Hierarchical decompositions for MPC of resource constrained control systems: applications to building energy management

This paper presents a bilevel decomposition approach to a model predictive control of resource constrained dynamic systems. The proposed approach yields a distributed solution that converges to the same optimum that would be obtained by a centralized controller. It is also showed that this decomposition enables the use of multi-core or distributed architectures. Computational analyses of experiments of synthetics problems are reported and discussed, showing the capacity of the bilevel approach in combination with parallel computation.

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“…In order to present a more convenient form for bilevel optimization, as in (Camponogara et al, 2018), problem P is recast as follows,…”

Section: Bilevel Decompositionmentioning

confidence: 99%

“…This work adopts an approach where the master problem optimizes over the decision space of resource allocations ss, followed by the optimization of the lower-level subproblems and the computation of sensitivities ∂f m /∂ss to compute the improving directions for the upper-level algorithm (Camponogara et al, 2018).…”

Section: Bilevel Decompositionmentioning

confidence: 99%

A Computational Analysis of a Bilevel Decomposition for MPC of Resource Constrained Dynamic Systems

Silva

Brinhosa

Camponogara

et al. 2019

Anais Do 14º Simpósio Brasileiro De Automação Inteligente

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“…In [12], the authors presented a hierarchical decomposition approach for MPC of dynamic systems using Bilevel, Lagrangean, and Benders decompositions. The authors reported results from a numerical analysis of the decompositions and a simulated application to the energy management of a building, in which a limited source of chilled water is distributed among HVAC units.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, the main benefit of a hierarchical decomposition is not computational but rather organizational as it facilitates the expansion and reconfiguration of the control system. This feature stems from the simple coordination scheme and reduced information communication [12]. In addition, it has already been shown in the literature that, by employing hierarchical decompositions, a reduction in computational time can be achieved by parallel computation, but not linearly as the number of cores increases [13].…”

Section: Introductionmentioning

confidence: 99%

“…These two decomposition strategies can be used to model activation variables, i.e., binary variables, to enable or disable the input of control signals into the system if necessary. In this sense, we extend the formulation previously presented in [12] (which only considered continuous variables) to include activation variables (binary)-which are able to individually define which subsystems are on or off-using Benders Decomposition and Outer Approximation.…”

Section: Introductionmentioning

confidence: 99%

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Decompositions for MPC of Linear Dynamic Systems with Activation Constraints

et al. 2020

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The interconnection of dynamic subsystems that share limited resources are found in many applications, and the control of such systems of subsystems has fueled significant attention from scientists and engineers. For the operation of such systems, model predictive control (MPC) has become a popular technique, arguably for its ability to deal with complex dynamics and system constraints. The MPC algorithms found in the literature are mostly centralized, with a single controller receiving the signals and performing the computations of output signals. However, the distributed structure of such interconnected subsystems is not necessarily explored by standard MPC. To this end, this work proposes hierarchical decomposition to split the computations between a master problem (centralized component) and a set of decoupled subproblems (distributed components) with activation constraints, which brings about organizational flexibility and distributed computation. Two general methods are considered for hierarchical control and optimization, namely Benders decomposition and outer approximation. Results are reported from a numerical analysis of the decompositions and a simulated application to energy management, in which a limited source of energy is distributed among batteries of electric vehicles.

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Event-driven online decoupling control mechanism for the variable flow rate HVAC system based on the medium response properties

Wang

Zhao

2022

Building and Environment

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Hierarchical decompositions for MPC of resource constrained control systems: applications to building energy management

Cited by 11 publications

References 29 publications

A Computational Analysis of a Bilevel Decomposition for MPC of Resource Constrained Dynamic Systems

A Computational Analysis of a Bilevel Decomposition for MPC of Resource Constrained Dynamic Systems

Decompositions for MPC of Linear Dynamic Systems with Activation Constraints

Event-driven online decoupling control mechanism for the variable flow rate HVAC system based on the medium response properties

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