Details
| Original language | English |
|---|---|
| Pages (from-to) | 325-332 |
| Number of pages | 8 |
| Journal | ISA transactions |
| Volume | 62 |
| Publication status | Published - 1 May 2016 |
Abstract
This paper presents the design and evaluation of a minimal order Generalized Minimum Variance controller with long-range prediction horizon and how it affects the controller and plant output variances. This study investigates how the increased prediction horizon can contribute to mitigate stochastic disturbances and attenuate oscillations. In order to design high order prediction minimum variance filters, a design procedure independent of the Diophantine Equation solution is used. The evaluation is conducted through simulations and practical essays with two different plants: a first order water flow rate problem and a second order under-damped electronic circuit. Both problems are assessed under an incremental control scheme and based on identified stochastic models. Also, two optimal tuning procedures for the algorithm are proposed.
Keywords
- Kalman filter, Long-range predictive control, Minimum variance control, Stochastic control
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
- Physics and Astronomy(all)
- Instrumentation
- Computer Science(all)
- Computer Science Applications
- Engineering(all)
- Electrical and Electronic Engineering
- Mathematics(all)
- Applied Mathematics
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In: ISA transactions, Vol. 62, 01.05.2016, p. 325-332.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Generalized minimum variance control under long-range prediction horizon setups
AU - Silveira, Antonio
AU - Trentini, Rodrigo
AU - Coelho, Antonio
AU - Kutzner, Rüdiger
AU - Hofmann, Lutz
N1 - Funding information: Rodrigo Trentini acknowledges the financial support of the Brazilian Research Agency (CNPq) (Grant no. 247945/2012-9 ).
PY - 2016/5/1
Y1 - 2016/5/1
N2 - This paper presents the design and evaluation of a minimal order Generalized Minimum Variance controller with long-range prediction horizon and how it affects the controller and plant output variances. This study investigates how the increased prediction horizon can contribute to mitigate stochastic disturbances and attenuate oscillations. In order to design high order prediction minimum variance filters, a design procedure independent of the Diophantine Equation solution is used. The evaluation is conducted through simulations and practical essays with two different plants: a first order water flow rate problem and a second order under-damped electronic circuit. Both problems are assessed under an incremental control scheme and based on identified stochastic models. Also, two optimal tuning procedures for the algorithm are proposed.
AB - This paper presents the design and evaluation of a minimal order Generalized Minimum Variance controller with long-range prediction horizon and how it affects the controller and plant output variances. This study investigates how the increased prediction horizon can contribute to mitigate stochastic disturbances and attenuate oscillations. In order to design high order prediction minimum variance filters, a design procedure independent of the Diophantine Equation solution is used. The evaluation is conducted through simulations and practical essays with two different plants: a first order water flow rate problem and a second order under-damped electronic circuit. Both problems are assessed under an incremental control scheme and based on identified stochastic models. Also, two optimal tuning procedures for the algorithm are proposed.
KW - Kalman filter
KW - Long-range predictive control
KW - Minimum variance control
KW - Stochastic control
UR - http://www.scopus.com/inward/record.url?scp=84969338125&partnerID=8YFLogxK
U2 - 10.1016/j.isatra.2016.01.019
DO - 10.1016/j.isatra.2016.01.019
M3 - Article
VL - 62
SP - 325
EP - 332
JO - ISA transactions
JF - ISA transactions
SN - 0019-0578
ER -