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Trends in the application of model-based fault detection and diagnosis of technical processes

control engineering PRACTICE 1997年第5期5卷 709-719页

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

After a short overview of the historical development of model-based fault detection, some proposals for the terminology in the field of supervision, fault detection and diagnosis are stated, based on the work within the IFAC SAFEprocess Technical Committee. Some basic fault-detection and diagnosis methods are briefly considered. Then, an evaluation of publications during the last 5 years shows some trends in the application of model-based fault-detection and diagnosis methods. Copyright (C) 1997 Elsevier Science Ltd.

关键词： fault detection fault diagnosis supervision actuator faults sensor faults process faults state observer parity space parameter estimation classification diagnostic reasoning

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Mechatronic systems for machines and automobiles

Mechatronic systems for machines and automobiles

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

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

Summary form only given. The synergetic integration of mechanical processes, microelectronics and information processing opens new possibilities for process design as well as for automatic control. The solution of tasks within mechatronic systems is performed on the process side and the digital-electronic side. As the interrelations during the design play an important role, engineering must be simultaneous from the very beginning. Mechatronic systems are developed for mechanical elements, machines, vehicles and precision mechanic devices. The integration of mechatronic systems can be performed by the components (hardware-integration) and by information processing (software-integration). The information processing consists of low-level and high-level feedback control, supervision and diagnosis and general process management. Special signal processing, model based and adaptive methods are applied. With the aid of a knowledge base and inference mechanisms mechatronic systems with increasing intelligence will be developed. The main goals are to increase systems performance, reliability and economy, and production costs. Some examples for the development of mechatronic systems are shown, e.g. active damping of oscillations of mechanical drives, hydraulic pipes and vehicle suspensions, control of machine tools with force reconstruction, smart actuators and supervision and fault diagnosis for automobiles.

关键词： Mechatronics Automobiles Information processing Intelligent actuators Microelectronics process design Automatic control Automotive engineering Design engineering Vehicles

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Mechatronic systems-a challenge for control engineering

Mechatronic systems-a challenge for control engineering

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American control Conference (ACC)

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

The synergetic integration of mechanical processes, micro-electronics and information processing opens new possibilities as well to the design of processes as for its automatic control. The solution of tasks within mechatronic systems is performed on the process side and the digital-electronic side. As the interrelations during the design play an import role simultaneous engineering from the very beginning has to take place. Mechatronic systems are developed for mechanical elements, machines, vehicles and precision mechanic devices. The integration of mechatronic systems can be performed by the components (hardware-integration) and by information processing (software-integration). The information processing consists of low-level and high-level feedback control, supervision and diagnosis and general process management. Special signal processing, model based and adaptive methods are applied. With the aid of a knowledge base and inference mechanisms, mechatronic systems with increasing intelligence will be developed. The main goals are to increase systems performance, reliability and economy, and production costs. Some examples for the development of mechatronic systems are given, such as smart actuators, adaptive suspensions, electrical brakes, adaptive cruising control of cars, and hardware-in-the-loop simulation of combustion engines. Experimental results are shown, and the improvements by the mechatronic approaches are pointed out.

关键词： Mechatronics control engineering Information processing Intelligent actuators Programmable control Adaptive control process design Automatic control Automotive engineering Design engineering

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Nonlinear system identification and predictive control of a heat exchanger based on local linear fuzzy models

Nonlinear system identification and predictive control of a ...

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American control Conference (ACC)

作者： O. Hecker O. Nelles O. Moseler Institute of Automatic Control Laboratory of Control Engineering and Process Automation Technical University of Darmstadt Darmstadt Germany

This paper deals with identification and control of a highly nonlinear real world application, The performance and applicability of the proposed methods are demonstrated for an industrial heat exchanger. The main difficulties for identification and control of this plant arise from the strongly nonlinear center and the widely varying dead times introduced by different water flows. The identification of this three input one output process is based on the local linear model trees (LOLIMOT) algorithm. It combines efficient local linear least-squares techniques for parameter estimation of the local linear models with a tree construction algorithm that determines the structure of their validity functions. Furthermore, a subset selection technique based on the orthogonal least-squares (OLS) algorithm is applied for an automatic determination of the model orders and dead times. This strategy allows to design a wide range high accuracy nonlinear dynamic model of the heat exchanger on which the predictive control approach is based on. The nonlinear predictive control takes the speed and limit constraints of the actuator into account and leads to a high performance control over all ranges of operation.

关键词： Nonlinear systems Predictive control Temperature control Water heating Circuits Nonlinear dynamical systems Heat engines Predictive models Automatic control Valves

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Representation of 3-D mappings for automotive control applications using neural networks and fuzzy logic

Representation of 3-D mappings for automotive control applic...

