Integrating dynamic economic optimization and model predictive control for optimal operation of nonlinear process systems

Ellis, Matthew J.; Christofides, Panagiotis D.

doi:10.1016/j.conengprac.2013.02.016

Cited by 100 publications

(54 citation statements)

References 30 publications

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“…This decrease in Subindex (1) indicates non-periodic behaviour enforced while (2) indicates that the periodic constraint is enforced. (2) , the terminal constraint is set up in relation to a pre-calculated optimal cycle obtained from (6). In the HEMPC (2) , the reference trajectory is computed by the upper layer every 24h.…”

Section: B Resultsmentioning

confidence: 99%

“…The prediction horizons should be selected such that H s p ≥ H p . Remark 1: Controllers (10) and (11) are not enforcing convergence to the precomputed optimal trajectory obtained in (6). Instead, they are meant to retain feasibility under possible changes of the economic parameters in the cost function and to find new optimal trajectories for the current conditions.…”

Section: Empc For Dwns With Changing Operating Patternsmentioning

confidence: 99%

“…i.e., δ x k 2 with δ ∈ R + and sufficiently small, is a convex regularisation term added to enforce the uniqueness of the solution to (6) given that the cost function (5) is originally not convex with respect to x. Defining the weighting matrices W s and W ∆u in (4) to be positive definite, thenṼ k (x k , u k ) is bounded and strictly convex by design with respect to (x, u, ξ).…”

Section: B System Management Criteriamentioning

confidence: 99%

“…Nevertheless, as discussed in [7], model inconsistencies, setpoint changes, time-varying parameters, disturbances, and time-scale differences may lead the system to unreachable set-points, suboptimal economic performance and feasibility loss. In order to tackle some of the main drawbacks of the typical hierarchical scheme and take more economic profit from the transitory behaviour of the system, some authors have proposed to integrate the economic optimisation within the MPC using either a two-layer approach, see, e.g., [6], [19], or a single-layer approach, i.e., the so called economic MPC (EMPC) [15]. It has been shown in the aforementioned references that closed-loop stability and/or average asymptotic performance can be guaranteed under some form of dissipativity, duality or convexity assumptions.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Economic MPC for the management of drinking water networks

Grosso

Ocampo‐Martínez

Puig

et al. 2014

2014 European Control Conference (ECC)

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Abstract-This paper addresses the management of drinking water networks (DWNs) regarding a multi-objective cost function by means of economically-oriented model predictive control (EMPC) strategies. Specifically, assuming the water demand and the energy price as periodically time-varying signals, this paper shows that the EMPC framework is flexible to enhance the control of DWNs without relying on hierarchical control schemes that require the use of real-time optimisers (RTO) or steady-state target optimisers (SSTO) in an upper layer. Four different MPC strategies are discussed in this paper: a hierarchical two-layer approach, a standard EMPC where the multi-objective cost function is optimised directly, and two different modifications of the latter, which are meant to overcome possible feasibility losses in the presence of changing operating patterns. The discussed schemes are tested and compared by means of a case study taken from a part of the Barcelona DWN.

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Section: B Resultsmentioning

confidence: 99%

Section: Empc For Dwns With Changing Operating Patternsmentioning

confidence: 99%

Section: B System Management Criteriamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Economic MPC for the management of drinking water networks

Grosso

Ocampo‐Martínez

Puig

et al. 2014

2014 European Control Conference (ECC)

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“…The stability and cost improvement of EMPC have been investigated for non-linear processes in [3,4], where Lyapunov-based 30 technique has been employed over the conventional MPC. In order to reduce the computational complexity, the general EMPC is divided into two layers [5], where EMPC is set in the upper layer and a lower feedback control layer is used.…”

mentioning

confidence: 99%

Non-linear economic model predictive control of water distribution networks

Wang

Puig

Cembraño

2017

Journal of Process Control

101

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This paper addresses a non-linear economic model predictive control (EMPC) strategy for water distribution networks (WDNs). A WDN could be considered as a non-linear system described by differential-algebraic equations (DAEs) when flow and hydraulic head equations are considered. As in other process industries, the main operational goal of WDNs is the minimisation of the economic costs associated to pumping and water treatment, while guaranteeing water supply with required flows and pressures at all the control/demand nodes in the network. Other operational goals related to safety and reliability are usually sought. From a control point of view, EMPC is a suitable control strategy for WDNs since the optimal operation of the network can not be established a priori by fixing reference volumes in the tanks. Alternatively, the EMPC strategy should determine the optimal filling/emptying sequence of the tanks taking into account that electricity price varies between day and night and that the demand also follows a 24-hour repetitive pattern. On the other hand, as a result of the ON/OFF operation of parallel pumps in pumping stations, a two-layer control scheme has been used: a non-linear EMPC strategy with hourly control interval is chosen in the upper layer and a pump scheduling approach with one-minute sampling time in the lower layer. Finally, closed-loop simulation results of applying the proposed control strategy to the D-Town water network are shown.

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Economic model predictive control with time‐varying objective function for nonlinear process systems

Ellis¹,

Christofides²

2013

AIChE Journal

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Economic model predictive control (EMPC) is a control scheme that combines real-time dynamic economic process optimization with the feedback properties of model predictive control (MPC) by replacing the quadratic cost function with a general economic cost function. Almost all the recent work on EMPC involves cost functions that are time invariant (do not explicitly account for time-varying process economics). In the present work, we focus on the development of a Lyapunov-based EMPC (LEMPC) scheme that is formulated with an explicitly time-varying economic cost function. First, the formulation of the proposed two-mode LEMPC is given. Second, closed-loop stability is proven through a theoretical treatment. Last, we demonstrate through extensive closed-loop simulations of a chemical process that the proposed LEMPC can achieve stability with time-varying economic cost as well as improve economic performance of the process over a conventional MPC scheme.

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Integrating dynamic economic optimization and model predictive control for optimal operation of nonlinear process systems

Cited by 100 publications

References 30 publications

Economic MPC for the management of drinking water networks

Economic MPC for the management of drinking water networks

Non-linear economic model predictive control of water distribution networks

Economic model predictive control with time‐varying objective function for nonlinear process systems

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