Dynamic Modeling, Predictive Control and Performance Monitoring

Description: Dynamic Modeling, Predictive Control and Performance Monitoring Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). A Data-driven Subspace Approach Author(s): Biao Huang, Ramesh Kadali Format: Paperback Publisher: Springer London Ltd, United Kingdom Imprint: Springer London Ltd ISBN-13: 9781848002326, 978-1848002326 Synopsis A typical design procedure for model predictive control or control performance monitoring consists of: 1. identification of a parametric or nonparametric model; 2. derivation of the output predictor from the model; 3. design of the control law or calculation of performance indices according to the predictor. Both design problems need an explicit model form and both require this three-step design procedure. Can this design procedure be simplified? Can an explicit model be avoided? With these questions in mind, the authors eliminate the first and second step of the above design procedure, a "data-driven" approach in the sense that no traditional parametric models are used; hence, the intermediate subspace matrices, which are obtained from the process data and otherwise identified as a first step in the subspace identification methods, are used directly for the designs. Without using an explicit model, the design procedure is simplified and the modelling error caused by parameterization is eliminated.

Price: 72.91 GBP

Location: Aldershot

End Time: 2024-11-06T17:56:37.000Z

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