Le concept d’habitat intelligent s’est largement développé ces dernières années afin de proposer des solutions face à deux préoccupations majeures : la gestion optimisée de l’énergie dans le bâtiment et l’aide au maintien à domicile de personnes âgées. C’est dans ce contexte que le projet CAPTHOM, dans lequel s’inscrit cette thèse, a été développé. Pour répondre à ces problématiques, de nombreux capteurs, de natures différentes, sont utilisés pour la détection de la présence humaine, la détermination de la localisation et de la posture de la personne. En effet, aucun capteur, ne peut, seul, répondre à l’ensemble de ces informations justifiant le développement d’un dispositif multi-capteurs et d’une politique de fusion de données. Dans ce projet, les capteurs retenus sont les détecteurs infrarouges passifs, les thermopiles et la caméra. Aucun capteur n’est porté par la personne (non invasivité du dispositif). Nous proposons une architecture globale du capteur intelligent composée de quatre modules de fusion permettant respectivement de détecter la présence humaine, de localiser en 3D la personne, de déterminer la posture et d’aider à la prise de décision finale selon l’application visée. Le module de détection de présence fusionne les informations des trois capteurs : les détecteurs IRP pour la détection du mouvement, les thermopiles pour la présence en cas d’immobilité de la personne et la caméra pour identifier l’entité détectée. La localisation 3D de la personne est réalisée grâce à l’estimation de position sur horizon glissant. Cette méthode, nommée Visual Receding Horizon Estimation (VRHE), formule le problème d’estimation de position en un problème d’optimisation non linéaire sous contraintes dans le plan image. Le module de fusion pour la détermination de posture s’appuie sur la théorie des ensembles flous. Il assure la détermination de la posture indépendamment de la personne et de sa distance vis à vis de la caméra. Enfin, un module d’aide à la décision fusionne les sorties des différents modules et permet de déclencher des alarmes dans le cas de la surveillance de personnes âgées ou de déclencher des applications domotiques (chauffage, éclairage) pour la gestion énergétique de bâtiments. / The smart home concept has been widely developed in the last years in order to propose solutions for twomain concerns : optimized energy management in building and help for in-home support for elderly people.In this context, the CAPTHOM project, in which this thesis is in line with, has been developed. To respondto these problems, many sensors, of different natures, are used to detect the human presence, to determinethe position and the posture of the person. In fact, no sensor can , alone, answers to all information justifyingthe development of a multi-sensor system and a data fusion method. In this project, the selected sensorsare passive infrared sensors (PIR), thermopiles and a video camera. No sensor is carried by the person(non invasive system). We propose a global architecture of intelligent sensor made of four fusion modulesallowing respectively to detect the human presence, to locate in 3D the person, to determine the posture andto help to make a decision according to the application. The human presence module fuses information ofthe three sensors : PIR sensors for the movement, thermopiles for the presence in case of immobility and thecamera to identify the detected entity. The 3D localisation of the person is realized thanks to position recedinghorizon estimation. This method, called Visual Receding Horizon Estimation (VRHE), formulates the positionestimation problem into an nonlinear optimisation problem under constraints in the image plane. The fusionmodule for the posture determination is based on fuzzy logic. It insures the posture determination regardlessof the person and the distance from the camera. Finally, the module to make a decision fuses the outputs of the preceding modules and gives the opportunity to launch alarms (elderly people monitoring) or to commandhome automation devices (lightning, heating) for the energy management of buildings.

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We present a new trajectory generation algorithm for autonomous guidance and control of unmanned vehicles from a given starting point to a given target location. We build and update incomplete a priori maps of the operating environment in real time using onboard sensors and compute level sets on the map reflecting the minimal cost of traversal from the current vehicle location to the goal. We convert the trajectory generation problem into a finite-time-horizon optimal control problem using the computed level sets as terminal costs in a receding horizon framework and transform it into a simpler nonlinear programming problem by discretization of the candidate control and state histories. We ensure feasibility of the generated trajectories by constraining the solution of the optimization problem using a simplified vehicle model. We provide strong performance guarantees by checking for stability of the algorithm through the test of matching conditions at the end of each iteration. The algorithm thus explicitly incorporates the vehicle dynamics and constraints and generates trajectories realizable by the vehicle in the field. Successful preliminary field demonstrations and complete simulation results for a marine unmanned surface vehicle demonstrate the efficacy of the proposed approach for fast operations in poorly characterized riverine environments. / Master of Science

