This book offers first a short introduction to advanced supervision, fault detection and diagnosis methods. It then describes model-based methods of fault detection and diagnosis for the main components of gasoline and diesel engines, such as the intake system, fuel supply, fuel injection, combustion process, turbocharger, exhaust system and exhaust gas aftertreatment. Additionally, model-based fault diagnosis of electrical motors, electric, pneumatic and hydraulic actuators and fault-tolerant systems is treated. In general series production sensors are used. It includes abundant experimental results showing the detection and diagnosis quality of implemented faults. Written for automotive engineers in practice, it is also of interest to graduate students of mechanical and electrical engineering and computer science.

Precise dynamic models of processes are required for many applications, ranging from control engineering to the natural sciences and economics. Frequently, such precise models cannot be derived using theoretical considerations alone. Therefore, they must be determined experimentally. This book treats the determination of dynamic models based on measurements taken at the process, which is known as system identification or process identification. Both offline and online methods are presented, i.e. methods that post-process the measured data as well as methods that provide models during the measurement. The book is theory-oriented and application-oriented and most methods covered have been used successfully in practical applications for many different processes. Illustrative examples in this book with real measured data range from hydraulic and electric actuators up to combustion engines. Real experimental data is also provided on the Springer webpage, allowing readers to gather their first experience with the methods presented in this book. Among others, the book covers the following subjects: determination of the non-parametric frequency response, (fast) Fourier transform, correlation analysis, parameter estimation with a focus on the method of Least Squares and modifications, identification of time-variant processes, identification in closed-loop, identification of continuous time processes, and subspace methods. Some methods for nonlinear system identification are also considered, such as the Extended Kalman filter and neural networks. The different methods are compared by using a real three-mass oscillator process, a model of a drive train. For many identification methods, hints for the practical implementation and application are provided. The book is intended to meet the needs of students and practicing engineers working in research and development, design and manufacturing.

Supervision, condition-monitoring, fault detection, fault diagnosis and fault management play an increasing role for technical processes and vehicles in order to improve reliability, availability, maintenance and lifetime. For safety-related processes fault-tolerant systems with redundancy are required in order to reach comprehensive system integrity.

This book is a sequel of the book Fault-Diagnosis Systems published in 2006, where the basic methods were described. After a short introduction into fault-detection and fault-diagnosis methods the book shows how these methods can be applied for a selection of 20 real technical components and processes as examples, such as:

Electrical drives (DC, AC)

Electrical actuators

Fluidic actuators (hydraulic, pneumatic)

Centrifugal and reciprocating pumps

Pipelines (leak detection)

Industrial robots

Machine tools (main and feed drive, drilling, milling, grinding)

Heat exchangers

Also realized fault-tolerant systems for electrical drives, actuators and sensors are presented.

The book describes why and how the various signal-model-based and process-model-based methods were applied and which experimental results could be achieved. In several cases a combination of different methods was most successful.

The book is dedicated to graduate students of electrical, mechanical, chemical engineering and computer science and for engineers.

The increasing demands for internal combustion engines with regard to fuel consumption, emissions and driveability lead to more actuators, sensors and complex control functions. A systematic implementation of the electronic control systems requires mathematical models from basic design through simulation to calibration. The book treats physically-based as well as models based experimentally on test benches for gasoline (spark ignition) and diesel (compression ignition) engines and uses them for the design of the different control functions. The main topics are: - Development steps for engine control - Stationary and dynamic experimental modeling - Physical models of intake, combustion, mechanical system, turbocharger, exhaust, cooling, lubrication, drive train - Engine control structures, hardware, software, actuators, sensors, fuel supply, injection system, camshaft - Engine control methods, static and dynamic feedforward and feedback control, calibration and optimization, HiL, RCP, control software development - Control of gasoline engines, control of air/fuel, ignition, knock, idle, coolant, adaptive control functions - Control of diesel engines, combustion models, air flow and exhaust recirculation control, combustion-pressure-based control (HCCI), optimization of feedforward and feedback control, smoke limitation and emission control This book is an introduction to electronic engine management with many practical examples, measurements and research results. It is aimed at advanced students of electrical, mechanical, mechatronic and control engineering and at practicing engineers in the field of combustion engine and automotive engineering.

