Continuous process Models are widely used in system identification and fault detection. However, dynamic models require the derivatives of the process' input and output signals. Often they cannot be accessed by me...
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Continuous process Models are widely used in system identification and fault detection. However, dynamic models require the derivatives of the process' input and output signals. Often they cannot be accessed by measurements. Thus they have to be provided by digital filters. Commonly state variable filters are used for this purpose. But this approach has a couple of drawbacks caused by the recursive structure of the filter. In this paper a consistent approach for the design of FIR differentiators by means of modulating functions is proposed. Finally the application of these filters for fault detection using a microcontroller is presented.
In modern vehicles, mechatronic systems are increasingly used. To improve reliability, safety and economy, an early recognition of small or drifting faults is becoming increasingly important. After a short introductio...
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In modern vehicles, mechatronic systems are increasingly used. To improve reliability, safety and economy, an early recognition of small or drifting faults is becoming increasingly important. After a short introduction to methods of model based fault detection and diagnosis, application examples for fault detection of automotive vehicle suspension and hydraulic brake systems are given.
This paper describes a mechanical system with a bouncing ball, it’s parameters, mathematical model and control design process using a programmable logic controller. This system is very good object for the demonstrati...
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This paper describes a mechanical system with a bouncing ball, it’s parameters, mathematical model and control design process using a programmable logic controller. This system is very good object for the demonstration of discrete event control and illustration of the possibilities and constraints of programmable logic controllers.
This paper proposes a genetic-based algorithm for surface reconstruction of three-dimension (3-D) objects from a group of contours representing its section plane lines. The algorithm can optimize the triangulation of ...
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This paper proposes a genetic-based algorithm for surface reconstruction of three-dimension (3-D) objects from a group of contours representing its section plane lines. The algorithm can optimize the triangulation of the surface of 3-D objects with a multi-objective optimization function to meet the needs of a wide range of applications. Further, a new crossover operator for triangulation and a new 3-D quadrilateral mutation operator are also introduced.
This paper deals with the comparison of two design methodologies for nonlinear fuzzy model based controllers. A straightforward approach to design nonlinear controllers is to linearize the nonlinear model at the curre...
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作者:
Rolf IsermannInstitute 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 and microelectronic components during the design and operation requires systematic methods and software tools for theoretical modeling, experimental identification and simulation. Therefo...
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The integration of mechanical and microelectronic components during the design and operation requires systematic methods and software tools for theoretical modeling, experimental identification and simulation. Therefore, the contribution summarizes the state-of-the-art in these areas based on the practical experience with several mechatronic systems and tries to show open problems. It is typical for mechatronic systems that they are composed of components from different physical domains, such as electrical mechanical, fluidic, thermal and thermodynamic processes. One of the key issues, therefore, is to find a unified way especially for theoretical modeling, but also for identification and simulation of these heterogeneous systems. A further task is to develop software tools for modeling, identification and simulation and to make them interconnectable. For theoretical modeling a unified procedure can be given for lumped parameter processes with energy and material flows. A multi port representation can be stated for processes with energy flows for electrical, mechanical and fluidic processes. However, problems with a unified representation arise for thermal and thermodynamic processes. The development from multi ports to block diagrams and bond graphs is shortly described. Present developments are characterized by object-oriented modeling with introduction of causalities at a late state. Identification methods for mechatronic systems are required frequently e.g. for theoretical model verification or on-line estimation of unknown and time varying parameters or identification of nonlinear static characteristics and dynamics. The properties of suitable methods are described, including parameter estimation and dynamical neural networks for nonlinear processes. Then, various kinds of simulation methods for mechanical systems are described, especially with regard to the time behaviour. For several applications real-time simulation is required. Examples are process simulati
A fault detection and isolation scheme for a brushless DC motor driving a mechanical actuation system is presented. First, a detailed mathematical model of the drive is derived. The residual generator is based on pari...
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A fault detection and isolation scheme for a brushless DC motor driving a mechanical actuation system is presented. First, a detailed mathematical model of the drive is derived. The residual generator is based on parity relations while the fault isolation part is implemented by means of the transferable belief model. The problem of distinguishing between faults with the same fault signatures is addressed. It is shown that additional improvements in terms of resolution can be achieved by employing parameter estimation. The proposed FDI scheme is tested on the actual drive under various faults. The achieved performance features the highest resolution, diagnostic stability and accuracy.
Advanced engine controlsystems require accurate process models. This paper presents neural net models for combustion engines. After briefly introducing a special local linear RBF network (LOLIMOT) two applications ar...
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Advanced engine controlsystems require accurate process models. This paper presents neural net models for combustion engines. After briefly introducing a special local linear RBF network (LOLIMOT) two applications are described. Different methods for developing exhaust gas models are compared and a dynamic model for the charging pressure dynamics of a turbocharger is presented. Finally, an exhaust vs. consumption optimization is presented for optimizing the injection angle dependent on given weighting factors for specific emissions, the fuel consumtion and the current driving situation.
A novel approach for the supervision of fuzzy model on-line adaptation is proposed. A nonlinear predictive controller is designed based on a Takagi-Sugeno fuzzy model. By adapting the fuzzy model on-line, high control...
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A novel approach for the supervision of fuzzy model on-line adaptation is proposed. A nonlinear predictive controller is designed based on a Takagi-Sugeno fuzzy model. By adapting the fuzzy model on-line, high control performance can be achieved even with time-variant process behavior and changing unmodeled disturbances. A local weighted recursive least-squares algorithm exploits the local linearity of Takagi-Sugeno fuzzy models. In order to cope with problems resulting from insufficient excitation a supervisory level is introduced. It comprises a variable forgetting factor and an additional adaptation model which makes the on-line adaptation robust and reliable. The effectiveness and real-world applicability of the proposed approach are demonstrated by application to temperature control of an industrial-scale heat exchanger.
A real time fault detection approach for a brushless DC motor driving a mechanical actuation system is presented. The brushless DC motor is controlled by a PWM inverter using rectangular current excitation. After an i...
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A real time fault detection approach for a brushless DC motor driving a mechanical actuation system is presented. The brushless DC motor is controlled by a PWM inverter using rectangular current excitation. After an introduction into fault detection with parameter estimation and parity equations, a mathematical model for the actuator with special emphasis on the motor itself is derived. The application of the estimation algorithm to detect electrical and mechanical parameter changes in the motor is described. In addition parity equations are used to detect sensor offsets. The fault detection scheme is implemented on a digital signal processor controlling the actuator. Finally experimental results are given.
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