检索结果-内蒙古大学图书馆

Knowledge-Based Structures for Fault Diagnosis and Its Applications

IFAC Proceedings Volumes 1997年第27期30卷 1-18页

作者： Rolf Isermann Institute of Automatic Control Laboratory of Control Engineering and Process Automation Darmstadt University of Technology Landgraf-Georg Str. 4 D-64283 Darmstadt Germany Phone: +49 (6151) 16-7412 FAX: +49 (6151)293604

The operation of technical processes requires increasingly advanced supervision and fault diagnosis to improve reliability, safety and economy. This paper describes structures for advanced methods of fault detection and diagnosis. It begins with a consideration of a knowledge-based procedure which is based on analytical and heuristic information. Then different methods of fault detection are considered, which extract features from measured signals and use process and signal models. These methods are based on parameter estimation, state estimation and parity equations. By comparison with the normal behaviour, analytic symptoms are generated. Human operators may be a further source of information, and support the generation of heuristic symptoms. For fault diagnosis, all symptoms have to be processed in order to determine possible faults. This can be performed by classification methods or approximate reasoning, using probabilistic or possibilistic (fuzzy) approaches based on if-then-rules. The application of these methods is shown for the fault detection and diagnosis of Dieselengines.

关键词： Fault detection supervision monitoring parameter estimation parity equations technical processes actuators sensors fault diagnosis diagnostic reasoning fuzzy reasoning wheel suspension electrical mechanical actuator

来源：评论

学校读者我要写书评

暂无评论

Adaptive Predictive control Based on Local Linear Fuzzy Models

引用

IFAC Proceedings Volumes 1997年第11期30卷 819-824页

作者： Martin Fischer Oliver Nelles 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 Phone: +49/6151/16-5109 Fax: +49/6151/293445

In this paper, local linear fuzzy models are used for adaptive predictive control of nonlinear processes. First, an algorithm (LOLIMOT = local linear model tree algorithm) for off-line identification of Takagi-Sugeno type fuzzy models is briefly reviewed. In order to cope with time-variant nonlinear processes and also with the influence of non-measurable disturbances, an on-line adaptation of the model is performed. A recursive least-squares algorithm (RLS) is applied to update the linear parameters in the rule consequents locally. The local estimation results in low computational effort and avoids forgetting in non-active operating regimes. The effectiveness of the approach is demonstrated by simulations and by controlling the output temperature of a cross-flow heat exchanger.

关键词： nonlinear control predictive control adaptation fuzzy models heat exchangers

来源：评论

学校读者我要写书评

暂无评论

Model and Signal Based Supervision of Components of Cars

引用

IFAC Proceedings Volumes 1997年第8期30卷 479-484页

作者： Thomas Weispfenning Institute of Automatic Control Laboratory of Control Engineering and Process Automation Darmstadt University of Technology Landgraf-Georg-Str. 4 D-64283 Darmstadt Germany Phone: +49(6151)16-7412 FAX: +49(6151)293604

In this paper methods for fault diagnosis of car components are presented. Model based methods like parameter estimation can be used for an estimation of the process coefficients. By dividing the nonlinear characteristic curve into several sections good estimation results can be achieved and a diagnosis of the shock absorber be performed. Signal spectra estimation for detection of tire pressure loss requires only an accelerometer to measure the vertical acceleration of the wheel. The presented results were obtained with measured data drawn from a test rig and a driving car. The proposed methods are suited for an on-line supervision of the car as well as for technical inspection e.g. in workshops.

关键词： fault detection supervision vehicle suspension signal analysis parameter estimation

来源：评论

学校读者我要写书评

暂无评论

Orthonormal Basis Functions for Nonlinear System Identification with Local Linear Model Trees (LOLIMOT)

引用

IFAC Proceedings Volumes 1997年第11期30卷 639-644页

作者： Oliver Nelles Darmstadt University of Technology Institute of Automatic Control Laboratory of Control Engineering and Process Automation Landgraf-Georg-Str. 4 D-64283 Darmstadt Germany Phone: +49/6151/16-4524 Fax: +49/6151/293445

A new approach for identification of nonlinear dynamic systems is proposed. It is based on a combination of generalized orthonormal basis functions and local linear model trees (LOLIMOT). The main idea is to approximate an unknown function from data by the interpolation of many local linear models. The number of local linear models and their validity regions are determined by a tree construction algorithm that partitions the input space by axisorthogonal cuts. The parameters of the local linear models are estimated by minimizing a equation error criterion (ARX models). These local parametric models are replaced by linear parameterized output error models based on generalized orthonormal basis functions. Thus, stability of the nonlinear dynamic model can be proven and the low bias property of output error models can be exploited. Furthermore, a subset selection technique may be applied for choosing the complexity of each local linear model. Since different basis functions may be constructed for each local linear model, processes with operating condition dependent dynamic behavior can be modeled efficiently.

