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Dive into the research topics where Anna Sadowska is active.

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Featured researches published by Anna Sadowska.


Water Resources Management | 2014

Hierarchical Operation of Water Level Controllers: Formal Analysis and Application on a Large Scale Irrigation Canal

Anna Sadowska; P. J. van Overloop; Charles M. Burt; B. De Schutter

We introduce a hierachical controller, the purpose of which is to speed up the water delivery process as compared to the standard method applied currently in the field. The lower layer of the hierarchical control consists of local proportional integral filter controllers (PIF controllers) for upstream control at each gate; specifically they are proportional integral controllers with a low-pass filter. In contrast, the higher layer is composed of a centralized model-based predictive controller, which acts by controlling the head gate and by coordinating the local PIF controllers by modifying their setpoints when needed. The centralized controller is event-driven and is invoked only when there is a need for it (a water delivery request) and as such it contributes scarcely to the communication burden. The scheme is robust to temporary communication losses as the local PIF controllers are fully able to control the canal in their normal independent automatic upstream control mode until the communication links are restored. We discuss the application of the hierarchical controller to a precise numerical model of the Central California Irrigation District Main Canal. This shows the improved performance of the new hierarchical controller over the standard control method.


IEEE Transactions on Control Systems and Technology | 2015

Delivery-Oriented Hierarchical Predictive Control of an Irrigation Canal: Event-Driven Versus Time-Driven Approaches

Anna Sadowska; Bart De Schutter; Peter-Jules van Overloop

In this paper, we present the concept of a hierarchical predictive controller used for irrigation canals. The motivation behind this paper is the need in the field of irrigation to deliver water to farmers fast, but with minimal resources involved, as the communication links in the field are not dependable in practice. In response to such a control problem, we propose a hierarchical controller: the lower control layer is formed by decentralized proportional integral (PI) controllers and the higher control layer is constituted by a centralized predictive controller, the purpose of which is to control the inflow to the canal and, importantly, to coordinate the local controllers by modifying their setpoints. Having in mind the restrictions on the available communication infrastructure and the control equipment already present, the scheme is designed to be event driven, i.e., activated when there are either delivery requests or non-delivery-related events of any sort, requiring special care on top of the control provided by the PI controllers. We also study a time-driven formulation with an additional postprocessing step to avoid excessive negligible setpoint modifications. We compare the event-driven formulation and the time-driven formulation theoretically as well as by means of a simulation study for the West-M irrigation canal in Phoenix, Arizona, illustrating the findings of this paper. It is shown that the event-driven controller is able to provide a good balance between the control performance and the required update frequency of the control settings.


IEEE Control Systems Magazine | 2015

Human-in-the-Loop Model Predictive Control of an Irrigation Canal [Applications of Control]

P. J. van Overloop; J. M. Maestre; Anna Sadowska; Eduardo F. Camacho; Bart De Schutter

Until now, advanced model-based control techniques have been predominantly employed to control problems that are relatively straightforward to model. Many systems with complex dynamics or containing sophisticated sensing and actuation elements can be controlled if the corresponding mathematical models are available, even if there is uncertainty in this information. Consequently, the application of model-based control strategies has flourished in numerous areas, including industrial applications [1]-[3].


conference on decision and control | 2014

Human in the loop model Predictive Control: an irrigation canal case study

J. M. Maestre; P. J. van Overloop; M. Hashemy; Anna Sadowska; Eduardo F. Camacho

In this work, we propose to expand the application of model predictive control (MPC) to problems in which there are human agents involved in the sensing and actuation processes. To this end, a new configuration of a control system structure that combines centralized predictive control and local operations is presented. Additional constraints are included in the optimization problem to take into account the mobility and the role of the operators over the prediction horizon. This new type of control system structure, referred to as Mobile Model Predictive Control (MoMPC), is tested on a linear model of a large scale irrigation canal and its performance is compared to centralized MPC and manual operation.


european control conference | 2013

Formation control design for car-like nonholonomic robots using the backstepping approach

Anna Sadowska; H.J.C. Huijberts

In this paper we study the formation control problem for car-like robots which may be viewed as a more general type of robots than the usually considered unicycle type robots. We develop a controller using the backstepping approach and give conditions solving the formation control problem as well as the coordination control problem. We also present simulation results to demonstrate the applicability of the proposed controller.


international conference on intelligent transportation systems | 2014

Tractable robust predictive control approaches for freeway networks

Shuai Liu; José Ramón Domínguez Frejo; Alfredo Núñez; Bart De Schutter; Anna Sadowska; Hans Hellendoorn; Eduardo F. Camacho

Robust control aims to maintain predefined performance specifications for a wide range of uncertainties. In this paper, we consider the robust control problem for freeway networks, including the uncertainties explicitly in the control design step. We use min-max scheme for handling the uncertainties occurring in freeway networks. In order to reduce the computational complexity of min-max scheme, we propose scenario-based min-max Model Predictive Control (MPC) and scenario-based Receding-Horizon Parametrized Control (RHPC) in this paper, which solve the complete robust problem approximately. In addition, a new objective function is proposed to ensure the satisfaction of queue length constraints. A case study is implemented to assess the effectiveness of the proposed approaches. The results show that nominal MPC and nominal RHPC may result in a better performance than scenario-based min-max MPC and scenario-based min-max RHPC. However, nominal MPC and nominal RHPC cannot ensure the satisfaction of the queue length constraint. By applying scenario-based min-max MPC and scenario-based min-max RHPC, the queue length constraint is satisfied conservatively at the cost of an increase in the performance index.


