Reliable fault-tolerant model predictive control of drinking water transport networks

This paper proposes a reliable fault-tolerant model predictive control applied to drinking water transport networks. After a fault has occurred, the predictive controller should be redesigned to cope with the fault effect. Before starting to apply the fault-tolerant control strategy, it should be evaluated whether the predictive controller will be able to continue operating after the fault appearance. This is done by means of a structural analysis to determine loss of controllability after the fault complemented with feasibility analysis of the optimization problem related to the predictive controller design, so as to consider the fault effect in actuator constraints. Moreover, by evaluating the admissibility of the different actuator-fault configurations, critical actuators regarding fault tolerance can be identified considering structural, feasibility, performance and reliability analyses. On the other hand, the proposed approach allows a degradation analysis of the system to be performed. As a result of these analyses, the predictive controller design can be modified by adapting constraints such that the best achievable performance with some pre-established level of reliability will be achieved. The proposed approach is tested on the Barcelona drinking water transport network.Postprint (author's final draft

Leak signature space: an original representation for robust leak location in water distribution networks

In this paper, an original model-based scheme for leak location using pressure sensors in water distribution networks is introduced. The proposed approach is based on a new representation called the Leak Signature Space (LSS) that associates a specific signature to each leak location being minimally affected by leak magnitude. The LSS considers a linear model approximation of the relation between pressure residuals and leaks that is projected onto a selected hyperplane. This new approach allows to infer the location of a given leak by comparing the position of its signature with other leak signatures. Moreover, two ways of improving the method's robustness are proposed. First, by associating a domain of influence to each signature and second, through a time horizon analysis. The efficiency of the method is highlighted by means of a real network using several scenarios involving different number of sensors and considering the presence of noise in the measurements.Postprint (published version

Sensor placement for leak location in water distribution networks using the leak signature space

In this paper, a sensor placement approach to improve the leak location in water distribution networks is proposed. The sensor placement problem is formulated as an integer optimization problem where the criterion to minimize is the number of overlapping signature domains computed from the leak signature space (LSS) representation. A stochastic optimization process is proposed to solve this problem, based on either a Genetic Algorithms (GA) or a Particle Swarm Optimization (PSO) approach. Experiments on two different DMAs are used to evaluate the performance of the resolution methods as well as the effciency achieved in the leak location when using the sensor placement results.Postprint (published version

Robust nonlinear trajectory controllers for a single-rotor UAV with particle swarm optimization tuning

This paper presents the utilization of robust nonlinear control schemes for a single-rotor unmanned aerial vehicle (SR-UAV) mathematical model. The nonlinear dynamics of the vehicle are modeled according to the translational and rotational motions. The general structure is based on a translation controller connected in cascade with a P-PI attitude controller. Three different control approaches (classical PID, Super Twisting, and Adaptive Sliding Mode) are compared for the translation control. The parameters of such controllers are hard to tune by using a trial-and-error procedure, so we use an automated tuning procedure based on the Particle Swarm Optimization (PSO) method. The controllers were simulated in scenarios with wind gust disturbances, and a performance comparison was made between the different controllers with and without optimized gains. The results show a significant improvement in the performance of the PSO-tuned controllers.Peer ReviewedPostprint (published version

Efficient access to large datasets for linear regression models

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Extended-horizon analysis of pressure sensitivities for leak detection in water distribution networks: Application to the Barcelona Network

In this paper, a new approach for leak detection in water networks is proposed which considers an extended time horizon analysis of pressure sensitivities. Previous works based on pressure sensitivities analysis were developed by considering time instant evaluation. This fact makes them very sensitive to demand changes and noise in measurements. The proposed approach has been combined with five detection methods: the first is the binarization method, the second, third and fourth are based on the analysis of vectors with methods of correlation, vector angle and Euclidean distance respectively, and finally, the fifth is based on the least square optimization method. Another contribution of this paper is the performance comparison between the five detection methods in presence of single leaks in scenarios with noise in measurements and demands in each node. Results showed that in most of the methods efficiency is high, being the best the vector angle method, with efficiencies higher than 96%. The correlation and optimization method had similar behaviors with efficiencies superior to 90%. Finally, the binarization method is effective only in some scenarios but in presence of noise has a poor performance

Extended-horizon analysis of pressure sensitivities for leak detection in water distribution networks

In this paper, a new approach for leak detection in water networks is proposed which considers an extended time horizon analysis of pressure sensitivities. Previous works based on pressure sensitivities analysis were developed by considering time instant evaluation. This fact makes them very sensitive to demand changes and noise in measurements. The proposed approach has been combined with five detection methods: the first is the binarization method, the second, third and fourth are based on the comparison of measured pressure vectors with leak sensitivity matrix using methods of correlation, vector angle and Euclidean distance respectively. And, finally, the fifth is based on the least square optimization method. Another contribution of this paper is the performance comparison between the five detection methods in presence of single leaks in scenarios with noise in measurements and nodal demands. Results showed that in most of the methods effectiveness is high, being the best the vector angle method, with effectiveness higher than 96%. The correlation and optimization method had similar behaviors with effectiveness superior to 90%. Finally, the binarization method is effective only in some scenarios but in presence of noise has a poor performance

Sensor placement for leak location in water distribution networks using the leak signature space

In this paper, a sensor placement approach to improve the leak location in water distribution networks is proposed. The sensor placement problem is formulated as an integer optimization problem where the criterion to minimize is the number of overlapping signature domains computed from the leak signature space (LSS) representation. A stochastic optimization process is proposed to solve this problem, based on either a Genetic Algorithms (GA) or a Particle Swarm Optimization (PSO) approach. Experiments on two different DMAs are used to evaluate the performance of the resolution methods as well as the effciency achieved in the leak location when using the sensor placement results

Methodology for actuator fault tolerance evaluation of linear constrained MPC: application to the Barcelona water network

This paper presents a methodology to evaluate the admissibility of actuator fault configurations (AFC) when Linear Constrained Model Predictive Control (LCMPC) is used. The methodology combines the use of structural and feasability analysis. Structural analysis allows to evaluate the loss of reachability after a fault occurrence. The results of the structural analysis can be complemented with the feasibility analysis of the MPC problem taking into account the effect of actuator constraints after the fault occurrence. Additionally, a degradation analysis of the system performance can also be included. The proposed methodology is tested in the Barcelona water network

Extended-horizon analysis of pressure sensitivities for leak detection in water distribution networks

In this paper, a new approach for leak detection in water networks is proposed which considers an extended time horizon analysis of pressure sensitivities. Previous works based on pressure sensitivities analysis were developed by considering time instant evaluation. This fact makes them very sensitive to demand changes and noise in measurements. The proposed approach has been combined with five detection methods: the first is the binarization method, the second, third and fourth are based on the comparison of measured pressure vectors with leak sensitivity matrix using methods of correlation, vector angle and Euclidean distance respectively. And, finally, the fifth is based on the least square optimization method. Another contribution of this paper is the performance comparison between the five detection methods in presence of single leaks in scenarios with noise in measurements and nodal demands. Results showed that in most of the methods effectiveness is high, being the best the vector angle method, with effectiveness higher than 96%. The correlation and optimization method had similar behaviors with effectiveness superior to 90%. Finally, the binarization method is effective only in some scenarios but in presence of noise has a poor performance