关键词： orthonormal basis functions nonlinear system identification local linear models

来源：评论

学校读者我要写书评

暂无评论

Fault Detection of Vehicle Suspensions

引用

IFAC Proceedings Volumes 1997年第18期30卷 801-806页

作者： Thomas Weispfenning Rolf Isermann Institute of Automatic Control Laboratory of Control Engineering and Process Automation Darmstadt University of Technology Landgraf-Georg-Str. 4 D-64283 Darmstadt Germany Phone: +49(6151)16-7412 FAX:+49(6151)293604

In this paper methods for fault detection and diagnosis of vehicle suspensions are presented. With parameter estimation and parity equations symptoms on the current process status can be extracted. By means of parameter estimation detailed symptoms can be generated, allowing an automatic distinction of different faults. For the automatic classification, neural networks were trained. Parity equations are well suited for a detection of sensor faults, although they do not offer the possibility for a distinction of different faults. All the presented results were obtained with measured data drawn from a test rig and a driving car. The proposed methods are suited for an on-line supervision of the car as well as for technical inspection e.g. in workshops.

关键词： fault detection parameter estimation parity equation vehicle suspension tire pressure application results

来源：评论

学校读者我要写书评

暂无评论

Automatic Model Selection in Local Linear Model Trees (LOLIMOT) for Nonlinear System Identification of a Transport Delay process

引用

IFAC Proceedings Volumes 1997年第11期30卷 699-704页

作者： Oliver Nelles Oliver Hecker 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 Phone: +49/6151/16-4524 Fax: +49/6151/293445 th-darmstadt. de

In this paper a new method for nonlinear system identification is proposed. It is based on local linear models constructed by a tree algorithm in combination with a subset selection technique for determination of the local linear models’ structure. The local linear model tree can be interpreted as a Takagi-Sugeno fuzzy model, where the tree algorithm constructs the rule premises, the input membership functions and allows easy control of the model’s complexity (number of rules) while the subset selection technique determines the rule conclusions. The selection of the local linear model structure allows an automatic choice of different model orders and dead times in different operating regions. The capability of this approach to model a real world process with operating point dependent dead times and time constants is demonstrated.

关键词： identification nonlinear local linear models tree structure subset selection

来源：评论

学校读者我要写书评

暂无评论

Robustness Properties of Extended Horizon Nonlinear Predictive control Strategies Applied for the Hammerstein Model

引用

IFAC Proceedings Volumes 1997年第16期30卷 321-325页

作者： Robert Haber Ruth Bars Zoltán Czipríán Department of Process Engineering Laboratory of Process Control Cologne Institute of Technology 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 are promising also in the case of nonlinear systems. Two versions of extended horizon predictive control algorithms are given here for the nonlinear simple Hammerstein model. A quadratic cost function is minimized, which considers the quadratic deviation of the reference signal and the output signal predicted in a future point and also the squares of the control increments. The system model is transformed to a predictive incremental form. Two versions of suboptimal extended horizon control algorithms are given with different assumptions for the control signal during the control horizon. Robustness properties of these algorithms are considered in case of plant-model mismatch through some simulation examples.

关键词： Predictive control nonlinear control control algorithms suboptimal control robustness Hammerstein model

来源：评论

学校读者我要写书评

暂无评论

Robust Design of PID and IMC-Based controllers in the Time Domain

引用

IFAC Proceedings Volumes 1997年第16期30卷 365-370页

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

A third-order proportional process model with parameter uncertainty is controlled by different simple controllers. First the robustness of four different PID-control designs is investigated. Then internal model control (IMC) is designed in the time domain for the exact process model and for its approximating model with a first-order lag and a delay time. Finally, the PID-control of the nominal model is extended by an IMC-like feedback, which makes the control especially robust.

关键词： Robust control PID control internal model control controller design

来源：评论

学校读者我要写书评

暂无评论

On the design and control of mechatronic systems - A survey

引用

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 1996年第1期43卷 4-15页

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

The integration of mechanical systems and microelectronics opens new possibilities for mechanical design and automatic functions. After a discussion of the mechanical and electronic design the organization of information processing in different levels is described, Within this frame ''low-degree intelligent'' mechatronic systems can be developed which comprise adaptive control, supervision with fault diagnosis, and decisions with regard to further actions. This requires the realization of knowledge-based systems with learning abilities. Some aspects of the design of information processing including modeling and estimation, control, and supervision methods are considered. Finally as example an adaptive semiactive shock absorber for vehicle suspension systems is shown.

关键词： control systems Mechatronics Information processing Automatic control Mechanical systems Microelectronics Adaptive control Fault diagnosis Knowledge based systems process design

来源：评论

学校读者我要写书评

暂无评论

Fuzzy systems design based on a hybrid neural structure and application to the fault diagnosis of technical processes

引用

control engineering PRACTICE 1996年第1期4卷 35-42页

作者： Ayoubi, M Technical University of Darmstadt Institute of Automatic Control Laboratory of Control Engineering and Process Automation Landgraf-Georg 4 64283 Darmstadt Germany

A novel structure which models the fuzzy inference mechanism based on neural units is proposed, to combine both the adaptive feature of neural networks and the transparency of fuzzy systems. It is shown how a perceptron with a sigmoidal activity function can perform the aggregation of premise antecedents and can thus implement conjunction or disjunction operations depending on the neuron's threshold. Knowledge-base parameters such as relevance weights of antecedents and priority weights of rules are introduced and discussed. The network topology is extracted by means of a coincidence learning law, the so-called Hebbian rule, in order to limit the problem of high dimensionality known by local classifiers. Two real-world problems are reported: Monitoring of the state of a turbocharger on the basis of model-based symptoms, and the supervision of air pressure in vehicle wheels, based on physically extracted symptoms.

关键词： fault diagnosis rule extraction neuro-fuzzy structure Hebbian learning turbocharger vehicle wheels

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：