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Information processing for mechatronic systems

ROBOTICS AND AUTONOMOUS SYSTEMS 1996年第2期19卷 117-134页

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

The integration of mechanical systems and microelectronics opens many new possibilities for process design and automatic functions. After discussing the mutual interrelations between mechanical and electronic design the different ways of integration within mechatronic systems and the resulting properties are described. The information processing can be organized in multilevels, ranging from low-level control, through supervision to general process management. In connection with knowledge bases and inference mechanisms intelligent control systems result. The design of control systems for mechanical systems is described, from modeling, identification to adaptive control for nonlinear systems. This is followed by solving supervision tasks with fault diagnosis. Then design tools for mechatronic systems are considered and examples of applications are given, like intelligent control of an electromechanical throttle actuator and force and torque reconstruction for a robot.

关键词： mechatronic systems intelligent control nonlinear control adaptive control supervision fault diagnosis hardware-in-the-loop simulation intelligent automobile actuators torque reconstruction robot control

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Fault detection in milling, using parameter estimation and classification methods

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control engineering PRACTICE 1996年第11期4卷 1573-1578页

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

In this paper a new method of fault detection in milling is reported. Based on measured cutting forces, model parameters are estimated for each insert of the milling cutter. Using a classifier, the patterns of these estimated parameters are processed further, and the state of the milling process is determined. The method was first tested with simulated data, and then verified with measurements on a machining center.

关键词： machine tools cutting failure detection neural networks

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Fault detection based on adaptive parity equations and single-parameter tracking

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control engineering PRACTICE 1996年第10期4卷 1361-1369页

作者： Hofling, T Isermann, R Institute of Automatic Control Laboratory of Control Engineering and Process Automation Darmstadt University of Technology Landgraf-Georg-Str. 4 D-64283 Darmstadt Germany

Faults which appear in technical processes can often be described as additive or multiplicative faults with respect to the process model. To perform fast detection of these faults, continuous-time parity equations are used. Parameter deviations are estimated directly from residuals, providing information about their size. The combined method enables one to distinguish between additive and parametric faults. In case of time-variant processes with slow parameter changes, the coefficients of the parity equations can also be adapted with respect to the tracked parameters. The problem of persistent process excitation for estimation is by-passed. The fault-detection scheme is demonstrated on a permanently excited d.c. motor on a laboratory rig. Its properties, and the experimental results, are discussed.

关键词： fault detection adaptive parameter estimation parity space continuous-time dcmotors

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Local linear model trees for on-line identification of time-variant nonlinear dynamic systems

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1st International Conference on Artificial Neural Networks, ICANN 1996

作者： Nelles, Oliver Technical University of Darmstadt Institute of Automatic Control Laboratory of Control Engineering and Process Automation Landgraf-Georg-Str. 4 DarmstadtD-64283 Germany

ISBN: (纸本)3540615105

This paper discusses on-line identification of time-variant nonlinear dynamic systems. A neural network (LOLIMOT, [1]) based on local linear models weighted by basis functions and constructed by a tree algorithm is introduced. Training of this network can be divided into a structure and a parameter optimization part. Since the network is linear in its parameters a recursive least-squares algorithm can be applied for on-line identification. Other advantages of the proposed local approach are robustness and high training and generalisation speed. The simplest recursive version of the algorithm requires only slightly more computations than a recursive linear model identification. The locality of LOLIMOT enables on-line learning in one operating region without forgetting in the others. A drawback of this approach is that systems with large structural changes over time cannot be properly identified, since the model structure is fixed. © Springer-Verlag Berlin Heidelberg 1996.

关键词： Forestry

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Identification of a high efficiency boiler based on neural networks with locally distributed dynamics

Identification of a high efficiency boiler based on neural n...

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IEEE International Symposium on Intelligent control (ISIC)

作者： J. Ohl M. Ayoubi M. Kurth Laboratory of Control Engineering & Process Automation Institute of Automatic Control Technical University of Darmstadt Darmstadt Germany

This paper considers the application of neural network with distributed dynamics to the identification of nonlinear systems. The main intention is to provide a simulation tool to the development engineer. The identification of the thermal plant is accomplished without any a priori knowledge about the nonlinear structure or the dynamics of the plant. Identification results of two different neural nets are shown and compared. The application area is boilers for building energy management systems.

