Yolanda Bolea

Gain-Scheduled Smith Predictor PID-Based LPV Controller for Open-Flow Canal Control

In this paper, a gain-scheduled Smith Predictor PID controller is proposed for the control of an open-flow canal system that allows for dealing with large variation in operating conditions. A linear parameter varying (LPV) control-oriented model for open-flow canal systems based on a second-order delay Hayami model is proposed. Exploiting the second-order structure of this model, an LPV PID controller is designed using H∞ and linear matrix inequalities pole placement. The controller structure includes a Smith Predictor, real time estimated parameters from measurements (including the known part of the delay) that schedule the controller and predictor and unstructured dynamic uncertainty, which covers the unknown portion of the delay. Finally, the proposed controller is validated in a case study based on a single real reach canal: the Lunax Gallery at Gascogne (France).

Linear parameter varying modeling and identification for real-time control of open-flow irrigation canals

Irrigation canals are open-flow water hydraulic systems, whose objective is mainly to convey water from its source down to its final users. They are large distributed systems characterized by non-linearity and dynamic behavior that depends on the operating point. Moreover, in canals with multiple reaches dynamic behavior is highly affected by the coupling among them. The physical model for those systems leads to a distributed-parameter model whose description usually requires partial differential equations (PDEs). However, the solution and parameter estimation of those PDE equations can only be obtained numerically and imply quite time-consuming computations that make them not suitable for real-time control purposes. Alternatively, in this paper, it will be shown that open-flow canal systems can be suitably represented for control purposes by using linear parameter-varying (LPV) models. The advantage of this approach compared to the use of PDE equation is that allows simpler models which are suitable for control design and whose parameters can be easily identified from input-output data by means of classical identification techniques. In this paper, the well-known control-oriented, model named integral delay zero (IDZ), that is able to represent the canal dynamics around a given operating point by means of a linear time-invariant (LTI) model is extended to multiple operating points by means of an LPV model. The derivation of this LPV model for single-reach open-flow canal systems as well as its extension to multiple-reach open-flow canals is proposed. In particular, the proposed methodology allows deriving the model structure and estimating model parameters using data by means of identification techniques. Thus, a gray-box control model is obtained whose validation is carried out using single-pool and two-pool test canals obtaining satisfactory results. Irrigation canals are open-flow water hydraulic systems that are described by a distributed parameter model.However, those PDE equations can only be obtained numerically and are not suitable for real-time control.This paper shows that open-flow canal systems can be suitably represented by using LPV models for control.In this paper, the IDZ model is extended to multiple operating points by means of an LPV model.Results on two cases studies illustrate the validity of the proposed approach.

Fractional DC/DC converter in solar-powered electrical generation systems

This paper deals with the fractional modeling of a DC-DC buck-boost converter, suitable in solar-powered electrical generation systems, and the design of a fractional controller for the aforementioned switching converter. Although the modeling and design of the controller is carried out for this particular DC-DC converter, it can be easily extended to other kind of switching converter. In addition, the comparison between integer-order plant/controller and fractional-order plants/controller is carried out. The article also shows that, under the same design conditions, the fractional-order controller has a better performance and behaviour than the classical integer-order controller in both situations, that is, with integer-order plant and fractional-order plant models.

Vision-Based SLAM System for Unmanned Aerial Vehicles.

The present paper describes a vision-based simultaneous localization and mapping system to be applied to Unmanned Aerial Vehicles (UAVs). The main contribution of this work is to propose a novel estimator relying on an Extended Kalman Filter. The estimator is designed in order to fuse the measurements obtained from: (i) an orientation sensor (AHRS); (ii) a position sensor (GPS); and (iii) a monocular camera. The estimated state consists of the full state of the vehicle: position and orientation and their first derivatives, as well as the location of the landmarks observed by the camera. The position sensor will be used only during the initialization period in order to recover the metric scale of the world. Afterwards, the estimated map of landmarks will be used to perform a fully vision-based navigation when the position sensor is not available. Experimental results obtained with simulations and real data show the benefits of the inclusion of camera measurements into the system. In this sense the estimation of the trajectory of the vehicle is considerably improved, compared with the estimates obtained using only the measurements from the position sensor, which are commonly low-rated and highly noisy.

