Real-Time Optimization of Periodic Systems: A Modifier-Adaptation Approach

Mirasierra, Victor; Vergara-Dietrich, José D.; Limón, Daniel

doi:10.1016/j.ifacol.2020.12.2238

Cited by 1 publication

(2 citation statements)

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“…The finite-horizon optimal control problem (FHOCP) typical of eMPC is modified similarly to the method in Equation (17). Defining the generic state and input sequences x := {χ 0 , χ 1 , .…”

Section: Economic Mpc With Modifiersmentioning

confidence: 99%

“…This represents a major challenge, especially when dealing with noisy measurements. Even the most recent MA investigations, which strive for feasibility improvement [15], faster convergence [16], applicability to periodic systems [17], or large-scale systems [18], are still based on the assumption that the plant gradients are perfectly known. Nevertheless, several approaches for estimating plant gradients have been proposed, as detailed next.…”

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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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: Economic Mpc With Modifiersmentioning

confidence: 99%