关键词： Boilers Neural networks Aerodynamics Nonlinear dynamical systems Autoregressive processes Temperature control Heating Neurons Optimal control control systems

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Fuzzy rule extraction by a genetic algorithm and constrained nonlinear optimization of membership functions

Fuzzy rule extraction by a genetic algorithm and constrained...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： O. Nelles M. Fischer B. Muller Institute of Automatic Control Laboratory of Control Engineering and Process Automation Technical University of Darmstadt Darmstadt Germany

We propose a new method for fuzzy rule extraction from data by a genetic algorithm and a fine tuning of the extracted membership functions by a constrained nonlinear optimization. This approach is able to select the most significant rules out of a set of all possible ones, that is it learns the rule structure by itself. The genetic algorithm does not limit the kind of operator and the number and form of the membership functions for the inputs. However, in order to utilize linear optimization techniques, singletons and center of gravity defuzzification are used on the output side. Since each rule premise may include a conjunction of a variable number of inputs (between one and the input dimension), the "curse of dimensionality" can be overcome, that is the number of rules does not increase exponentially with the input dimension. This feature makes the proposed algorithm especially attractive for interpretation of high dimensional nonlinear mappings that are hard to visualize. The strategy followed by the nonlinear optimization of the fuzzy input membership functions focuses on a good interpretability rather than on best approximation performance. This will be demonstrated on a real world data example.

关键词： Genetic algorithms Constraint optimization Fuzzy systems Fuzzy control Data mining Convergence Neural networks Backpropagation Gaussian processes automatic control

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Mechatronic Systems - with Applications for Cars -

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IFAC Proceedings Volumes 1996年第1期29卷 7732-7737页

作者： Rolf Isermann Institute of Automatic Control Laboratory of Control Engineering and Process Automation Technical University of Darmstadt Landgraf-Georg-Str 4 D-64283 Darmstadt Germany

The integration of mechanical processes and microelectronics towards mechatronic systems opens new possibilities as well for the design of mechanical components as for automatic functions. The contribution discusses first the involved mechanical components and machines and the ways of integration. Then the different automation functions are described in the frame of intelligent control systems which contain multilevel control functions, a knowledge base, and inference mechanisms. Multilevel feedback control for mechanical systems comprises lower level and higher level control, including e.g. nonlinear adaptive control and fuzzy control. The inclusion of model based supervision and fault diagnosis is a further development step. Two examples of mechatronic systems for cars are shown, like an adaptive suspension system and selftuning damping of drive chain oscillations.

关键词： mechatronic systems intelligent control nonlinear control adaptive control supervision fault diagnosis adaptive suspension selftuning damping of drive chain oscillations

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Integrated Model Based Fault Detection and Diagnosis with Application To Electromechnical Drives

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IFAC Proceedings Volumes 1996年第1期29卷 6406-6411页

作者： R. Isermann T. Pfeufer Institute of Automatic Control Laboratory of Control Engineering and Process Automation Technical University of Darmstadt Landgraf-Georg-Str 4 D-64283 Darmstadt Germany

A general procedure for model based fault detection and diagnosis is first described. It comprises the steps of a knowledge based approach by merging analytical and heuristic knowledge. Model based fault detection methods are summarized together with underlying fault models and appropriate combinations are proposed. Then fault diagnosis based on analytical and heuristic symptoms by using methods of approximate reasoning with fuzzy-logic is briefly described. Finally the practical application for an automotive electro-mechanical actuator is shown.

关键词： Fault detection fault diagnosis parameter estimation state estimation observer parity equations approximate reasoning fuzzy inference automotive elcctromcchanic actuator

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Adaptive Parity Equations and Advanced Parameter Estimation for Fault Detection and Diagnosis

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IFAC Proceedings Volumes 1996年第1期29卷 6377-6382页

作者： Thomas Hötling Rolf Isermann Institute of Automatic Control Laboratory of Control Engineering and Process Automation Technical University of Darmstadt Landgraf-Georg-Str. 4 D-64283 Darmstadt Germany

Faults which appear in technical processes can often be described as additive or multiplicative faults with respect to the process model. To perform fast detection of these faults continuous-time parity equations are used. Parameter deviations are estimated directly from residuals providing information about their size. The combined method enables to distinguish between additive and parametric faults. In case of time variant processes with slow parameter changes the coefficients of the parity equations can also be adapted with respect to the tracked parameters. The problem of persistent process excitation for estimation is by-passed. The fault detection scheme is demonstrated at a permanently excited *** on a laboratory rig. Its properties and the experimental results are discussed.

关键词： Fault detection parameter estimation parity space continuous-time d.c.motor

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Intelligent Electromechanical Servosystem

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IFAC Proceedings Volumes 1996年第1期29卷 7272-7277页

作者： Thomas Pfeufer Rolf Isermann Institute of Automatic Control Laboratory of Control Engineering and Process Automation Technical University of Darmstadt Landgraf-Georg-Str. 4 D-64283 Darmstadt Germany

Servo systems play an important role in many automated processes. In order to fulfil the hard demands on reliability and fast and precise operation, intelligent concepts for the control, supervision and (reconfiguration are necessary. In this paper, an approach is presented which integrates different levels of signal processing in an electromechanical servo system. The digital controller and the model-based fault detection scheme are designed taking into account model-uncertainty and the time variant process behaviour, which is caused by temperature influences. After a brief description of the theoretical basis an experimental application shows results for an automobile servo system which is driven by a d.c. motor.

关键词： Intelligent control sliding mode control supervision model-based fault detection parameter estimation parity equations reconfiguration

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