Vicenç Puig

Optimal control of urban drainage systems. A case study

This paper deals with the use of optimal control techniques in urban drainage systems containing gates and detention tanks as well as a telemetry/telecontrol system. Optimal control is used to provide control strategies which contribute to reducing the events of flooding and polluting discharges to the environment. The case of the Barcelona system is presented.

Application of predictive control strategies to the management of complex networks in the urban water cycle [Applications of Control]

The management of the urban water cycle (UWC) is a subject of increasing interest because of its social, economic, and environmental impact. The most important issues include the sustainable use of limited resources and the reliability of service to consumers with adequate quality and pressure levels, as well as the urban drainage management to prevent flooding and polluting discharges to the environment.

Fault diagnosis and fault tolerant control using set-membership approaches: Application to real case studies

Fault diagnosis and fault tolerant control using set-membership approaches: Application to real case studies This paper reviews the use of set-membership methods in fault diagnosis (FD) and fault tolerant control (FTC). Setmembership methods use a deterministic unknown-but-bounded description of noise and parametric uncertainty (interval models). These methods aims at checking the consistency between observed and predicted behaviour by using simple sets to approximate the exact set of possible behaviour (in the parameter or the state space). When an inconsistency is detected between the measured and predicted behaviours obtained using a faultless system model, a fault can be indicated. Otherwise, nothing can be stated. The same principle can be used to identify interval models for fault detection and to develop methods for fault tolerance evaluation. Finally, some real applications will be used to illustrate the usefulness and performance of set-membership methods for FD and FTC.

Fault-tolerant control strategy for actuator faults using LPV techniques

Fault-tolerant control strategy for actuator faults using LPV techniques: Application to a two degree of freedom helicopter In this paper, a Fault Tolerant Control (FTC) strategy for Linear Parameter Varying (LPV) systems that can be used in the case of actuator faults is proposed. The idea of this FTC method is to adapt the faulty plant instead of adapting the controller to the faulty plant. This approach can be seen as a kind of virtual actuator. An integrated FTC design procedure for the fault identification and fault-tolerant control schemes using LPV techniques is provided as well. Fault identification is based on the use of an Unknown Input Observer (UIO). The FTC controller is implemented as a state feedback controller and designed using polytopic LPV techniques and Linear Matrix Inequality (LMI) regions in such a way as to guarantee the closed-loop behavior in terms of several LMI constraints. To assess the performance of the proposed approach, a two degree of freedom helicopter is used.

Passive Robust Fault Detection of Dynamic Processes Using Interval Models

Model-based fault detection relies on the use of a model to check the consistency between the predicted and the measured (or observed) behavior of a system. However, there is always some mismatch between the modeled and the real process behavior. Then, any model-based fault detection algorithm should be robust against modeling errors. One possible approach to take into account modeling uncertainty is to include all the uncertainty in system parameters using an interval model that allows generating an adaptive threshold. In this paper, the use of interval models in robust fault detection considering three schemes (simulation, prediction, or observation) is presented and discussed. The main contribution is to present a comparative study that allows identifying the benefits and drawbacks of using each scheme. This study will provide a guideline for the use of the proposed fault detection schemes in real applications. Finally, an intelligent servoactuator, proposed as a benchmark in the context of European Research Training Network DAMADICS, is used to illustrate the application and the comparative study of these interval-based fault detection schemes.

PASSIVE ROBUST FAULT DETECTION APPROACHES USING INTERVAL MODELS

Abstract The problem of robustness in fault detection has been treated basically using two kinds of approaches: actives and passives. Most of the literature in robust fault detection is focused on the problem of active approach based on decoupling the effects of the uncertainty from the effects of the faults on the residual. On the other hand, the passive approach is based of propagating the effect of the uncertainty on the residuals and then using adaptive thresholds. In this paper, the passive approach based on adaptive thresholds produced using a model with uncertain parameters bounded in intervals, also known as an “ interval model ”, will be presented in the context of parity equations and observers methodologies, deriving their corresponding interval versions. Finally, an example based on an industrial actuator used as a FDI benchmark in the European project DAMADICS will be used for testing and comparing the proposed approaches.

Predictive optimal control of sewer networks using CORAL tool: application to Riera Blanca catchment in Barcelona

This paper deals with the global control of the Riera Blanca catchment in the Barcelona sewer network using a predictive optimal control approach. This catchment has been modelled using a conceptual modelling approach based on decomposing the catchments in subcatchments and representing them as virtual tanks. This conceptual modelling approach allows real-time model calibration and control of the sewer network. The global control problem of the Riera Blanca catchment is solved using a optimal/predictive control algorithm. To implement the predictive optimal control of the Riera Blanca catchment, a software tool named CORAL is used. The on-line control is simulated by interfacing CORAL with a high fidelity simulator of sewer networks (MOUSE). CORAL interchanges readings from the limnimeters and gate commands with MOUSE as if it was connected with the real SCADA system. Finally, the global control results obtained using the predictive optimal control are presented and compared against the results obtained using current local control system. The results obtained using the global control are very satisfactory compared to those obtained using the local control.

A GMDH neural network-based approach to passive robust fault detection using a constraint satisfaction backward test

This paper proposes a new passive robust fault detection scheme using non-linear models that include parameter uncertainty. The non-linear model considered here is described by a group method of data handling (GMDH) neural network. The problem of passive robust fault detection using models including parameter uncertainty has been mainly addressed by checking if the measured behaviour is inside the region of possible behaviours based on the so-called forward test since it bounds the direct image of an interval function. The main contribution of this paper is to propose a new backward test, based on the inverse image of an interval function, that allows checking if there exists a parameter in the uncertain parameter set that is consistent with the measured system behaviour. This test is implemented using interval constraint satisfaction algorithms which can perform efficiently in deciding if the measured system state is consistent with the GMDH model and its associated uncertainty. Finally, this approach is tested on the servoactuator being a FDI benchmark in the European Project DAMADICS.

Leak Localization in Water Networks: A Model-Based Methodology Using Pressure Sensors Applied to a Real Network in Barcelona [Applications of Control]

The efficient distribution of water is a subject of major concern for water utilities and authorities [1]. While some leaks in water distribution networks (WDNs) are unavoidable, one of the main challenges in improving the efficiency of drinking water networks is to minimize leaks. Leaks can cause significant economic losses in fluid transportation and extra costs for the final consumer due to the waste of energy and chemicals in water treatment plants. Leaks may also damage infrastructure and cause third-party damage and health risks. In many WDNs, losses due to leakage are estimated to account up to 30% of the total amount of extracted water [2]; a very important issue in a world struggling to satisfy water demands of a growing population.

Fault Diagnosis of Wind Turbines using a Set-membership Approach

Abstract In this paper, the problem of fault diagnosis in wind turbines will be addressed applying a set-membership approach. Fault detection is based on the use of parity equations and unknown but bound description of the noise and modelling errors. Fault detection test is based on checking consistency between measurements and the model by finding if there is parameter in the feasible parameter set (approximated by a zonotope) that is compatible with modelling and noise bounds. The fault isolation algorithm is based on analyzing the observed fault signatures on-line and matching them with the theoretical ones obtained using structural analysis. Finally, the proposed approach will be tested using the wind turbine benchmark proposed in the context of the WT FDI competition.