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American control Conference (ACC)

作者： K. Pfeiffer R. Isermann Laboratory for Control Engineering and Process Automation Institute of Automatic Control Technical University of Darmstadt DarMstadt Germany

The dynamical engine test stand described with a real engine and a drive-line simulation is a capable tool for exhaust emission analysis. To simulate the dynamics of load changes occurring in a driving vehicle, a model of the car body including clutch, manual gear-box, drive-line, differential and wheels has been developed and implemented on the test stand. Exhaust emission tests may be performed automatically with a proper driver simulation used in the dynamical engine test stands. Starting vehicle from standstill is a critical operation, especially for vehicles with manual gearbox, that occurs frequently in exhaust emission test cycles. Model-based control strategies for the vehicle startup have been developed. These strategies are presented and discussed.

关键词： Automatic control Automatic testing Engines Vehicle dynamics Wheels Torque Aerodynamics Vehicles Vehicle driving Roads

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A Comparison Between RBF Networks and Classical Methods for Identification of Nonlinear Dynamic Systems

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IFAC Proceedings Volumes 1995年第13期28卷 233-238页

作者： Oliver Nelles Rolf Isermann Darmstadt University of Technology Institute of Automatic Control Laboratory of Control Engineering and Process Automation Landgraf-Georg-Str. 4 64283 Darmstadt Germany

This paper compares radial basis function networks for identification of nonlinear dynamic systems with classical methods derived from the Volterra series. The performance of these different approaches as Hammerstein, Wiener and NDE models is analysed. Since the centres and variances of the Gaussian radial basis functions will be fixed before learning and only the weights are learned, a linear optimization problem arises. Therefore training the network and parameter estimation become comparable in calculational effort. It will be shown, that the classical methods can compete or even perform better than the neural network, if the assumptions for the structure are valid. However if in practical applications the structure is not known the radial basis function network performs much better than the classical methods.

关键词： identification nonlinear systems parameter estimation neural networks radial basis function networks

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Identification and Adaptive Nonlinear control of Drives with Friction

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IFAC Proceedings Volumes 1995年第14期28卷 305-310页

作者： A. Abou-El-Ela Th. Pfeufer R. Isermann Technical University of Darmstadt Institute of Automatic Control Laboratory for Control Engineering and Process Automation Landgraf Georg Str.4 D-64283 Darmstadt Germany

In this contribution several approaches to nonlinear adaptive control of mechanical drives are proposed taking into account determined nonlinear actuator characteristics such as friction, hysteresis and other static nonlinearities. Improved control performance in terms of dynamics, high positioning accuracy and robustness is achieved by combining linear position control with nonlinear feed-forward and adaptive friction compensation methods. Based on a precise model of the drive dynamics recursive identification techniques are applied to obtain reliable estimates of the time varying and position dependent process parameters, the nonlinear friction characteristic in particular. As examples the nonlinear friction characteristics of robotic joint drives and pneumatic drives are determined and it is shown how the control can be improved considerably by model based nonlinear control in the presence of time varying nonlinear characteristics and hysteresis effects. Experimental results illustrate the efficiency of the developed nonlinear control schemes.

关键词： Nonlinear adaptive control parameter identification friction compensation robotic joint drives pneumatic drives

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Fault Detection of Flowrate and Temperature control Loops using Estimated Parity Equations

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IFAC Proceedings Volumes 1995年第12期28卷 193-198页

作者： Thomas Höfling Rüdiger Deibert Oliver Hecker Technical University of Darmstadt Institute of Automatic Control Laboratory of Control Engineering and Process Automation Landgraf-Georg-Str. 4 D-64283 Darmstadt Phone: +49 6151 163114 Fax: +49 6151 293445

Many systems with nonlinear behaviour are difficult to model. Consequently model based approaches to fault detection can not be applied easily. Additional problems are introduced in closed loops by the controversity of controller design and fault detection. For a certain class of processes with mainly constant input signals a combination of parameter estimation techniques and the parity space approach allows on-line fault detection with small signal models. Only few knowledge of the process is required: An idea about the dynamic model order and the static nonlinear characteristic curve. Using the proposed method fault detection is performed for temperature control loops in a thermic plant.

关键词： Fault detection model based nonlinear parameter estimation parity space

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Nonlinear distance and cruise control for passenger cars

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IFAC Proceedings Volumes 1995年第1期28卷 209-214页

作者： St. Germann R. Isermann Technical University of Darmstadt Institute of Automatic Control Laboratory for Control Engineering and Process Automation Landgraf-Georg-Straße 4 D-64283 Darmstadt Germany Telephone : 0049-6151-162114 Telefax:0049-6151-293604

A methodology for designing an automated vehicle longitudinal velocity and distance controller is presented and applied to an automobile. Typically a vehicle is described by velocity depended dynamics and specific nonlinearities. Therefore the controller consists of a three layer structure. In the first layer a linearization of the nonlinearities is done in order to achieve a simplified structure for controller design purposes. With respect to changes in the typical vehicle parameters-mass and aerodynamical drag - an adaptive controller structure is used and these parameters are estimated by a recursive least squares algorithm. Based on classical controlling techniques a linear acceleration controller is developed in the middle layer. Up to now no mathematical equations are available describing the subjective demands of the driver and passengers during longitudinal motion. Therefore a fuzzy controller is applied in the upper layer. This controller based on the linguistic description of comfort demands. The complete structure is used in two different series fabricated vehicles and experimental results are shown for highway traffic as well as for stop-go traffic on highway congestions.

