文件名称:Thed
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This work presents a combination of the Generalized Predictive Control (GPC) algorithm with event-based
sampling techniques. The proposed control scheme preserves all well-known individual advantages of
GPC and event-based sampling algorithms, respectively. The main benefits of this combination are an
important reduction of actuation load meanwhile the control system performance is maintained within
an acceptable level. Guidelines for a tuning procedure are given and tested for a wide set of industrial
process models. Furthermore, the resulting algorithm is simple to be implemented and allows to establish
a tradeoff between control performance and the number of actuations. The performance of the proposed
control algorithm is first verified for a first-order plus delay process and afterwards it is uated by
using a case study based on the greenhouse temperature control problem.-This work presents a combination of the Generalized Predictive Control (GPC) algorithm with event-based
sampling techniques. The proposed control scheme preserves all well-known individual advantages of
GPC and event-based sampling algorithms, respectively. The main benefits of this combination are an
important reduction of actuation load meanwhile the control system performance is maintained within
an acceptable level. Guidelines for a tuning procedure are given and tested for a wide set of industrial
process models. Furthermore, the resulting algorithm is simple to be implemented and allows to establish
a tradeoff between control performance and the number of actuations. The performance of the proposed
control algorithm is first verified for a first-order plus delay process and afterwards it is uated by
using a case study based on the greenhouse temperature control problem.
sampling techniques. The proposed control scheme preserves all well-known individual advantages of
GPC and event-based sampling algorithms, respectively. The main benefits of this combination are an
important reduction of actuation load meanwhile the control system performance is maintained within
an acceptable level. Guidelines for a tuning procedure are given and tested for a wide set of industrial
process models. Furthermore, the resulting algorithm is simple to be implemented and allows to establish
a tradeoff between control performance and the number of actuations. The performance of the proposed
control algorithm is first verified for a first-order plus delay process and afterwards it is uated by
using a case study based on the greenhouse temperature control problem.-This work presents a combination of the Generalized Predictive Control (GPC) algorithm with event-based
sampling techniques. The proposed control scheme preserves all well-known individual advantages of
GPC and event-based sampling algorithms, respectively. The main benefits of this combination are an
important reduction of actuation load meanwhile the control system performance is maintained within
an acceptable level. Guidelines for a tuning procedure are given and tested for a wide set of industrial
process models. Furthermore, the resulting algorithm is simple to be implemented and allows to establish
a tradeoff between control performance and the number of actuations. The performance of the proposed
control algorithm is first verified for a first-order plus delay process and afterwards it is uated by
using a case study based on the greenhouse temperature control problem.
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1-s2.0-S0098135412000816-main.pdf
1-s2.0-S095070511000167X-main.pdf