlinear off-line model of the controlled plant is built by LS-SVM with radial basis function (RBF) kernel. In the process of system running, the off-line model is linearized at each sampling instant, and the generalized prediction control (GPC) algorithm is employed to implement the prediction control for the controlled *** obtained algorithm is applied to a boiler temperature control system with complicated nonlinearity and large time *** results of the experiment verify the effectiveness and merit of the algorithm.

关键词： Predictive control Least squares support vector machines RBF kernel function Generalized prediction control

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Performance assessment of model predictive control in industrial distillation column

Performance assessment of model predictive control in indust...

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World Congress on Intelligent control and automation (WCICA)

作者： Maying Yang Xiaoming Jin Fei Chen Automation Department Information Engineering College Zhejiang University of Technology Hangzhou China National Key Laboratory of Industrial Control Technology Institute of Advanced Process Control University of Zhejiang Hangzhou China

ISBN: (纸本)0780382730

A synthetical method of multivariable control system performance assessment is proposed in this paper, which uses multivariable minimum variance control (MVC) benchmark to determine the stochastic performance, and normalized multivariate impulse response (NMIR) curve as an alternative measure of performance to test the dynamic performance, and with the help of auto-correlation function (ACF) and cross-correlation function (CCF) to analyse if there are oscillations exist. The method is applied to assess the performance of multivariable predictive control system of industrial distillation column.

关键词： Predictive models Predictive control Industrial control Distillation equipment Electrical equipment industry control systems System performance Benchmark testing Stochastic systems Impulse testing

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Optimizing the structure of hierarchical mixture of experts using genetic algorithms

Optimizing the structure of hierarchical mixture of experts ...

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International IEEE Conference on Intelligent Systems, IS

作者： D.A. Karras C.E. Vlitakis Y.S. Boutalis B.G. Mertzios Chalkis Institute of Technology Department Automation and Hellenic Open University Athens Greece Department Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece Department of Automation Thessdoniki Institute of Technology Laboratory of Automatic Control Systems Thessaloniki Hellas and Democritus University Xanthi Greece

This study is an effort to give a practical solution in the problem of optimizing the structure of the hierarchical mixture of experts model, which is a natural extension of the associative Gaussian mixture of experts system. We present two novel methods for optimizing such structures using genetic algorithms. Special concern is taken for reducing the computational time so as to efficiently allow the structure to "grow" while it evolves with the genetic algorithm. The main contribution of the paper lies on the efficient, topologically oriented, representations of such architectures so as to be optimized through involving genetic algorithms.

关键词： Genetic algorithms Biological cells Optimization methods Neural networks Classification tree analysis automation Decision trees Expert systems Computer architecture Supervised learning

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Model-based fault detection and diagnosis for hydraulic braking systems 5

Model-based fault detection and diagnosis for hydraulic brak...

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5th IFAC Symposium on Fault Detection, Supervision and Safety of Technical processes, Safeprocess 2003

作者： Straky, Harald Muenchhof, Marco Isermann, Rolf Institute of Automatic Control Laboratory of Control Engineering and Process Automation Darmstadt University of Technology Landgraf-Georg-Str. 4 DarmstadtD-64283 Germany

This paper describes fault detection and diagnosis techniques for a hydraulic passenger car braking system. First, a model of the hydraulic braking system is derived in state space representation. This model is subsequentlyemployed for fault detection and diagnosis. Fault detection is based on the calculation of the loss volume, i.e. the amount of brake fluid consumed due to the presence of a fault. The type of fault is determined by means of a correlation analysis approach. Furthermore, the location of the fault can also be determined. This is accomplished by analyzing the master brake cylinder pressure signals. The paper also presents numerical results of data recorded at a braking system testbed which illustrates the feasibility of the proposed approaches. © 2003 International Federation of automatic control.

关键词： Fault detection

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Model-based supervision of a vacuum brake booster 5

Model-based supervision of a vacuum brake booster

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5th IFAC Symposium on Fault Detection, Supervision and Safety of Technical processes, Safeprocess 2003

作者： Muenchhof, Marco Straky, Harald Isermann, Rolf Institute of Automatic Control Laboratory of Control Engineering and Process Automation Darmstadt University of Technology Landgraf-Gerog-Str. 4 DarmstadtD-64283 Germany

This paper presents the design of a model-based supervision system for the vacuum brake booster of current hydraulic passenger car braking systems. A model is derived, which allows to calculate the pressure in the vacuum chamber and the working chamber of the vacuum brake booster. Based on this model, a real-time supervision system has been implemented. The fidelity of the model has been evaluated by testing the model against experimental data from a braking system test bed. The functioning of the model-based supervision system has also been probed with measurements taken at the aforementioned testbed. © 2003 International Federation of automatic control.

关键词： Brakes

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Model-based supervision of a vacuum brake booster

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IFAC Proceedings Volumes 2003年第5期36卷 429-434页

作者： Marco Muenchhof Harald Straky Rolf Isermann Institute of Automatic Control Laboratory of Control Engineering and Process Automation Darmstadt University of Technology Landgraf-Gerog-Str. 4 D-64283 Darmstadt Germany Phone: +496151 16-7406 FAX: +496151 16-7421

关键词： Brakes Pneumatic Fault Detection

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Near minimax robust control of flexible structures

Near minimax robust control of flexible structures

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American control Conference (ACC)

作者： M. Muenchhof T. Singh Department of Mechanical and Aerospace Engineering SUNY at Buffalo Buffalo NY USA Institute of Automatic Control Laboratory of Control Systems and Process Automation Darmstadt University of Technology Darmstadt Germany

This paper presents an approach to calculate prefilters that are insensitive to parameter deviations. The cost function chosen for this approach is the magnitude of the time-delay filter transfer function. By approximating the cost function with a polynomial, the effort of calculating minimax robust profiles can be reduced. The resulting control profiles yield a performance similar to the minimax robust controller. This is verified by the numerical results included in this paper.

关键词： Minimax techniques Robust control Flexible structures Filters Uncertainty Frequency Cost function Vibrations control systems Delay effects

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Model-based fault detection and diagnosis for hydraulic braking systems

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IFAC Proceedings Volumes 2003年第5期36卷 307-312页

作者： Harald Straky Marco Muenchhof Rolf Isermann Institute of Automatic Control Laboratory of Control Engineering and Process Automation Darmstadt University of Technology Landgraf-Georg-Str. 4 D-64283 Darmstadt Germany Phone: +49 6151 16-7406 FAX: +49 6151 16-7421

关键词： Brakes Hydraulic Electro-Hydraulic Fault Detection Fault Diagnosis

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Data fusion for precise dead-reckoning of passenger cars 15th

Data fusion for precise dead-reckoning of passenger cars

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15th World Congress of the International Federation of automatic control, 2002

作者： Kochem, M. Wagner, N. Hamann, C.-D. Isermann, R. University of Technology Darmstadt Institute of Automatic Control Laboratory for Control Engineering and Process Automation Germany Adam Opel AG Rüsselsheim Germany

ISBN: (纸本)9783902661746

This paper investigates the possibility of computing the actual position of a passenger car based on different independent internal signals available in a production car. A new front wheel based dead reckoning approach is compared to a model based approach as well as to an Extended Kalman Filter. Depending on the method the input signals are the wheel revolutions of the front wheels, the steering angle and the yaw rate. Experimental results show the quality of all three algorithms compared to position data obtained by a DGPS system and also to the well known rear wheel based dead reckoning approach. Copyright © 2002 IFAC.

关键词： Sensor data fusion

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