Validation of Data Association for Monocular SLAM

Simultaneous Mapping and Localization (SLAM) is a multidisciplinary problem with ramifications within several fields. One of the key aspects for its popularity and success is the data fusion produced by SLAM techniques, providing strong and robust sensory systems even with simple devices, such as webcams in Monocular SLAM. This work studies a novel batch validation algorithm, the highest order hypothesis compatibility test (HOHCT), against one of the most popular approaches, the JCCB. The HOHCT approach has been developed as a way to improve performance of the delayed inverse-depth initialization monocular SLAM, a previously developed monocular SLAM algorithm based on parallax estimation. Both HOHCT and JCCB are extensively tested and compared within a delayed inverse-depth initialization monocular SLAM framework, showing the strengths and costs of this proposal.

New validation algorithm for data association in SLAM

In this work, a novel data validation algorithm for a single-camera SLAM system is introduced. A 6-degree-of-freedom monocular SLAM method based on the delayed inverse-depth (DI-D) feature initialization is used as a benchmark. This SLAM methodology has been improved with the introduction of the proposed data association batch validation technique, the highest order hypothesis compatibility test, HOHCT. This new algorithm is based on the evaluation of statistically compatible hypotheses, and a search algorithm designed to exploit the characteristics of delayed inverse-depth technique. In order to show the capabilities of the proposed technique, experimental tests have been compared with classical methods. The results of the proposed technique outperformed the results of the classical approaches.

Non-speech sound feature extraction based on model identification for robot navigation

Non-speech audio gives important information from the environment that can be used in robot navigation altogether with other sensor information. In this article we propose a new methodology to study non-speech audio signals with pattern recognition techniques in order to help a mobile robot to self-localize in space do-main. The feature space will be built with the more relevant coefficients of signal identification after a wavelet transformation preprocessing step given the non-stationary property of this kind of signals.

Inland navigation channel model: Application to the Cuinchy-Fontinettes reach

Inland navigation networks offer an alternative to land transport with economic and environmental benefits, and direct access to urban and industrial centers. Promoting the navigation transport requires the modernization of the network management, in particular the control of navigation levels and the improvement of the network safety. To reach these aims, modeling methods of the inland navigation networks have to be proposed. These networks are large scale distributed systems characterized by non-linearities, time-delays and generally no significant slope. A modeling method of a navigation channel based on identification method is proposed in this paper. It is applied on the Cuinchy-Fontinettes reach located in the north of France.

Remote laboratory for control engineering degree

This paper presents an innovative web-based control laboratory focused on the necessity of control education community. The usefulness of the remote laboratory proposed in this paper is justified by the opportunity of organizing the remote experiments, saving time and money for the students.

Gray-Box Model of Inland Navigation Channel: Application to the Cuinchy–Fontinettes Reach

Abstract In a context of global change, inland navigation transport has gained interest with economic and environmental benefits. The development of this means of conveyance requires the improvement of its management rules to deal with the increase of navigation (schedules and frequency) and the potential impact of global change. To achieve this aim, it is first necessary to have a better knowledge about the dynamics of inland navigation networks and their interaction with the environment. Second, the potential effects of global change have to be anticipated. This article focuses on the modeling of inland navigation reaches. An inland navigation network is a large-scale distributed system composed of several interconnected reaches. These reaches are characterized by non-linearities, time delays, and generally no significant slope. To deal with these particularities, a gray-box model is proposed. It consists in determining the delays according to the physical characteristics of the system. The parameters of the model are identified with measured data. The gray-box model is used to reproduce the dynamics of the Cuinchy–Fontinettes reach located in the north of France.