Real-Time Application of a Multivariable Generalized State-Space Receding Horizon Control Algorithm

Gambier, Adrián; Unbehauen, H.

doi:10.1016/s1474-6670(17)58798-4

Cited by 2 publications

(3 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the control performed in a first stage in a nonadaptive scheme with a Kalman filter as state and disturbance estimator (see [8]). The identification run in stand-by form.…”

Section: Resultsmentioning

confidence: 99%

“…A generalized receding horizon control based on a statespace model was proposed in [8] and the results of the realtime implementation applied to a turbo-generator pilot plant were also presented. The here presented contribution is an extension of [8] to a new adaptive approach on the basis of an extended bootstrap algorithm for joint estimation of parameters, states and constant disturbances.…”

Section: Introductionmentioning

confidence: 99%

“…The here presented contribution is an extension of [8] to a new adaptive approach on the basis of an extended bootstrap algorithm for joint estimation of parameters, states and constant disturbances.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive multivariable state-space receding horizon control of a turbo-generator pilot plant

Gambier

Unbehauen²

Proceedings of 35th IEEE Conference on Decision and Control

Self Cite

View full text Add to dashboard Cite

The real-time results of an adaptive multivariable generalized state-space receding horizon control, applied to a turbo-generator pilot plant, are reported in this paper. The control algorithm consists of a state-space receding horizon tracking system, a constant-disturbances compensator and a parameters, state and constant-disturbances estimator based on an augmented bootstrap algorithm. The turbo-generator consisting of a turbine and a synchronous generator exhibits nonlinear and nonminimum phase behaviour in a stochastic environment.

show abstract

“…However, the control performed in a first stage in a nonadaptive scheme with a Kalman filter as state and disturbance estimator (see [8]). The identification run in stand-by form.…”

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%