2011
DOI: 10.3182/20110828-6-it-1002.02060
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Tuning predictive controllers with optimization: Application to GPC and FGPC

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Cited by 10 publications
(10 citation statements)
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“…On the other hand, in the case of FGPC one has to optimize only two parameters, and , and this automatically leads to nonconstant weighting sequences; recall that GPC and FGPC controllers share a common LTI expression, as was pointed out in Section 2 [49].) For this reason, we have tuned several GPC controllers with different constant weighting sequences and .…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…On the other hand, in the case of FGPC one has to optimize only two parameters, and , and this automatically leads to nonconstant weighting sequences; recall that GPC and FGPC controllers share a common LTI expression, as was pointed out in Section 2 [49].) For this reason, we have tuned several GPC controllers with different constant weighting sequences and .…”
Section: Resultsmentioning
confidence: 99%
“…A FGPC-tuning method was proposed in [49]. Based on optimization, the objective is the system to fulfil phase margin, sensitivity functions, and some other robustness specifications.…”
Section: Controller Formulationmentioning
confidence: 99%
“…This could be accomplished by trial and error or by optimization. (For applications of optimization methods to tune model predictive controllers see [9,32].) However, in this work, all system requirements will be expressed as constraints both for the throttle control and for the brake control.…”
Section: Control Constraints Implementationmentioning
confidence: 99%
“…Although the tuning of MPC or GPC in the closed loop is well explained in [4,5,7], still the tuning of predictive control for some given specifications with robustness is still a very challenging problem. Romero et al [11] developed a tuning rule for model-based predictive control for the desired gain margin and phase margin based on optimisation. This algorithm is analysed for both GPC and fractional-order GPC.…”
Section: Introductionmentioning
confidence: 99%
“…Romero et al . [11] developed a tuning rule for model‐based predictive control for the desired gain margin and phase margin based on optimisation. This algorithm is analysed for both GPC and fractional‐order GPC.…”
Section: Introductionmentioning
confidence: 99%