Paulo Lopes dos Santos

Guest Editorial Special Issue on Applied LPV Modeling and Identification

The nine regular and three brief papers in this special issue present the current state-of-the-art in the neighboring fields of Linear Parametrically Varying (LPV) modeling and system identification.

Linear Parameter-Varying System Identification: New Developments and Trends

• A submitted manuscript is the authors version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publishers website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.

An LPV Modeling and Identification Approach to Leakage Detection in High Pressure Natural Gas Transportation Networks

In this paper a new approach to gas leakage detection in high pressure natural gas transportation networks is proposed. The pipeline is modelled as a Linear Parameter Varying (LPV) System driven by the source node massflow with the gas inventory variation in the pipe (linepack variation, proportional to the pressure variation) as the scheduling parameter. The massflow at the offtake node is taken as the system output. The system is identified by the Successive Approximations LPV System Subspace Identification Algorithm which is also described in this paper. The leakage is detected using a Kalman filter where the fault is treated as an augmented state. Given that the gas linepack can be estimated from the massflow balance equation, a differential method is proposed to improve the leakage detector effectiveness. A small section of a gas pipeline crossing Portugal in the direction South to North is used as a case study. LPV models are identified from normal operational data and their accuracy is analyzed. The proposed LPV Kalman filter based methods are compared with a standard mass balance method in a simulated 10% leakage detection scenario. The Differential Kalman Filter method proved to be highly efficient.

Modelling a gas pipeline as a repetitive process: controllability, observability and stability

In this paper, the gas dynamics within the pipelines is modelled as a repetitive process with smoothing. Controllability and observability criteria when the system is steered through initial and boundary data, which is achieved by an adequate choice of the homogeneity, are obtained. From the point of view of the technical applications, it seems to make more sense to consider boundary data controls as for instance in the management of high pressure gas networks. Stability criteria suitable computer simulations are also included.

Simulation of Gas Networks and Leak Detection Using Quadripole Models

A cost-effective, accurate, and robust leak detection method is essential in gas network management in order to reduce inspection time and to increase reliability in the system. This work presents a model-based leakage detection method; the gas dynamics are described by a linearized system of partial differential equations that is further reduced to a one-dimensional spatial model. By using an electrical analogy, a pipeline can be represented by a two-port network, where mass flow behaves like current and pressure like voltage. Four transfer function quadripole models are then established to describe the gas pipeline dynamics, depending on the variables of interest at the pipeline boundaries. A leak detection method is devised by employing mass flow data at boundaries and pressure data at some point of the pipeline, as well as by assessing the effects of the leakage on the pressure and mass flow along the pipeline. A case study has been built from operational data supplied by REN Gasodutos (the Portuguese gas company) to show the advantages of the proposed models.

Boundary control of discrete repetitive processes with smoothing: controllability, observability and disturbance attenuation

In this paper, we proffer an explicit representation of solutions for a specific class of linear repetitive processes with smoothing. This representation is used to obtain direct controllability and observability criteria of this same class of discrete time 2-D systems. Not only classical controllability properties are considered, where control of the system is obtained by choosing its inhomogeneity appropriately, but also controllability of the system by steering it through boundary data control. From the point of view of technical applications, for instance in high pressure gas network modelling (see Azevedo-Perdicoúlis and Jank in Proceedings of n-DS, international workshop on multidimensional systems, Thessaloniki. 2009), it seems to be more reliable to consider boundary data controls. Therefore, in this paper we emphasise boundary data control properties of the system. A disturbed optimal boundary control problem with a quadratic criterion is also solved.