Scheduling refinery operation promises a big cut in logistics cost, maximizes efficiency, organizes allocation of material and resources, and ensures that production meets targets set by planning team. Obtaining accurate and reliable schedules for execution in refinery plants under different scenarios has been a serious challenge. This research was undertaken with the aim to develop robust methodologies and solution procedures to address refinery scheduling problems with uncertainties in process parameters. The research goal was achieved by first developing a methodology for short-term crude oil unloading and transfer, as an extension to a scheduling model reported by Lee et al. (1996). The extended model considers real life technical issues not captured in the original model and has shown to be more reliable through case studies. Uncertainties due to disruptive events and low inventory at the end of scheduling horizon were addressed. With the extended model, crude oil scheduling problem was formulated under receding horizon control framework to address demand uncertainty. This work proposed a strategy called fixed end horizon whose efficiency in terms of performance was investigated and found out to be better in comparison with an existing approach. In the main refinery production area, a novel scheduling model was developed. A large scale refinery problem was used as a case study to test the model with scheduling horizon discretized into a number of time periods of variable length. An equivalent formulation with equal interval lengths was also presented and compared with the variable length formulation. The results obtained clearly show the advantage of using variable timing. A methodology under self-optimizing control (SOC) framework was then developed to address uncertainty in problems involving mixed integer formulation. Through case study and scenarios, the approach has proven to be efficient in dealing with uncertainty in crude oil composition.

The tangential contact stiffness for ground Ti-6Al-4V surfaces is measured to linearly decrease with the application of tangential load. At the beginning of the application of tangential load, for ground surfaces, the ratio of the tangential contact stiffness to the normal contact stiffness is seen to be approximately half the Mindlin ratio. This is consistent with many other published experimental studies. Measurements of normal contact stiffness for ground surfaces conform to a model that posits a linear relationship between normal contact stiffness and normal load. An equivalent surface roughness parameter is defined for two surfaces in contact; and the normal contact stiffness for ground surfaces is observed to be inversely proportional to this parameter. Single asperity models were constructed to simulate the effect of different frictional laws and plasticity on the tangential displacement of an asperity contact. Further, multi-asperity modelling showed the effect of different normal load distributions on the tangential behaviour of interfaces. In addition, normal contact stiffness was modelled for a grid of asperities taking into account asperity interactions. A receding contact problem for which the required form of the distributed dislocations is bounded-bounded was solved. Then, a fundamental 2D frictional receding contact problem involving a homogeneous linear elastic infinite layer pressed by a line load onto a half-plane of the same material was analysed. This was done by the insertion of preformed distributed dislocations (or eigenstrains), which take into account the correct form of the separation of the interface at points away from the area of loading, along with corrective bounded-bounded distributions. The general method of solution was further refined and adapted to solve three other receding contact problems. The solutions demonstrated the robustness and applicability of this new procedure.

A novel application is presented for a fault-tolerant adaptive model predictive control system for small-scale helicopters. The use of a joint Extended Kalman Filter, (EKF), for the estimation of the states and parameters of the UAV, provided the advantage of implementation simplicity and accuracy. A linear model of a small-scale helicopter was utilized for testing the proposed control system. The results, obtained through the simulation of different fault scenarios, demonstrated that the proposed scheme was able to handle different types of actuator and system faults effectively. The types of faults considered were represented in the parameters of the mathematical representation of the helicopter. Benefits provided by the proposed fault-tolerant adaptive model predictive control systems include: The use of the joint Kalman filter provided a straightforward approach to detect and handle different types of actuator and system faults, which were represented as changes of the system and input matrices. The built-in adaptability provided for the handling of slow time-varying faults, which are difficult to detect using the standard residual approach. The successful inclusion of fault tolerance yielded a significant increase in the reliability of the UAV under study. A byproduct of this research is an original comparison between the EKF and the Unscented Kalman Filter, (UKF). This comparison attempted to settle the conflicting claims found in the research literature concerning the performance improvements provided by the UKF. The results of the comparison indicated that the performance of the filters depends on the approximation used for the nonlinear model of the system. Noise sensitivity was found to be higher for the UKF, than the EKF. An advantage of the UKF appears to be a slightly faster convergence.