Archive | 2015

Hierarchical MPC-Based Control of an Irrigation Canal

Anna Sadowska; P. J. van Overloop; Charles M. Burt; B. De Schutter

We discuss the problem of controlling an irrigation canal to accommodate fast changes in the canal state in response to events such as offtakes announced with no time lag or sudden weather changes. Our proposed approach comprises a hierarchical controller consisting of two layers with decentralized PI controllers in the lower layer and a centralized MPC-based event-driven controller in the higher layer. By incorporating the hierarchical controller structure we achieve a better performance than with the PI controllers only as currently in use in the real world, while barely increasing the communication requirements and remaining robust to temporary communication link breakdowns as the lower layer can work independently of the higher layer when the links are being restored. The operation of the higher-layer controller relies on controlling the head gate and modifying the settings of the local controllers. This way, an acceleration of water transporting is attained as the controller allows for rapid reactions to the need for more water or less water at a location. Specifically, when there is a sudden need for water, the storage in some of the pools is used to temporarily borrow water. Alternatively, when there is too much water at a location, it can be stored for some time in upstream or downstream pools before the PI controllers manage to remove the water.


international conference on intelligent transportation systems | 2016

Scenario-based Distributed Model Predictive Control for freeway networks

Shuai Liu; Anna Sadowska; Hans Hellendoorn; Bart De Schutter

In this paper we develop a scenario-based Distributed Model Predictive Control (DMPC) approach for large-scale freeway networks. The uncertainties in a large-scale freeway network are categorized into global uncertainties for the overall network and local uncertainties for subnetworks. A reduced scenario tree is proposed, consisting of global scenarios and a reduced local scenario tree. For handling uncertainties in the scenario-based DMPC problem, a min-max setting is considered. A case study is implemented for investigating the scenario-based DMPC approach, and the results show that in the presence of uncertainties it is effective in improving the control performance with the queue length constraint being satisfied.


european control conference | 2015

Human-in-the-loop control of an irrigation canal using time instant optimization Model Predictive Control

Anna Sadowska; P. J. van Overloop; J. M. Maestre; B. De Schutter

In the paper we discuss the recently introduced Mobile Model Predictive Control (Mobile MPC) approach for an irrigation canal. Mobile MPC is a configuration of MPC that explicitly incorporates the role of the human operator traveling between the gates as ordered by a remote centralized controller. The operator provides the controller with up-to-date measurements from the locations visited and acts as the actuator as required by the remote controller. Mobile MPC provides a solution in between fully manual and fully automatic canal operation, as the first one may give poor performance and the second one might be impracticable in some situations, where it is not possible to rely on the equipment installed in the field. In the current paper we improve the performance of the original Mobile MPC approach by allowing the controller to decide the exact time instants when the operator should arrive at a specific gate and change the gates settings as well as we include a penalty in the objective function for the controller to minimize the workload of the human operator. We show that the new approach yields enhanced performance in comparison to the previous method, and we demonstrate the benefits of the new method as opposed to the previous one in a case study.


european control conference | 2014

Hierarchical control of irrigation canals in the presence of disturbances: Framework and comparison

Anna Sadowska; Bart De Schutter; Peter-Jules van Overloop

We study a control problem of delivering water to farmers through an irrigation canal and introduce a hierarchical controller with a Coordinator that by employing Model Predictive Control principles coordinates local canal reaches by modifying setpoints only when it is needed. Once the setpoints are set, the Coordinator does not interfere with the functioning of the local sites and the canal is fully controlled by local PI controllers located at each gate. Therefore the communication between the centralized controller and the local sites is kept minimal, which is motivated by the communication restrictions that are present in the field of irrigation. We consider three predictive control designs, namely a nominal controller, and two robust designs: a constraint tightening controller adapted to fit our application and a min-max controller. We present a numerical example to compare the performance obtained by the three controllers. It is found that for the given case study with a small disturbance realization, the nominal controller performs better than the robust controllers, the behaviors of which prove overly conservative.

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Bart De Schutter

Delft University of Technology

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P. J. van Overloop

Delft University of Technology

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B. De Schutter

Delft University of Technology

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Hans Hellendoorn

Delft University of Technology

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Shuai Liu

Delft University of Technology

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Alfredo Núñez

Delft University of Technology

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Charles M. Burt

California Polytechnic State University

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