PID Controller Tuning Using the Magnitude Optimum Criterion

Name: PID Controller Tuning Using the Magnitude Optimum Criterion
Brand: Springer International Publishing AG
SKU: 9783319348605
Price: 124.88 EUR
Availability: InStock

Автор: Konstantinos G. Papadopoulos

Език:

Корици: С меки корици

Издател: Springer International Publishing AG

Наличност: Външен склад

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124.88 € 244.25 лв

An instructive reference that will help control researchers and engineers, interested in a variety o...

Информация за книгата

Автор

Konstantinos G. Papadopoulos

Език

Английски език

Корици

Книга - С меки корици

Издадена

2016

страници

296

EAN

9783319348605

ISBN

3319348604

Enbook ID

13633485

Издател

Springer International Publishing AG

Теглоt

4803

Размери

155 x 235 x 19

Пълно описание

An instructive reference that will help control researchers and engineers, interested in a variety of industrial processes, to take advantage of a powerful tuning method for the ever-popular PID control paradigm.§§This monograph presents explicit PID tuning rules for linear control loops regardless of process complexity. It shows the reader how such loops achieve zero steady-position, velocity, and acceleration errors and are thus able to track fast reference signals. The theoretical development takes place in the frequency domain by introducing a general-transfer-function-known process model and by exploiting the principle of the magnitude optimum criterion. It is paralleled by the presentation of real industrial control loops used in electric motor drives. The application of the proposed tuning rules to a large class of processes shows that irrespective of the complexity of the controlled process the shape of the step and frequency response of the control loop exhibits a specific performance. This specific performance, along with the PID explicit solution, formulates the basis for developing an automatic tuning method for the PID controller parameters which is a problem often met in many industry applications-temperature, pH, and humidity control, ratio control in product blending, and boiler-drum level control, for example. The process of the model is considered unknown and controller parameters are tuned automatically such that the aforementioned performance is achieved. The potential both for the explicit tuning rules and the automatic tuning method is demonstrated using several examples for benchmark process models recurring frequently in many industry applications.§§

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