Abstract
One of the reasons for the success of the traditional PID controllers in industry is that PID are very easy to implement and tune using heuristic tuning rules such as the Ziegler-Nichols rules frequently used in practice. A Generalized Predictive Controller, as shown in the previous chapter, results in a linear control law which is very easy to implement once the controller parameters are known. The derivation of the GPC parameters requires, however, some mathematical complexities such as recursively solving the Diophantine equation, forming the matrices G, G′ and f and then solving a set of linear equations. Although this is not a problem for people in the research control community where mathematical packages are normally available, it may be discouraging for practitioners used to much simpler ways of implementing and tuning controllers.
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© 2007 Springer-Verlag London
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Camacho, E.F., Bordons, C. (2007). Simple Implementation of GPC for Industrial Processes. In: Model Predictive control. Advanced Textbooks in Control and Signal Processing. Springer, London. https://doi.org/10.1007/978-0-85729-398-5_5
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DOI: https://doi.org/10.1007/978-0-85729-398-5_5
Publisher Name: Springer, London
Print ISBN: 978-1-85233-694-3
Online ISBN: 978-0-85729-398-5
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