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Design of a fault tolerant model predictive control using symbolic processing software

Design of a fault tolerant model predictive control using symbolic processing software This paper gives a controller for a fault tolerant model predictive control when a fault occurs at output feedback loop. Fault tolerant control is to control safely even when a fault occurs. That is, the steady gain does not change at a fault and transient response has not a large overshoot. The transient response is decided by the poles of the closed-loop and the controller. Hence, this paper derives the mathematical expressions of specifications: 1) the closed-loop poles; 2) the controller poles; 3) the steady gain at the output feedback failure by using symbolic processing software. Using the obtained expressions this paper gives a straightforward design procedure. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Advanced Mechatronic Systems Inderscience Publishers

Design of a fault tolerant model predictive control using symbolic processing software

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd
ISSN
1756-8412
eISSN
1756-8420
DOI
10.1504/IJAMECHS.2017.095890
Publisher site
See Article on Publisher Site

Abstract

This paper gives a controller for a fault tolerant model predictive control when a fault occurs at output feedback loop. Fault tolerant control is to control safely even when a fault occurs. That is, the steady gain does not change at a fault and transient response has not a large overshoot. The transient response is decided by the poles of the closed-loop and the controller. Hence, this paper derives the mathematical expressions of specifications: 1) the closed-loop poles; 2) the controller poles; 3) the steady gain at the output feedback failure by using symbolic processing software. Using the obtained expressions this paper gives a straightforward design procedure.

Journal

International Journal of Advanced Mechatronic SystemsInderscience Publishers

Published: Jan 1, 2017

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