7. Multivariable Process Control Choosing Controlled Variables Pairing Controlled and Manipulated Variables Decoupling Control Systems McGraw Hill - Process Control Systems (Shinskey) - Download as PDF File .pdf), Text File .txt) or read online. Process Control Systems - Shinskey - 4th - Ebook download as PDF File .pdf) or read book online.
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Process control systems, second edition, by F. G. Shinskey; McGraw‐Hill, february, ; pages; $ T. J. McAvoy. Professor. Chemical Engineering. F. G. SHINSKEY () also necessary to properly design and apply process control strategies. PID algorithms that continuously (in analog control systems). Control Systems — Cascade Loops. F. G. SHINSKEY (, ). B. G. LIPTÁK (). R. BARS, J. HETTHÉSSY (). INTRODUCTION. Cascade control.
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First published: January But the most brilliantly conceived control strategy, by itself, is nothing.
By the same token, the most definitive mathematical representation of the process, alone, is worthless. The control system must be the embodiment of the process characteristics if it is to perform as intended. Without a process, there can be no control system. Anyone who designs controls without knowing what is to be controlled is fooling himself.
A pressure regulator cannot be used to control composition. Neither can a temperature controller on a fractionator perform the same function as one on a heater. For these reasons this entire text is written from the viewpoint of the needs of the process. Each type of physicalchemical operation which has a history of misbehavior is treated individually.
Not every situation can be covered, because plants and specifications differ, and so do people. If for no other reason, this book will never be complete.
But enough attention is given to basic principles and typical applications to permit extension to a broad area of problems. The plant engineer can take it from there. In appreciation for their assistance in this endeavor, I wish to express my gratitude to Bill Vannah for providing the initiative, to Molly Dickinson, who did all the typing, and to John Louis for his thoughtful criticism. Model-based control, on the other hand, makes use of a model of the process either fundamentally-based or empirical to decide on the appropriate control strategy to be implemented to achieve the desired objective.
In principle, these can lead to improved performance, but, in practice, their performance may be strongly dependent on the accuracy of the model used. Some simple examples are given by Seborg et al.
Nagy, I. Noltingk, B.
Seborg, D. Shinskey, E.