Estimation technique for offset-free economic MPC based on modifier adaptation

Vaccari, Marco; Pelagagge, Federico; Bonvin, Dominique; Pannocchia, Gabriele

doi:10.1016/j.ifacol.2020.12.357

Cited by 5 publications

(6 citation statements)

References 15 publications

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“…where p P , p E , p A , and p B are the molar prices of products and reactants. The plant parameters can be found in [32] and in Table 1. The model used for control design comprises only two reactions:…”

Section: Processmentioning

confidence: 99%

“…This work represents an extension to [32], but it also goes further by comparing several gradient-estimation techniques. This is important to steer future research on how MA can best be combined with eMPC.…”

Section: Introductionmentioning

confidence: 99%

“…The number of data points in the regression is also n s = 4. Note that, in the presence of plant-model mismatch, the use of the disturbance model (51) by itself is not sufficient to eliminate offset, as reaching plant optimality requires perfect knowledge of plant gradients [25,32]. When not otherwise specified, M = 15 is chosen for all controllers.…”

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confidence: 99%

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Offset-Free Economic MPC Based on Modifier Adaptation: Investigation of Several Gradient-Estimation Techniques

et al. 2021

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Various offset-free economic model predictive control schemes that include a disturbance model and the modifier-adaptation principle have been proposed in recent years. These schemes are able to reach plant optimality asymptotically even in the presence of plant–model mismatch. All schemes are affected by a major issue that is common to all modifier-adaptation formulations, namely, plant optimality (note that convergence per se does not require perfect plant gradients) requires perfect knowledge of static plant gradients, which is a piece of information not known in most practical applications. To address this issue, we present two gradient-estimation techniques, one based on Broyden’s update and the other one on linear regression. We apply these techniques for the estimation of either the plant gradients or the modifiers directly. The resulting economic MPC schemes are tested in a simulation and compared on two benchmark examples of different complexity with respect to both convergence speed and robustness to measurement noise.

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Section: Processmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Offset-Free Economic MPC Based on Modifier Adaptation: Investigation of Several Gradient-Estimation Techniques

et al. 2021

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“…In their work, the gradients were considered known. Recently, Vaccari et al (2020) presented a technique for direct estimation of the modifiers using steady-state perturbations and a Broyden update algorithm. After that, Oliveira-Silva et al (2021) presented a dynamic optimizer with MA (DOMA) and an algorithm to estimate directly the modifiers, avoiding the estimation of the process gradients, using transient information, the Dynamic Modifier Estimation (DME).…”

Section: Introductionmentioning

confidence: 99%

“…DME uses an optimization algorithm executed on-line to make the estimated modifiers converge to the ones in steady state required by MA. More recently, Vaccari et al (2021) presented a extension of Vaccari et al (2020) to compare two techniques to estimate either plant gradients or modifiers using steady-state measurements via Broyden's update and linear regression. The eMPC schemes were tested in simulation in two benchmark examples, stressing the fact that the use of transient measurements to estimate the process gradients can be an interesting approach to speed up convergence.…”

Section: Introductionmentioning

confidence: 99%