关键词： vehicle dynamics longitudinal motion intelligent vehicle highway systems fuzzy logic intelligent cruise control

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Nonlinear distance and cruise control for passenger cars

Nonlinear distance and cruise control for passenger cars

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American control Conference (ACC)

作者： S. Dermann R. Isermann Inst. of Autom. Control Tech. Univ. Darmstadt Germany Institute of Automatic Control Laboratory for Control Engineering and Process Automation Technical University of Darmstadt Darmstadt Germany

A methodology for designing an automated vehicle longitudinal velocity and distance controller is presented and applied to an automobile. nonlinearities. The controller consists of a three layer structure. In the first layer a linearization of the nonlinearities is done in order to achieve a simplified structure for controller design purposes. With respect to changes in the typical vehicle parameters-mass and aerodynamical drag-an adaptive controller structure is used and these parameters are estimated by a recursive least squares algorithm. Based on classical controlling techniques a linear acceleration controller is developed in the middle layer. A fuzzy controller is applied in the upper layer. This controller based on the linguistic description of comfort demands. Additionally a neural network is used in this layer instead of the fuzzy system. The complete structure is used in two different series fabricated vehicles and experimental results are shown for highway traffic and also for stop-go traffic on highway congestions. Additionally a neural network is trained by measurement data as a second approach to describe the comfort demands.

关键词： Automatic control Vehicles control nonlinearities Neural networks Road transportation Communication system traffic control Design methodology Velocity control Automobiles Programmable control

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Supervision of Lateral Vehicle Motion Using a Discrete Parity Space Approach

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IFAC Proceedings Volumes 1995年第1期28卷 75-79页

作者： Michael Würtenberger Rolf Isermann Technical University of Darmstadt Institute of Automatic Control Laboratory of Control Engineering and Process Automation Landgraf-Georg-Straße 4 D-64283 Darmstadt Phone: +49 6151 167407 Fax: +49 6151 293604

An approach for supervision of vehicle dynamics is presented which may be used for intelligent vehicle control and state monitoring. In particular, the task is to determine automatically an altered road surface for vehicles (may be due to weather conditions) with possibly lower adhesion between tires and road. Fault detection methods like the parity space approach can be used to detect changes in technical processes. These changes indicate different process behaviour in a new operation range. This may be of special importance when the new behaviour is more dangerous for the driver and the passengers of a car. In a further step, suitable classification algorithms were used to detect the actual driving state by processing the residual output.

关键词： Vehicle supervision parity space discrete-time active safety fault detection

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Adaptive Predictive control of Nonlinear Dynamic processes

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IFAC Proceedings Volumes 1995年第13期28卷 401-406页

作者： Robert Haber Ruth Bars Cologne Institute of Technology (Fachhochschule Köln) Department of Process Engineering Laboratory of Process Control D-50679 Köln Betzdorfer Str. 2 Germany. Department of Automation Technical University of Budapest H-1111 Budapest Goldmann Gy. tér 3 Hungary.

Predictive control algorithms determine a series of the control signal minimizing the deviation between the reference and the output signal in a given future horizon. The output of the plant to be controlled is predicted on the basis of a model, which can be linear or nonlinear, parametric or nonparametric. In adaptive control these process parameters are identified and the control signal is calculated taking the identified values into consideration. In the paper simulation results present some properties of adaptive predictive control. Robustness of the control algorithm is illustrated through control of a simple Wiener model . The relationship between the plant order and the prediction horizon is also mentioned. The promising results indicate that further systematic analysis is worthwhile.

关键词： nonlinear control predictive control adaptive control control algorithms parametric nonparametric models Volterra series

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Model based fault detection in milling by classification of estimated cutting parameters

Model based fault detection in milling by classification of ...

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IEEE International Conference on Systems, Man and Cybernetics

作者： H. Konrad R. Isermann N. Heintz Institute of Automatic Control Laboratory of Control Engineering and Process Automation Technical University of Darmstadt Darmstadt Germany Technische Universitat Darmstadt Fachbereich Biologie Darmstadt Hessen DE Inst. of Autom. Control Tech. Univ. of Darmstadt Germany

This paper describes a new method of fault detection in milling. The presented detection algorithm is based on the estimation of particular model parameters using measured cutting force signals. By classifying the res... 详细信息

关键词： Fault detection Milling Force measurement Teeth Parameter estimation Feeds Particle measurements Signal processing Signal generators Fault diagnosis

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ON THE APPLICABILITY OF MODEL-BASED FAULT-DETECTION FOR TECHNICAL processES

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control engineering PRACTICE 1994年第3期2卷 439-450页

作者： ISERMANN, R Institute of Automatic Control Laboratory for Control Engineering and Process Automation Technical University of Darmstadt Landgraf-Georg-Straβe 4 D-64283 Darmstadt Germany

Beginning with classical supervision a summary is given of the main principles of model-based fault detection methods. Their basic assumptions, results from simulation and experiments allow a discussion of the features of the methods with regard to their applicability. The importance of realistic fault modeling is outlined. Finally the role of model-based fault detection as one information source for fault diagnosis is discussed. Several methods of fault detection have to be integrated to support a powerful diagnosis.

关键词： FAULT DETECTION SUPERVISION MONITORING PARAMETER ESTIMATION STATE ESTIMATION PARITY EQUATIONS TECHNICAL processES ACTUATORS SENSORS FAULT DIAGNOSIS

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