Topic

# Transfer function

About: Transfer function is a(n) research topic. Over the lifetime, 14362 publication(s) have been published within this topic receiving 214983 citation(s). The topic is also known as: system function & network function.

##### Papers published on a yearly basis

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07 Jun 1995

TL;DR: Striking a balance between theory and applications, Linear System Theory and Design, 3/e, is ideal for use in advanced undergraduate/first-year graduate courses in linear systems and multivariable system design in electrical, mechanical, chemical, and aeronautical engineering departments.

Abstract: From the Publisher:
An extensive revision of the author's highly successful text, this third edition of Linear System Theory and Design has been made more accessible to students from all related backgrounds. After introducing the fundamental properties of linear systems, the text discusses design using state equations and transfer functions. The two main objectives of the text are to: use simple and efficient methods to develop results and design procedures; enable students to employ the results to carry out design. Striking a balance between theory and applications, Linear System Theory and Design, 3/e, is ideal for use in advanced undergraduate/first-year graduate courses in linear systems and multivariable system design in electrical, mechanical, chemical, and aeronautical engineering departments. It assumes a working knowledge of linear algebra and the Laplace transform and an elementary knowledge of differential equations.

3,913 citations

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16 Aug 1989

TL;DR: This book discusses the development of Empirical Models from Process Data, Dynamic Behavior of First-Order and Second-Order Processes, and Dynamic Response Characteristics of More Complicated Processes.

Abstract: PART ONE: INTRODUCTORY CONCEPTS.1. Introduction to Process Control.2. Theoretical Models of Chemical Processes.PART TWO: DYNAMIC BEHAVIOR OF PROCESSES.3. Laplace Transforms.4. Transfer Function and State-Space Models.5. Dynamic Behavior of First-Order and Second-Order Processes.6. Dynamic Response Characteristics of More Complicated Processes.7. Development of Empirical Models from Process Data.PART THREE: FEEDBACK AND FEEDFORWARD CONTROL.8. Feedback Controllers.9. Control System Instrumentation.10. Overview of Control System Design.11. Dynamic Behavior and Stability of Closed-Loop Control Systems.12. PID Controller Design, Tuning, and Troubleshooting.13. Frequency Response Analysis.14. Control System Design Based on Frequency Response Analysis.15. Feedforward and Radio Control.PART FOUR: ADVANCED PROCESS CONTROL.16. Enhanced Single-Loop Control Strategies.17. Digital Sampling, Filtering, and Control.18. Multiloop and Multivariable Control.19. Real-Time Optimization.20. Model Predictive Control.21. Process Monitoring.22. Batch Process Control.23. Introduction to Plantwide Control.24. Plantwide Control System Design .Appendix A: Digital Process Control Systems: Hardware and Software.Appendix B: Review of Thermodynamics Concepts for Conservation Equations.Appendix C: Use of MATLAB in Process Control.Appendix D: Contour Mapping and the Principle of the Argument.Appendix E: Dynamic Models and Parameters Used for Plantwide Control Chapters.

2,243 citations

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08 Jun 1976TL;DR: A new canonical circuit model is proposed, whose fixed topology contains all the essential inputr-output and control properties of any dc-todc switching converter, regardless of its detailed configuration, and by which different converters can be characterized in the form of a table conveniently stored in a computer data bank to provide a useful tool for computer aided design and optimization.

Abstract: A method for modelling switching-converter power stages is developed, whose starting point is the unified state-space representation of the switched networks and whose end result is either a complete state-space description or its equivalent small-signal low<-f requency linear circuit model. A new canonical circuit model is proposed, whose fixed topology contains all the essential inputr-output and control properties of any dc-todc switching converter, regardless of its detailed configuration, and by which different converters can be characterized in the form of a table conveniently stored in a computer data bank to provide a useful tool for computer aided design and optimization. The new canonical circuit model predicts that, in general;switching action introduces both zeros and poles into the duty ratio to output transfer function in addition to those from the effective filter network.

1,900 citations

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TL;DR: In this article, a canonical circuit model is proposed, whose fixed topology contains all the essential input-output and control properties of any d.c.-to-d.c. switching converter, regardless of its detailed configuration, and by which different converters can be characterized in the form of a table conveniently stored in a computer data bank.

Abstract: A method for modelling switching-converter power stages is developed, whose starting-point is the unified state-space representation of the switched notworks and whose end result is either a complete state-space description or its equivalent small-signal low-frequency linear circuit model. A new canonical circuit model is proposed, whose fixed topology contains all the essential input-output and control properties of any d.c.-to-d.c. switching converter, regardless of its detailed configuration, and by which different converters can be characterized in the form of a table conveniently stored in a computer data bank to provide a useful tool for computer-aided design and optimization. The new canonical circuit model predicts that, in general, switching action introduces both zeros and poles into the duty ratio to output transfer function in addition to those from the effective filter network.

1,809 citations

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TL;DR: In this article, it was shown that the state vector of a linear system can be reconstructed from observations of the system inputs and outputs, and that the observer which reconstructs this state vector is itself a linear systems whose complexity decreases as the number of output quantities available increases.

Abstract: In much of modern control theory designs are based on the assumption that the state vector of the system to be controlled is available for measurement. In many practical situations only a few output quantities are available. Application of theories which assume that the state vector is known is severely limited in these cases. In this paper it is shown that the state vector of a linear system can be reconstructed from observations of the system inputs and outputs. It is shown that the observer, which reconstructs the state vector, is itself a linear system whose complexity decreases as the number of output quantities available increases. The observer may be incorporated in the control of a system which does not have its state vector available for measurement. The observer supplies the state vector, but at the expense of adding poles to the over-all system.

1,478 citations