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Title: Suboptimal nonlinear predictive controllers
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Abstract:
Predictive control based on linear models has become a mature technology in the last decade. Many successful real-time applications can be found in almost every sector of industry. Nonlinear predictive control can further increase the performance of this easy-to-understand control strategy. ; One of the main problems of implementing nonlinear predictive control is the computational aspect, which is of most importance in real-life applications. In this paper, suboptimal nonlinear predictive control strategies are proposed and compared. The nonlinear predictors are built based on neural identification methods or by white modelling. ; The use of diophantine equations, which is a common technique to calculate the optimal contribution of the noise model, is avoided by using a more natural method. The comparison between the control algorithms is made based on a simulated discrete multivariable nonlinear system and a continuous stirred tank reactor.
Publisher:
Zielona Góra: Uniwersytet Zielonogórski
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Source:
AMCS, volume 9, number 1 (1999) ; click here to follow the link
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Biblioteka Uniwersytetu Zielonogórskiego
Object collections:
- Digital Library of Zielona Góra > Repository > Faculties > Faculty of Computer, Electrical and Control Engineering
- Digital Library of Zielona Góra > Repository > Types of work > Articles
- Digital Library of Zielona Góra > Repository > Scientific journals and UZ publishing series > International Journal of Applied Mathematics and Computer Science (AMCS)
- Digital Library of Zielona Góra > Repository > Scientific journals and UZ publishing series > International Journal of Applied Mathematics and Computer Science (AMCS) > International Journal of Applied Mathematics and Computer Science (AMCS) (1999)
Last modified:
Sep 3, 2021
In our library since:
Jan 19, 2021
Number of object content hits:
65
All available object's versions:
https://zbc.uz.zgora.pl/publication/64777
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International Journal of Applied Mathematics and Computer Science (AMCS)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 26 (2016)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 25 (2015)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 24 (2014)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 23 (2013)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 22 (2012)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 21 (2011)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 20 (2010)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 19 (2009)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 18 (2008)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 17 (2007)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 16 (2006)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 15 (2005)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 13 (2003)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 12 (2002)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 11 (2001)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 10 (2000)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 9 (1999)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 9, number 1 (1999)
- Some issues in the design of predictive controllers
- Adaptive control through on-line optimization. The MPCI paradigm and variants
- Analytical design of stable continuous-time generalised predictive control
- Robust predictive control using a time-varying youla parameter
- Suboptimal nonlinear predictive controllers
- On fast state-space algorithms for predictive control
- Sub-optimal nonlinear predictive and adaptive control based on the parametric Volterra model
- Adaptive predictive controller using orthonormal series functions
- Adaptive predictive control of a distillation column
- D-step ahead Kalman predictor for controlled autoregressive processes with random coefficients
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 9, number 2 (1999)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 9, number 3 (1999)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 9, number 4 (1999)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 9, number 1 (1999)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 8 (1998)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 7 (1997)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 6 (1996)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 5 (1995)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 4 (1994)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 3 (1993)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 2 (1992)
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International Journal of Applied Mathematics and Computer Science (AMCS),volume 1 (1991)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 26 (2016)
| Edition name | Date |
|---|---|
| Suboptimal nonlinear predictive controllers | Sep 3, 2021 |
