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Distributed model predictive control for irrigation canals
 Networks and Heterogeneous Media
, 2009
"... Distributed model predictive control of irrigation canals ∗ ..."
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Cited by 34 (22 self)
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Distributed model predictive control of irrigation canals ∗
Decentralized model predictive control of drinking water networks using an automatic subsystem decomposition approach,”
 in Proceedings of the 12th LSS Symposium on LargeScale Systems: Theory and Applications, Villeneuve d’Ascq
, 2010
"... AbstractIn this paper, a decentralized model predictive control (DMPC) strategy for drinking water networks (DWN) is proposed. The DWN is partitioned in a set of subnetworks using a partitioning algorithm that makes use of the topology of the network, the information about the actuator usage and h ..."
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Cited by 19 (13 self)
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AbstractIn this paper, a decentralized model predictive control (DMPC) strategy for drinking water networks (DWN) is proposed. The DWN is partitioned in a set of subnetworks using a partitioning algorithm that makes use of the topology of the network, the information about the actuator usage and heuristics. A suboptimal DMPC strategy was derived that allows the hierarchical solution of the set of MPC controllers used to control each partition. A comparative study between the centralized MPC (CMPC) and DMPC approaches is developed on the case study, which consists in an aggregate version of the Barcelona DWN. Results have shown the effectiveness of the proposed DMPC approach in terms of the computation time while an admissible level of suboptimality is obtained in all the considered scenarios.
Partitioning approach oriented to the decentralised predictive control of largescale systems
 Journal of Process Control
"... In this paper, a partitioning approach for largescale systems based on graphtheory is presented. The algorithm starts with the translation of the system model into a graph representation. Once the system graph is obtained, the problem of graph partitioning is then solved. The resultant partition c ..."
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Cited by 16 (12 self)
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In this paper, a partitioning approach for largescale systems based on graphtheory is presented. The algorithm starts with the translation of the system model into a graph representation. Once the system graph is obtained, the problem of graph partitioning is then solved. The resultant partition consists in a set of nonoverlapping subgraphs whose number of vertices is as similar as possible and the number of interconnecting edges between them is minimal. To achieve this goal, the proposed algorithm applies a set of procedures based on identifying the highlyconnected subgraphs with balanced number of internal and external connections. In order to illustrate the use and application of the proposed partitioning approach, it is used to decompose a dynamical model of the Barcelona drinking water network (DWN). Moreover, a hierarchicallike DMPC strategy is designed and applied over the resultant set of partitions in order to assess the closedloop performance. Results obtained when used several simulation scenarios show the effectiveness of both the partitioning approach and the DMPC strategy in terms of the reduced computational burden and, at the same time, of the admissible loss of performance in contrast to a centralised MPC strategy.
Distributed control applied to combined electricity and natural gas infrastructures
 in Proceedings of the International Conference on Infrastructure Systems
, 2008
"... Abstract — The optimization of combined electricity and natural gas systems is addressed in this paper. The two networks are connected via energy hubs. Using the energy hub concept, the interactions between the different infrastructures can be analyzed. A system consisting of several interconnected ..."
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Cited by 6 (4 self)
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Abstract — The optimization of combined electricity and natural gas systems is addressed in this paper. The two networks are connected via energy hubs. Using the energy hub concept, the interactions between the different infrastructures can be analyzed. A system consisting of several interconnected hubs forms a distributed power generation structure where each hub is controlled by its respective control agent. Recently, a distributed control method has been applied to such a system. The overall optimization problem including the entire system is decomposed into subproblems according to the control agents. In this paper, a parallel and serial version of that method is discussed. Simulation results are obtained through experiments on a threehub benchmark system. I.
Coordinated control of FACTS devices in power systems for security enhancement
 in Proc. 2007 iREP Symposium—Bulk Power System Dynamics and Control—VII, Revitalizing Operational Reliability
, 2007
"... Abstract — FACTS devices provide the possibility to control voltages and power flows in a power system and therefore to improve the security of the system. In order to make use of this possibility, the set values of the FACTS controllers have to be chosen appropriately. A valuable option is the appl ..."