The introduction of mechatronic components for the powertrain, steering and braking systems opens the way to automatic driving functions. Together with internal and environmental sensors, various driver assistance systems are going to be developed for improving driving comfort and safety. Automatic driving control functions suppose a well-designed vehicle behavior. In order to develop and implement the software-based control functions mathematical vehicle models for the stationary and dynamic behavior are required. The book first introduces basic theoretically derived models for the tire traction and force transfer, the longitudinal, lateral, roll and pitch dynamic behavior and related components, like suspensions, steering systems and brakes. These models have to be tailored to allow an identification of the many unknown parameters during driving, also in dependence of different road conditions, velocity and vehicle load. Based on these mathematical models drive dynamic control systems are developed for semi-active and active suspensions, hydraulic and electromechanical brakes including ABS, traction and steering control. Then driver assistance systems like adaptive cruise control (ACC), electronic stability control (ESC), electronic course control and anti-collision control systems are considered. The anti-collision systems are designed and tested for emergency braking, emergency steering and avoiding of overtaking accidents. The book is dedicated to automotive engineers as well as to graduate students of mechanical, electrical and mechatronic engineering and computer science.

This book offers first a short introduction to advanced supervision, fault detection and diagnosis methods. It then describes model-based methods of fault detection and diagnosis for the main components of gasoline and diesel engines, such as the intake system, fuel supply, fuel injection, combustion process, turbocharger, exhaust system and exhaust gas aftertreatment. Additionally, model-based fault diagnosis of electrical motors, electric, pneumatic and hydraulic actuators and fault-tolerant systems is treated. In general series production sensors are used. It includes abundant experimental results showing the detection and diagnosis quality of implemented faults. Written for automotive engineers in practice, it is also of interest to graduate students of mechanical and electrical engineering and computer science.

The increasing demands for internal combustion engines with regard to fuel consumption, emissions and driveability lead to more actuators, sensors and complex control functions. A systematic implementation of the electronic control systems requires mathematical models from basic design through simulation to calibration. The book treats physically-based as well as models based experimentally on test benches for gasoline (spark ignition) and diesel (compression ignition) engines and uses them for the design of the different control functions. The main topics are: - Development steps for engine control - Stationary and dynamic experimental modeling - Physical models of intake, combustion, mechanical system, turbocharger, exhaust, cooling, lubrication, drive train - Engine control structures, hardware, software, actuators, sensors, fuel supply, injection system, camshaft - Engine control methods, static and dynamic feedforward and feedback control, calibration and optimization, HiL, RCP, control software development - Control of gasoline engines, control of air/fuel, ignition, knock, idle, coolant, adaptive control functions - Control of diesel engines, combustion models, air flow and exhaust recirculation control, combustion-pressure-based control (HCCI), optimization of feedforward and feedback control, smoke limitation and emission control This book is an introduction to electronic engine management with many practical examples, measurements and research results. It is aimed at advanced students of electrical, mechanical, mechatronic and control engineering and at practicing engineers in the field of combustion engine and automotive engineering.

Precise dynamic models of processes are required for many applications, ranging from control engineering to the natural sciences and economics. Frequently, such precise models cannot be derived using theoretical considerations alone. Therefore, they must be determined experimentally. This book treats the determination of dynamic models based on measurements taken at the process, which is known as system identification or process identification. Both offline and online methods are presented, i.e. methods that post-process the measured data as well as methods that provide models during the measurement. The book is theory-oriented and application-oriented and most methods covered have been used successfully in practical applications for many different processes. Illustrative examples in this book with real measured data range from hydraulic and electric actuators up to combustion engines. Real experimental data is also provided on the Springer webpage, allowing readers to gather their first experience with the methods presented in this book. Among others, the book covers the following subjects: determination of the non-parametric frequency response, (fast) Fourier transform, correlation analysis, parameter estimation with a focus on the method of Least Squares and modifications, identification of time-variant processes, identification in closed-loop, identification of continuous time processes, and subspace methods. Some methods for nonlinear system identification are also considered, such as the Extended Kalman filter and neural networks. The different methods are compared by using a real three-mass oscillator process, a model of a drive train. For many identification methods, hints for the practical implementation and application are provided. The book is intended to meet the needs of students and practicing engineers working in research and development, design and manufacturing.

