2014
DOI: 10.1016/j.conengprac.2013.09.007
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Improving performance and stability of MPC relevant identification methods

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Cited by 19 publications
(13 citation statements)
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“…In this sense, our program provides access to three MRI approaches: the method proposed by Gopaluni et al (2004), based on the direct optimization of the disturbance model and filter W k ; the algorithm proposed by Huang and Wang (1999), based on the prefiltering of the input/output signals; and the method proposed by Potts et al (2014) that gathers the advantages of the two previous methods and ensures the stability of the predictor. The method used to obtain the filter W k defines the characteristic of the different MRI methods.…”
Section: Model Predictive Controller Relevant Identification Methodsmentioning
confidence: 99%
“…In this sense, our program provides access to three MRI approaches: the method proposed by Gopaluni et al (2004), based on the direct optimization of the disturbance model and filter W k ; the algorithm proposed by Huang and Wang (1999), based on the prefiltering of the input/output signals; and the method proposed by Potts et al (2014) that gathers the advantages of the two previous methods and ensures the stability of the predictor. The method used to obtain the filter W k defines the characteristic of the different MRI methods.…”
Section: Model Predictive Controller Relevant Identification Methodsmentioning
confidence: 99%
“…Several approaches address the multi-step-ahead identification problem, see e.g. [15], [23], [26], [27], mainly in a stochastic framework. These approaches do not provide a way to quantify the model quality in terms of bounds on the simulation error, which could be directly exploited in robust decision making.…”
Section: Introductionmentioning
confidence: 99%
“…Early results using this approach require identification at every time step. In later contributions, , input excitation constraint is implemented based on a trigger, activated on poor model prediction. In a recent contribution, in order to avoid additional constraints in MPC, previous data was also used in reidentification step with recent data of the plant.…”
Section: Introductionmentioning
confidence: 99%