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Cited by 5 (1 self)
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Abstract — FACTS devices provide the possibility to control voltages and power flows in a power system and therefore to improve the security of the system. In order to make use of this possibility, the set values of the FACTS controllers have to be chosen appropriately. A valuable option is the application of Optimal Power Flow control, where the set values are determined such that an objective function is minimized given the model of the system. But due to the large size of power systems, it is often difficult for different reasons to include the entire system into the optimization process. In this paper, sensitivity analysis is used to determine the area on which the FACTS device has considerable influence and then only this limited area is included in the Optimal Power Flow control. If there are several devices placed in the same system, the areas assigned to these devices might overlap indicating mutual influences. Therefore, a coordination of the control entities is needed in order to avoid conflicting behavior of the devices rising the issue of MultiArea Control. Here, the method based on Approximate Newton Directions is extended for the case of overlapping areas which are determined by sensitivity analysis. I.
Multiagent Model Predictive Control of Signaling Split in Urban Traffic Networks ∗ ABSTRACT
"... Urban traffic networks are large, dynamic systems which remain a challenge in control engineering despite all of the scientific and technological progress. The sheer size, wide spread of sensors and control devices, and nonlinearities make such systems complex, beyond the scope of existing models, l ..."
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Cited by 4 (0 self)
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Urban traffic networks are large, dynamic systems which remain a challenge in control engineering despite all of the scientific and technological progress. The sheer size, wide spread of sensors and control devices, and nonlinearities make such systems complex, beyond the scope of existing models, let alone control algorithms. To this end, control engineers have looked for unconventional means for modeling and control, in particular the technology of multiagent systems whose appeal stems from their composite nature, flexibility, and scalability. This paper contributes to this evolving technology by proposing a framework for multiagent control of linear, dynamic systems. The framework decomposes a centralized model predictive control problem into a network of coupled, but small subproblems that are iteratively solved by the distributed agents. Theoretical results ensure convergence of the distributed iterations to a globally optimal solution. The framework is applied to the signaling split control of traffic networks. Experiments conducted with simulation software indicate that the multiagent framework attains performance comparable to conventional control, such as the trafficresponsive urban control strategy.
Intelligence in Transportation Infrastructures via ModelBased Predictive Control
"... via modelbased predictive control ..."
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006.html Multiarea control of overlapping areas in power systems for FACTS control
"... Abstract—As power systems generally are large interconnected systems controlled by several parties, centralized optimal power flow (OPF) control taking the entire grid into account is often not feasible. To use optimal control in power systems nevertheless, the overall system is decomposed into area ..."
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Cited by 3 (2 self)
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Abstract—As power systems generally are large interconnected systems controlled by several parties, centralized optimal power flow (OPF) control taking the entire grid into account is often not feasible. To use optimal control in power systems nevertheless, the overall system is decomposed into areas with associated subproblems, which are solved in an iterative way. Currently available decomposition techniques assume that the models and control objectives of areas are formulated to be nonoverlapping, i.e., the border of one area is at the same time also the border of a neighboring area. However, when the areas are determined independently from each other, e.g., by sensitivity analysis, the areas can be overlapping, making currently existing techniques not directly applicable. In this paper, we extend one of these techniques, viz. a modified Lagrange decomposition method, to the case of overlapping areas. Simulations are carried out on an adjusted IEEE 57bus system in which the controlled entities are FACTS devices and the objective is to improve system security. I.
Almost decentralized lyapunovbased nonlinear model predictive control
 in Proceedings of the 2010 American Control Conference
, 2010
"... AbstractThis paper proposes an almost decentralized solution to the problem of stabilizing a network of discretetime nonlinear systems with coupled dynamics that are subject to local state/input constraints. By "almost decentralized" we mean that each local controller is allowed to use t ..."
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AbstractThis paper proposes an almost decentralized solution to the problem of stabilizing a network of discretetime nonlinear systems with coupled dynamics that are subject to local state/input constraints. By "almost decentralized" we mean that each local controller is allowed to use the states of neighboring systems for feedback, whereas it is not permitted to employ iterations between the systems in the network to compute the control action. The controller synthesis method used in this work is Lyapunovbased model predictive control (MPC). The stabilization conditions are decentralized via a set of structured control Lyapunov functions (CLFs) for which the maximum over all the functions in the set is a CLF for the global network of systems. However, this does not necessarily imply that each function is a CLF for its corresponding subsystem. Additionally, we provide a solution for relaxing the temporal monotonicity of the CLF for the overall network. For structured CLFs defined using the infinity norm, we show that the decentralized MPC algorithm can be implemented by solving a single linear program in each network node. A nontrivial example illustrates the effectiveness of the developed theory and shows that the proposed method can perform as well as more complex distributed, iterationbased MPC algorithms.