The great advances made in large-scale integration of semiconductors and the resulting cost-effective digital processors and data storage devices determine the present development of automation. The application of digital techniques to process automation started in about 1960, when the first process computer was installed. From about 1970 process computers with cathodic ray tube display have become standard equipment for larger automation systems. Until about 1980 the annual increase of process computers was about 20 to 30%. The cost of hardware has already then shown a tendency to decrease, whereas the relative cost of user software has tended to increase. Because of the high total cost the first phase of digital process automation is characterized by the centralization of many functions in a single (though sometimes in several) process computer. Application was mainly restricted to medium and large processes. Because of the far-reaching consequences of a breakdown in the central computer parallel standby computers or parallel back-up systems had to be provided. This meant a substantial increase in cost. The tendency to overload the capacity and software problems caused further difficulties. In 1971 the first microprocessors were marketed which, together with large-scale integrated semiconductor memory units and input/output modules, can be assem bled into cost-effective microcomputers. These microcomputers differ from process computers in fewer but higher integrated modules and in the adaptability of their hardware and software to specialized, less comprehensive tasks."

Many processes and systems manifest an increasing integration of mechanical and electronic components with information processing capacity. The development of such mechatronic systems opens the way to many innovative solutions not possible with mechanics or electronics alone.

Mechatronic Systems introduces these developments by considering the dynamic modelling of components together with their interactions. The whole range of elements is presented from actuators, through different kinds of processes, to sensors.

Structured tutorial style takes learning from the basics of unified theoretical modelling, through information processing to examples of system development.

End-of-chapter exercises provide ready-made homework or self-tests.

Offers practical advice for engineering derived from experience with real systems and application-oriented research.

Written by one of the World's leading experts in this progressive field, Mechatronic Systems will be of great value to advanced students working in control, electrical and mechanical engineering and in areas where such definitions are being superseded. It will also prove useful to practising engineers wanting an in-depth understanding of how these disciplines and that of information processing are becoming interlinked.

With increasing demands for efficiency and product quality and progressing integration of automatic control systems in high-cost mechatronic and safety-critical processes, the field of supervision (or monitoring), fault detection and fault diagnosis plays an important role.

The book gives an introduction into advanced methods of fault detection and diagnosis (FDD). After definitions of important terms, the reliability, availability, safety and systems integrity of technical processes is considered. Then fault-detection methods for single signals without models like limit and trend checking and with harmonic and stochastic models, like Fourier analysis, correlation and wavelets are treated. This is followed by fault detection with process models using the relationships between signals like parameter estimation, parity equations, observers and principal component analysis. The treated fault-diagnosis methods include classification methods from Bayes classification to neural networks with decision trees and inference methods from approximate reasoning with fuzzy logic to hybrid fuzzy-neuro systems.

Especially for safety-critical processes fault-tolerant systems are required. Basic redundant structures like n-out-of-m systems, cold and hot standby are considered and ways to design fault-tolerant sensors, actuators and control systems are outlined.

Several practical examples for fault detection and diagnosis of DC motor drives, a centrifugal pump, automotive suspension and tire show applications.

Die Mechatronik im Fahrzeug hat heute entscheidenden Einfluss auf die Gestaltung der Radaufhangungen, Bremsen und Lenkungen und die dadurch moeglichen aktiven Eingriffe. Regelungen ermoeglichen so eine Beeinflussung der Fahrdynamik. Der Entwurf und die Erprobung dieser mechatronischen Systeme erfordert ein modellgestutztes Vorgehen mit verschiedenen Arten der Simulation, modellbasierten Regelungen, UEberwachungs- und Diagnosemethoden bis hin zum Test einer automatisierten Fahrzeugfuhrung. Hier gibt das Buch einen detaillierten UEberblick. Dabei werden besonders mechatronische Bremssysteme, aktive Radaufhangungen, aktive Stabilisatoren, aktive Lenksysteme, ABS-, ESP- und AFS-Regelungen und Fahrer-Assistenz-Systeme zur Abstandsregelung mit Stop-and-Go, zur Spurfuhrung und ein Parkassistent betrachtet. Weitere Kapitel behandeln Diagnosesysteme fur die Querdynamik-Regelung und aktive Fahrwerke.

Die stark gestiegenen Forderungen zur Erhoehung der Leistung und zur Senkung von Kraftstoffverbrauch und Emissionen fuhren zu einer Zunahme der Steuerungs-, Regelungs- und Diagnosefunktionen. Dieses Buch zeigt Entwurf, Erprobung und Implementierung dieser elektronischen Managementfunktionen. An verschiedenen Beispielen werden der modellgestutzte Entwurf der Steuerung und Regelung von Otto- und Dieselmotoren und ihre Applikation im Detail beschrieben, besonders auch fur neue Brennverfahren mit Brennraumdruck-Regelung und fur die Abgasnachbehandlung. Es zeigt das systematische Vorgehen, umfassende Modellbildungs- und Simulationstools und effiziente Applikationsmethoden.