Scheduling refinery operation promises a big cut in logistics cost, maximizes efficiency, organizes allocation of material and resources, and ensures that production meets targets set by planning team. Obtaining accurate and reliable schedules for execution in refinery plants under different scenarios has been a serious challenge. This research was undertaken with the aim to develop robust methodologies and solution procedures to address refinery scheduling problems with uncertainties in process parameters. The research goal was achieved by first developing a methodology for short-term crude oil unloading and transfer, as an extension to a scheduling model reported by Lee et al. (1996). The extended model considers real life technical issues not captured in the original model and has shown to be more reliable through case studies. Uncertainties due to disruptive events and low inventory at the end of scheduling horizon were addressed. With the extended model, crude oil scheduling problem was formulated under receding horizon control framework to address demand uncertainty. This work proposed a strategy called fixed end horizon whose efficiency in terms of performance was investigated and found out to be better in comparison with an existing approach. In the main refinery production area, a novel scheduling model was developed. A large scale refinery problem was used as a case study to test the model with scheduling horizon discretized into a number of time periods of variable length. An equivalent formulation with equal interval lengths was also presented and compared with the variable length formulation. The results obtained clearly show the advantage of using variable timing. A methodology under self-optimizing control (SOC) framework was then developed to address uncertainty in problems involving mixed integer formulation. Through case study and scenarios, the approach has proven to be efficient in dealing with uncertainty in crude oil composition.

Covariance assignment theory, introduced in the late 1980s, provided the only means to directly control the steady-state error properties of a linear system subject to Gaussian white noise and parameter uncertainty. This theory, however, does not extend to control of the transient uncertainties and to date there exist no practical engineering solutions to the problem of directly and optimally controlling the uncertainty in a linear system from one Gaussian distribution to another. In this thesis I design a dual-mode Receding Horizon Controller (RHC) that takes a controllable, deterministic linear system from an arbitrary initial covariance to near a desired stationary covariance in finite time. The RHC solves a sequence of free-time Optimal Control Problems (OCP) that directly controls the fundamental solution matrices of the linear system; each problem is a right-invariant OCP on the matrix Lie group GLn of invertible matrices. A terminal constraint ensures that each OCP takes the system to the desired covariance. I show that, by reducing the Hamiltonian system of each OCP from T?GLn to gln? x GLn, the transversality condition corresponding to the terminal constraint simplifies the two-point Boundary Value Problem (BVP) to a single unknown in the initial or final value of the costate in gln?. These results are applied in the design of a dual-mode RHC. The first mode repeatedly solves the OCPs until the optimal time for the system to reach the de- sired covariance is less than the RHC update time. This triggers the second mode, which applies covariance assignment theory to stabilize the system near the desired covariance. The dual-mode controller is illustrated on a planar system. The BVPs are solved using an indirect shooting method that numerically integrates the fundamental solutions on R4 using an adaptive Runge-Kutta method. I contend that extension of the results of this thesis to higher-dimensional systems using either in- direct or direct methods will require numerical integrators that account for the Lie group structure. I conclude with some remarks on the possible extension of a classic result called Lie?s method of reduction to receding horizon control.

Contact angle behavior controls the spreading, sticking, or movement of fluid droplets on top of solid substrates, and the immiscible displacement of mixed fluids in porous media. Therefore, it influences applications such as oil recovery, CO2 geological storage, water transport in unsaturated soils, and DNAPL soil remediation techniques. The attraction forces and geometrical-molecular arrangement at the atomic scale define the strength of the interfacial tension that changes in response to changes in temperature, pressure, or the fluid composition within the system. Contact line behavior such as contact line pinning or depinning, microscale roughness, and changes in interfacial tensions influence advancing and receding contact angles. This study consists of a comprehensive database of published advancing and receding contact angles to understand the underlying mechanisms of contact line pinning and depinning and the implications of these phenomena on advancing and receding contact angles. Calcite experiments that investigate advancing and receding contact angle measurements as a function of ionic concentration complement the published literature. Critical results include: an advancing contact angle trend with calcite as a function of ionic concentration, a point of minimum contact angle hysteresis when brine concentrations are close to 0.1 M, and that contact angle behavior depends on cation type and the calcite surface anisotropy. Contact line pinning prevents flow and increases contact angle hysteresis. An analysis of the database suggests that the wide range of contact angle hysteresis of calcite and quartz with water results both from hydrogen bonds and microscale roughness at the surface which leads to pinned contact lines. The Jamin effect reduces significantly in calcite when the resultant injection brines have an ionic concentration close to 0.1 M. Thus, the pressure difference required to displace a non-wetting fluid for a wetting fluid reduces, and leads to enhanced recovery of trapped oil, gas or DNAPL.

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