Distributed model predictive control using optimality condition decomposition and community detection

Segovia, P.; Puig, Vicenç; Duviella, E.; Etienne, Lucien

doi:10.1016/j.jprocont.2021.01.007

Cited by 21 publications

(16 citation statements)

References 48 publications

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“…However, as the number of reaches increase, the system becomes difficult to handle using a centralized approach. In this regard, future works could consider noncentralized approaches, given their flexibility and scalability [17]. On the other hand, a large amount of potential energy is lost during lock operations.…”

Section: Discussionmentioning

confidence: 99%

Hierarchical model predictive control and moving horizon estimation for open-channel systems with multiple time delays

Guekam

Segovia

Etienne

et al. 2021

2021 European Control Conference (ECC)

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This work presents the design of a hierarchical control and state estimation approach for the optimal water level management of open-channel systems using gates and pumping stations as actuators. Each reach may be characterized by a different time delay and a different prioritization of objectives. The design is divided in three layers: the upper layer determines the current operating mode. The intermediate layer is concerned with the design of appropriate controllers and observers to compute the references. Finally, the lower layer solves a scheduling problem to minimize the error between the references and the applied controls by discrete actuators. Simulation of a realistic case study based on part of the inland waterways in the north of France is used to demonstrate the effectiveness of the proposed approach.

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Section: Discussionmentioning

confidence: 99%

Hierarchical model predictive control and moving horizon estimation for open-channel systems with multiple time delays

Guekam

Segovia

Etienne

et al. 2021

2021 European Control Conference (ECC)

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“…The steps of the DMHE pre procedure are described in Algorithm 1. To get the one-step DMHE 1 pre procedure, it is sufficient to remove the step 10 and to use N i instead of N i .…”

Section: Dmhe Algorithmmentioning

confidence: 99%

“…The state of the system is represented by x = [p x p y v x v y ] which corresponds to the Cartesian coordinates of its position and velocity vectors. The dynamics of the target are described by model (1)…”

Section: Simulationsmentioning

confidence: 99%

“…Distributed algorithms have pervaded, in the last few years, many aspects of control engineering with applications for multi-robot systems, sensor networks, and others, covering topics such as control [1]- [4], state estimation [5]- [10], fault detection and mitigation [11], cyber-attack detection and mitigation on cyber-physical systems [12], [13], etc. Despite their different purposes, these topics share common characteristics as a consequence of the development in distributed schemes.…”

Section: Introductionmentioning

confidence: 99%

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A New ℓ-step Neighbourhood Distributed Moving Horizon Estimator

Venturino¹,

Bertrand²,

Maniu

et al. 2021

2021 60th IEEE Conference on Decision and Control (CDC)

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This paper focuses on Distributed State Estimation over a peer-to-peer sensor network composed by possible lowcomputational sensors. We propose a new -step Neighbourhood Distributed Moving Horizon Estimation technique with fused arrival cost and pre-estimation, improving the accuracy of the estimation, while reducing the computation time compared to other approaches from the literature. Simultaneously, convergence of the estimation error is improved by means of spreading the information amongst neighbourhoods, which comes natural in the sliding window data present in the Moving Horizon Estimation paradigm.

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“…Predictive control has received considerable attention due to its straightforward principle, rapid dynamic response, multivariable control, and immediate consideration of non-linear constraints, especially without PI controllers, modulation stage, hysteresis controllers, and look-up tables. In addition, predictive control has been widely applied in the industry due to its intuitiveness and versatility, as evidenced by the large number of industrial applications that has been reviewed [24].…”

Section: Introductionmentioning

confidence: 99%

Experimental Validation of Predictive Current Control for DFIG: FPGA Implementation

et al. 2021

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The purpose of this study is to design a real-time current predictive control for a wind energy conversion system (WECS) using a doubly-fed induction generator (DFIG). A wind emulator and a test bench for assessing control strategies were conceptualized. The DSPACE DS1104 board served as the foundation for the design of a wind emulation system. While power is indirectly regulated via currents, the latter is controlled directly by current predictive control. Using discrete time, the control suggests the appropriate voltages to the converter for each sample period to attain the specified set points and control the power. The field-oriented control is employed to ensure that the two components, axes d and q, are decoupled. The present predictive control was established to regulate a DFIG’s active and reactive capabilities. To begin, a thorough examination of the WECS is discussed. Following that, a comprehensive description of predictive control laws based on reference frame orientation is offered. As a result, a simulation was done using Matlab/Simulink environments to assess the performance and resilience of the proposed control model. The predictive current control was then experimentally validated on a test bench to demonstrate its efficacy. The observed results reveal an astonishing correlation between simulations and experiments.

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Distributed model predictive control using optimality condition decomposition and community detection

Cited by 21 publications

References 48 publications

Hierarchical model predictive control and moving horizon estimation for open-channel systems with multiple time delays

Hierarchical model predictive control and moving horizon estimation for open-channel systems with multiple time delays

A New ℓ-step Neighbourhood Distributed Moving Horizon Estimator

Experimental Validation of Predictive Current Control for DFIG: FPGA Implementation

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