Supervision, condition-monitoring, fault detection, fault diagnosis and fault management play an increasing role for technical processes and vehicles in order to improve reliability, availability, maintenance and lifetime. For safety-related processes fault-tolerant systems with redundancy are required in order to reach comprehensive system integrity. This book is a sequel of the book "Fault-Diagnosis Systems" published in 2006, where the basic methods were described. After a short introduction into fault-detection and fault-diagnosis methods the book shows how these methods can be applied for a selection of 20 real technical components and processes as examples, such as: Electrical drives (DC, AC) Electrical actuators Fluidic actuators (hydraulic, pneumatic) Centrifugal and reciprocating pumps Pipelines (leak detection) Industrial robots Machine tools (main and feed drive, drilling, milling, grinding) Heat exchangers Also realized fault-tolerant systems for electrical drives, actuators and sensors are presented. The book describes why and how the various signal-model-based and process-model-based methods were applied and which experimental results could be achieved. In several cases a combination of different methods was most successful. The book is dedicated to graduate students of electrical, mechanical, chemical engineering and computer science and for engineers.

This well-known book is an introduction to the field of digital, sampled-data control. It treats the field in depth and can be used for courses and for self study. The second edition has been completely revised and expanded with new results. The work now appears in two volumes, with Volume 2 to be published in 1989. The volumes form a unit and take the reader systematically from fundamentals to problems of real applications. The work is directed towards students of electrical and mechanical engineering, computer science (especially with a specialization on automation and control engineering), and other fields like biology, economics, space mathematics and physics. It is also directed to engineers and scientists concerned with solving concrete problems.

Fur viele Aufgabenstellungen bei der Automatisierung technischer Systeme und im Bereich der Naturwissenschaften und Wirtschaftsswissenschaften benotigt man genaue mathematische Modelle fur das dynamische Verhalten von Systemen. Das Werk behandelt Methoden zur Ermittlung dynamischer Modelle aus gemesssenen Signalen, die unter dem Begriff Systemidentifikation oder Prozessidentifikation zusammengefasst werden. Im Band II werden die Parameterschatzmethoden vertieft mit der Maximum-Likelihood- und der der Bayes-Methode und rekursiven Algorithmen mit zahlreichen Varianten und deren algorithmischen Realisierung. Zur Identifikation parametrischer Modelle mit zeitkontinuierlichen Signalen werden Kennwertermittlung, Modellabgleich und Parameterschatzung beschrieben. Es folgt die Identifikation von Mehrgrossensystemen und nichtlinearen Systemen. Mehrere Beispiele zeigen die Anwendung der Identifikation bei technischen Systemen.

Fur viele Aufgabenstellungen bei der Automatisierung technischer Systeme sowie im Bereich der Naturwissenschaften und Wirtschaftswissenschaften benotigt man genaue mathematische Modelle fur das dynamische Verhalten von Systemen. Das Werk behandelt Methoden zur Ermittlung dynamischer Modelle aus gemessenen Signalen, die unter dem Begriff Systemidentifikation oder Prozessidentifikation zusammengefasst werden. "Band 2" beschreibt weitergehende Methoden und Anwendungen: - Maximum-Likelihood-Methode; - Rekursive Parameterschatzung; - Modellabgleich-Verfahren; - Mehrgrossen- und nichtlineare Systeme; - Anwendungen in Maschinenbau und Elektrotechnik, Energie- und Verfahrenstechnik. Beide Bande bilden eine Einheit und fuhren systematisch von den Grundlagen bis zu den Problemen des praktischen Einsatzes. Sie wenden sich daher sowohl an Studenten der Fachrichtungen Elektrotechnik, Maschinenbau, Informatik, Mathematik, Natur- und Wirtschaftswissenschaften als auch an die in der Praxis tatigen Ingenieure und Wissenschaftler."

Fur viele Aufgabenstellungen bei der Automatisierung technischer Systeme und im Bereich der Naturwissenschaften und Wirtschaftswissenschaften benotigt man genaue mathematische Modelle fur das dynamische Verhalten von Systemen. Das Werk behandelt Methoden zur Ermittlung dynamischer Modelle aus gemessenen Signalen, die unter dem Begriff Systemidentifikation oder Prozessidentifikation zusammengefasst werden. In "Band 1" werden die grundlegenden Methoden behandelt. Nach einer kurzen Einfuhrung in die benotigten Grundlagen linearer Systeme wird zunachst die Identifikation nichtparametrischer Modelle mit zeitkontinuierlichen Signalen mittels Fourieranalyse, Frequenzgangmessung und Korrelationsanalyse behandelt. Dann folgt eine Einfuhrung in die Parameterschatzung fur parametrische Modelle mit zeitdiskreten Signalen. Dabei steht die Methode der kleinsten Quadrate im Vordergrund, gefolgt von ihren Modifikationen, der Hilfsvariablenmethode und der stochastischen Approximation."

