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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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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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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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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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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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SELFTUNING OF CLASSICAL controlLERS WITH FUZZY-LOGIC

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MATHEMATICS AND COMPUTERS IN SIMULATION 1994年第2-3期37卷 101-110页

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

Selftuning of classical PI-controllers for processes without known mathematical models is achieved by applying heuristic fuzzy rules. Step changes of the reference input are used to assess control performance in terms of overshoot, rise time and settling time of the step response. Similar to the strategy of an experienced plant operator, a fuzzy logic ''supervision and tuning module'' can conclude from these features, which changes of the controller parameters will improve control behaviour. The concept was tested in simulation series with Matlab/Simulink. Results show the benefits of the proposed fuzzy tuning module applied to 8 different simulated test plants. Experiments with speed-regulation of a DC-servomotor indicate that the concept is suitable for processes with noisy signals as well.

关键词： Self tuning control systems

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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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Model based supervision of lateral vehicle dynamics

Model based supervision of lateral vehicle dynamics

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American control Conference (ACC)

作者： M. Wurtenberger R. Isermann Institute of Automatic Control Laboratory of Control Engineering and Process Automation Technical University of Darmstadt Darmstadt Germany

An approach for supervision of vehicle dynamics is presented which may be used for intelligent vehicle control and state monitoring. In particular, an on-board process parameter estimation was implemented which allows one to compute the physical coefficients of lateral vehicle models and their changes during operation. In addition, tire- and velocity-dependent look-up tables in presently used vehicle models were replaced by feedforward neural networks. In the phase of driving state monitoring, a set of these hybrid models-each of them trained for a special driving situation-predict the vehicle motion as a result of the actual steering angle and velocity. In a further step, suitable classification algorithms were used to detect the actual driving state by processing the residual output.

关键词： Vehicle dynamics Vehicle driving Parameter estimation Monitoring Road vehicles automatic control Least squares approximation Character generation Acceleration Laboratories

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Modelling and control of longitudinal vehicle motion

Modelling and control of longitudinal vehicle motion

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American control Conference (ACC)

作者： S. Germann R. Isermann Laboratory for Control Engineering and Process Automation Institute of Automatic Control Technical University of Darmstadt Darmstadt Germany

Discusses model based methods for controlling vehicle dynamics. A nonlinear model describing the longitudinal motion of a vehicle is presented. This model consists of a braking system, a powertrain and mass-damper system with damping from aerodynamical drag and rolling resistance. According to the most essential time constants, parameter estimation is used to determine the mass and the aerodynamical drag of the vehicle. As an example for controller design, a combination of fuzzy logic and a classical feedback linearization is presented. Furthermore, some examples of a velocity controller are shown using the described controlling techniques.

关键词： Motion control Power system modeling Drag Velocity control Vehicle dynamics Mechanical power transmission Damping Parameter estimation Linear feedback control systems Fuzzy logic

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Estimation of parity equations in nonlinear systems

Estimation of parity equations in nonlinear systems

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IEEE Conference on control Technology and Applications (CCTA)

作者： Hofling Deibert Laboratory of Control Engineering and Process Automation Institute of Automatic Control Technical University of Darmstadt Darmstadt Germany

Many processes with nonlinear behaviour are difficult to model. Consequently model based approaches to fault detection can not be applied. For a certain class of these processes with mainly constant input signals a combination of parameter estimation techniques and the parity space approach allows online 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 at a flowrate control with a pneumatic driven valve.< >

关键词： Nonlinear systems Failure analysis Parameter estimation

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