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IEEE Conference on control Technology and Applications (CCTA)

作者： H. Holzmann C. Halfmann R. Isermann Institute of Automatic Control Laboratory for Control Engineering and Process Automation Darmstadt University of Technology Darmstadt Germany

Providing a simple and effective way to describe the nonlinear input-output behaviour of a system, three-dimensional mappings (3-D maps) have gained a lot of importance in modern automotive technology. Applications cover a wide range from real-time control systems up to the area of vehicle simulation. Replacing the conventional look-up-tables by neural network or fuzzy logic representations offers an easy possibility to generate 3-D maps by measured data and to adapt them online using measured signals. This paper describes the modelling of engine characteristics for vehicle control and simulation purposes by multilayer perceptron and radial-basis function networks. In addition to that, a neuro-fuzzy approach is discussed as well.

关键词： Automotive engineering Neural networks Fuzzy control Fuzzy neural networks Engines Vehicles Interpolation Automatic control control systems Fuzzy logic

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Integrated control, diagnosis and reconfiguration of a heat exchanger

Integrated control, diagnosis and reconfiguration of a heat ...

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American control Conference (ACC)

作者： P. Balle M. Fischer D. Fussel R. Isermann Institute of Automatic Control Laboratory of Control Engineering and Process Automation Darmstadt University of Technology Darmstadt Germany

Heat exchangers play an important role in chemical and process industries. In order to improve reliability and control performance, intelligent concepts for control, supervision and reconfiguration are necessary. In this paper, an approach is presented which integrates model-based adaptive control and reconfiguration based on fault detection/diagnosis applied to a heat exchanger plant. The adaptive controller and the fault detection scheme are based on a fuzzy model of the process (Takagi-Sugeno type) and the fault diagnosis is performed using a self-organizing fuzzy structure.

关键词： Centralized control Chemical industry Adaptive control Fault detection Fault diagnosis Fuzzy control Chemical processes Intelligent control Programmable control Takagi-Sugeno model

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Identification of Fuzzy Models for Predictive control of Nonlinear Time-Variant processes

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IFAC Proceedings Volumes 1997年第25期30卷 403-408页

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

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Comparison Between the Dynamic Multi-Layered Perception and the Generalised Hammerstein Model for Experimental Identification of the Loading process in Diesel Engines

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IFAC Proceedings Volumes 1997年第25期30卷 511-517页

作者： Mihiar Ayoubi Darmstadt University of Technology Lab. of Control Engineering and Process Automation Landgraf-Georg Str. 4 64283 Darmstadt Germany

A multi-layered feed forward neural network with locally distributed dynamics is described and applied to the nonlinear identification of the loading process within a diesel engine. The modelling capability of the dynamic neural network is compared with the classical Hammerstein model which possesses the same physical structure as the real-world process at hand. The performance comparison is carried out with respect to the model development effort, static approximation and dynamic prediction capability of both approaches.

关键词： Discrete-time dynamic neural networks globally feed forward locally recurrent networks nonlinear identification Hammerstein model loading process diesel engine

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Identification of nonlinear processes and model based fault isolation using local linear models

Identification of nonlinear processes and model based fault ...

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American control Conference (ACC)

作者： P. Balle D. Juricic A. Rakar S. Ernst Institute of Automatic Control Laboratory of Control Engineering and Process Automation Technical University of Darmstadt Darmstadt Germany Department of Computer Automation and Control Jozef Stefan Institute Ljubljana Slovenia

Deals with identification of nonlinear processes and model-based fault detection/isolation (FDI). The applicability of the proposed methods is illustrated on a three-tank laboratory setup. The process identification is based on the local linear model tree (LOLIMOT) algorithm and leads to local linear models. The parameters of the local models are used for generation of structured residual equations, similar to the well-known parity space approach. This enables detection and isolation of five different sensor faults of the three-tank process, continously over all ranges of operation.

关键词： Fault diagnosis Fault detection Automatic control Power system modeling Valves Laboratories DC motors automation Neural networks Benchmark testing

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Nonlinear Identification and control of a Thermal Plant Based on Multi-Layer Perceptron Networks with Locally Distributed Dynamics

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IFAC Proceedings Volumes 1997年第25期30卷 359-366页

作者： Mihiar Ayoubi Darmstadt University of Technology Lab. of Control Engineering and Process Automation Landgraf-Georg Str. 4 64283 Darmstadt Germany

This paper addresses the application of neural networks with distributed dynamics to the identification and control of nonlinear systems. The prime concern is to acquire a multi-input, nonlinear neural model which can be used to predict the water outlet temperature of a heat exchanger. The neural model is used to control of the outlet temperature based on the predictive control scheme. The heat exchanger possesses a significant static nonlinearity, minor dynamic nonlinearity and dead times depending on the operating point.

关键词： Dynamic Neural Networks Nonlinear Identification Predictive control Thermal Plant

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