Testprozesse I, ll, ---, XI zur Simulation: siehe Isermann (1987), Bd.I Je nach ZweckmaBigkeit wird als Dimension fur die Zeit in Sekunden "s" oder "sec" verwendet ("sec" urn Verwechslungen mit der Laplace- Variablen s = 6 ] i Col zu vermeiden) 1 EinfUhrung Das zeitliche Verhalten von Systemen, wie z.B. technischen Systemen aus den Bereichen der Elektrotechnik, Maschinenwesen und Verfahrenstech- nik oder nichttechnischen Systemen aus den Bereichen Biologie, Medizin, Chemie, Physik, okonomie kann mit Hilfe der Systemtheorie nach ein- heitlichen mathematischen Methoden beschrieben werden. Hierzu mussen jedoch mathematische Modelle fur das statische und dynamische Verhal- ten der Systeme bzw. seiner Elemente bekannt sein. Nach DIN 66201 wird unter einem System eine abgegrenzte Anordnung von aufeinander einwirkenden Gebilden verstanden. Mit l oaeC bezeichnet man die Umformung und/oder den Transport von Materie, Energie und/oder Information. Hierbei ist es zweckmaBig, zwischen Teilprozessen und Gesamtprozessen zu unterscheiden. Teilprozesse sind z.B. die Erzeugung von elektrischer aus mechanischer Energie, die spanabhebende Werkstuck- bearbeitung, die Warmeubertragung durch eine Wand oder die chemische Reaktion. usammen mit anderen Teilprozessen bilden sie die Gesamtpro- zesse elektrischer Generator, Werkzeugmaschine, Warmeaustauscher, che- mischer Reaktor. Versteht man nun unter GesamtprozeB ein "Gebilde", dann ergeben mehrere Gesamtprozesse ein System, also z.B. ein Kraftwerk, eine Fertigungsanlage, eine Heizanlage, eine Kunststoffproduktion. Das Verhalten eines Systems ergibt sich somit aus dem Verhalten seiner P- zesse.

Mechatronische Systeme entstehen durch Integration von vorwiegend mechanischen und elektronischen Systemen sowie zugehoriger Informationsverarbeitung. Wesentlich ist dabei die Integration der mechanischen und elektronischen Elemente durch ihre raumliche Anordnung und durch ihre Funktionen sowie die Erzielung synergetischer Effekte. Die ortliche Integration erfolgt durch den konstruktiven Entwurf, die funktionelle Integration durch die Informationsverarbeitung und damit durch die Gestaltung der Software.

Das vorliegende Buch fuhrt in den Aufbau und die Modellbildung mechatronischer Systeme in einer einheitlichen Form ein und stellt das Verhalten von mechanischen Bauelementen, elektrischen Antrieben, Maschinen, Sensoren, Aktoren und Mikrorechnern dar. Ziel dabei ist, ein bestimmtes Systemverhalten zu erreichen.

Die zweite Auflage enthalt wesentliche Erweiterungen bei der Entwicklungsmethodik, bei mechanischen Komponenten, elektrischen Antrieben, Beispielen von Maschinenmodellen, Sensoren, hydraulischen und pneumatischen Aktoren und fehlertoleranten Systemen. Aufgabensammlungen erganzen die einzelnen Kapitel."

Mit diesem Buch liegt eine kompakte Darstellung von Verfahren zur Optimierung der Regelung und Steuerung von Verbrennungsmotoren vor. Sie wendet sich in erster Linie an Ingenieure, die sich mit der regelungstechnischen Analyse und Synthese der Steuerungen und Regelungen besch ftigen. Neben der theoretischen und experimentellen Modellbildung werden der rechnerunterst tzte Entwurf von Steuerungen sowie die optimale Versuchsplanung f r die Vermessung von Motoren auf Pr fst nden behandelt. Weiterhin erf hrt der Leser in diesem Zusammenhang neue Methoden zur Fehlerdiagnose und dem Einsetzen von Neuronalen Netzen und Entwicklungs-Tools f r die Motorentwicklung.