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PID Control : New Identification and Design Methods /

By: Crowe, J [author.].
Contributor(s): Tan, K.K [author.] | Lee, T.H [author.] | Ferdous, R [author.] | Katebi, M.R [author.] | Huang, H.-P [author.] | Jeng, J.-C [author.] | Tang, K.S [author.] | Chen, G.R [author.] | Man, K.F [author.] | Kwong, S [author.] | Sánchez, A [author.] | Wang, Q.-G [author.] | Zhang, Yong [author.] | Zhang, Yu [author.] | Martin, P [author.] | Grimble, M.J [author.] | Greenwood, D.R [author.] | Johnson, Michael A [editor.] | Moradi, Mohammad H [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: London : Springer London, 2005.Description: XXVIII, 544 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9781846281488.Subject(s): Engineering | System theory | Complexity, Computational | Engineering design | Control engineering | Industrial engineering | Production engineering | Engineering | Control | Complexity | Industrial and Production Engineering | Engineering Design | Systems Theory, ControlDDC classification: 629.8 Online resources: Click here to access online
Contents:
PID Control Technology -- Some PID Control Fundamentals -- On-line Model-Free Methods -- Automatic PID Controller Tuning — the Nonparametric Approach -- Relay Experiments for Multivariable Systems -- Phase-Locked Loop Methods -- Phase-Locked Loop Methods and PID Control -- Process Reaction Curve and Relay Methods Identification and PID Tuning -- Fuzzy Logic and Genetic Algorithm Methods in PID Tuning -- Tuning PID Controllers Using Subspace Identification Methods -- Design of Multi-Loop and Multivariable PID Controllers -- Restricted Structure Optimal Control -- Predictive PID Control.
In: Springer eBooksSummary: The effectiveness of proportional-integral-derivative (PID) controllers for a large class of process systems has ensured their continued and widespread use in industry. Similarly there has been a continued interest from academia in devising new ways of approaching the PID tuning problem. To the industrial engineer and many control academics this work has previously appeared fragmented; but a key determinant of this literature is the type of process model information used in the PID tuning methods. PID Control presents a set of coordinated contributions illustrating methods, old and new, that cover the range of process model assumptions systematically. After a review of PID technology, these contributions begin with model-free methods, progress through non-parametric model methods (relay experiment and phase-locked-loop procedures), visit fuzzy-logic- and genetic-algorithm-based methods; introduce a novel subspace identification method before closing with an interesting set of parametric model techniques including a chapter on predictive PID controllers. Highlights of PID Control include: an introduction to PID control technology features and typical industrial implementations; chapter contributions ordered by the increasing quality of the model information used; novel PID control concepts for multivariable processes. PID Control will be useful to industry-based engineers wanting a better understanding of what is involved in the steps to a new generation of PID controller techniques. Academics wishing to have a broader perspective of PID control research and development will find useful pedagogical material and research ideas in this text. .
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PID Control Technology -- Some PID Control Fundamentals -- On-line Model-Free Methods -- Automatic PID Controller Tuning — the Nonparametric Approach -- Relay Experiments for Multivariable Systems -- Phase-Locked Loop Methods -- Phase-Locked Loop Methods and PID Control -- Process Reaction Curve and Relay Methods Identification and PID Tuning -- Fuzzy Logic and Genetic Algorithm Methods in PID Tuning -- Tuning PID Controllers Using Subspace Identification Methods -- Design of Multi-Loop and Multivariable PID Controllers -- Restricted Structure Optimal Control -- Predictive PID Control.

The effectiveness of proportional-integral-derivative (PID) controllers for a large class of process systems has ensured their continued and widespread use in industry. Similarly there has been a continued interest from academia in devising new ways of approaching the PID tuning problem. To the industrial engineer and many control academics this work has previously appeared fragmented; but a key determinant of this literature is the type of process model information used in the PID tuning methods. PID Control presents a set of coordinated contributions illustrating methods, old and new, that cover the range of process model assumptions systematically. After a review of PID technology, these contributions begin with model-free methods, progress through non-parametric model methods (relay experiment and phase-locked-loop procedures), visit fuzzy-logic- and genetic-algorithm-based methods; introduce a novel subspace identification method before closing with an interesting set of parametric model techniques including a chapter on predictive PID controllers. Highlights of PID Control include: an introduction to PID control technology features and typical industrial implementations; chapter contributions ordered by the increasing quality of the model information used; novel PID control concepts for multivariable processes. PID Control will be useful to industry-based engineers wanting a better understanding of what is involved in the steps to a new generation of PID controller techniques. Academics wishing to have a broader perspective of PID control research and development will find useful pedagogical material and research ideas in this text. .

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