319 research outputs found

    Reference Tracking AND Observer Design for Space-Fractional Partial Differential Equation Modeling Gas Pressures in Fractured Media

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    This paper considers a class of space fractional partial differential equations (FPDEs) that describe gas pressures in fractured media. First, the well-posedness, uniqueness, and the stability in L(∞R)L_(\infty{R})of the considered FPDEs are investigated. Then, the reference tracking problem is studied to track the pressure gradient at a downstream location of a channel. This requires manipulation of gas pressure at the downstream location and the use of pressure measurements at an upstream location. To achiever this, the backstepping approach is adapted to the space FPDEs. The key challenge in this adaptation is the non-applicability of the Lyapunov theory which is typically used to prove the stability of the target system as, the obtained target system is fractional in space. In addition, a backstepping adaptive observer is designed to jointly estimate both the system's state and the disturbance. The stability of the closed loop (reference tracking controller/observer) is also investigated. Finally, numerical simulations are given to evaluate the efficiency of the proposed method.Comment: 37 pages, 9 figure

    Sliding Mode Dirichlet Boundary Stabilization of Uncertain Parabolic PDE Systems With Spatially Varying Coefficients

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    Abstract-We consider the robust boundary stabilization problem of an unstable parabolic partial differential equation (PDE) system with uncertainties entering from both the spatially-dependent parameters and from the boundary conditions. The parabolic PDE is transformed through the Volterra integral into a damped heat equation with uncertainties, which contains the matched part (the boundary disturbance) and the mismatched part (the parameter variations). In this new coordinates, an infinite-dimensional sliding manifold that ensures system stability is constructed. For the sliding mode boundary control law to satisfy the reaching condition, an adaptive switching gain is used to cope with the above uncertainties, whose bound is unknown

    Robustness of Reaction-Diffusion PDEs Predictor-Feedback to Stochastic Delay Perturbations

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    This paper studies the robustness of a PDE backstepping delay-compensated boundary controller for a reaction-diffusion partial differential equation (PDE) with respect to a nominal delay subject to stochastic error disturbance. The stabilization problem under consideration involves random perturbations modeled by a finite-state Markov process that further obstruct the actuation path at the controlled boundary of the infinite-dimension plant. This scenario is useful to describe several actuation failure modes in process control. Employing the recently introduced infinite-dimensional representation of the state of an actuator subject to stochastic input delay for ODEs (Ordinary Differential Equations), we convert the stochastic input delay into r+1r+1 unidirectional advection PDEs, where rr corresponds to the number of jump states. Our stability analysis assumes full-state measurement of the spatially distributed plant's state and relies on a hyperbolic-parabolic PDE cascade representation of the plant plus actuator dynamics. Integrating the plant and the nominal stabilizing boundary control action, all while considering probabilistic delay disturbances, we establish the proof of mean-square exponential stability as well as the well-posedness of the closed-loop system when random phenomena weaken the nominal actuator compensating effect. Our proof is based on the Lyapunov method, the theory of infinitesimal operator for stability, and C0C_0-semigroup theory for well-posedness. Our stability result refers to the L2L^2-norm of the plant state and the H2H^2-norm of the actuator state...Comment: 16.5 pages, 6 figure

    Optimization based control design techniques for distributed parameter systems

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    The study presents optimization based control design techniques for the systems that are governed by partial differential equations. A control technique is developed for systems that are actuated at the boundary. The principles of dynamic inversion and constrained optimization theory are used to formulate a feedback controller. This control technique is demonstrated for heat equations and thermal convection loops. This technique is extended to address a practical issue of parameter uncertainty in a class of systems. An estimator is defined for unknown parameters in the system. The Lyapunov stability theory is used to derive an update law of these parameters. The estimator is used to design an adaptive controller for the system. A second control technique is presented for a class of second order systems that are actuated in-domain. The technique of proper orthogonal decomposition is used first to develop an approximate model. This model is then used to design optimal feedback controller. Approximate dynamic programming based neural network architecture is used to synthesize a sub-optimal controller. This control technique is demonstrated to stabilize the heave dynamics of a flexible aircraft wings. The third technique is focused on the optimal control of stationary thermally convected fluid flows from the numerical point of view. To overcome the computational requirement, optimization is carried out using reduced order model. The technique of proper orthogonal decomposition is used to develop reduced order model. An example of chemical vapor deposition reactor is considered to examine this control technique --Abstract, page iii

    A Strict Control Lyapunov Function for a Diffusion Equation with Time-Varying Distributed Coefficients

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    International audienceIn this paper, a strict Lyapunov function is developed in order to show the exponential stability and input-to-state stability (ISS) properties of a diffusion equation for nonhomogeneous media. Such media can involve rapidly time-varying distributed diffusivity coefficients. Based on this Lyapunov function, a control law is derived to preserve the ISS properties of the system and improve its performance. A robustness analysis with respect to disturbances and estimation errors in the distributed parameters is performed on the system, precisely showing the impact of the controller on the rate of convergence and ISS gains. This is important in light of a possible implementation of the control since, in most cases, diffusion coefficient estimates involve a high degree of uncertainty. An application to the safety factor profile control for the Tore Supra tokamak illustrates and motivates the theoretical results. A constrained control law (incorporating nonlinear shape constraints in the actuation profiles) is designed to behave as closely as possible to the unconstrained version, albeit with the equivalent of a variable gain. Finally, the proposed control laws are tested under simulation, first in the nominal case and then using a model of Tore Supra dynamics, where they show adequate performance and robustness with respect to disturbances

    Simulation and control of denitrification biofilters described by PDEs

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    Cette thèse concerne la simulation et la commande d'un biofiltre de dénitrification. Selon que l'on considère ou que l'on néglige la diffusion, des modèles d'EDP paraboliques ou hyperboliques sont considérés. En plus des classiques méthodes des lignes, des approches spécifiques au type d'EDP sont évaluées pour simuler le système. La méthode des caractéristiques s'applique aux systèmes d'EDP hyperboliques. L'analyse modale utilisée pour les systèmes d'EDP paraboliques permet de manipuler un système d'ordre réduit. L'objectif de commande est alors de réduire la concentration en azote en sortie du réacteur sous une certaine limite, en dépit des perturbations externes et des incertitudes du modèle. Deux stratégies de commande sont considérées. Une approche "early lumping" permet la synthèse d'une loi de commande linéaire H2 de type retour de sortie avec observateur. Une approche "late lumping" associe une loi de commande linéarisante à un observateur à paramètres distribués.This thesis addresses the simulation and control of a denitrification biofilter. Parabolic and hyperbolic PDE models may be considered, which depends on the fact of considering or neglecting the diffusion phenomenon. In plus of the classical methods of lines, approaches specific to the type of PDE system are evaluated to simulate the biofilter. The method of characteristics applies to hyperbolic PDE systems. The modal analysis used on the parabolic PDE system allows manipulating a reduced order model. The control objective is then the reduction of the nitrogen concentration at the output of the reactor below some pre-specified upper limit, in spite of the external disturbances and uncertainties of the model. Two control strategies are considered. An early lumping approach is used to synthesize an observer-based H2 output feedback linear controller. A late lumping approach associates a linearizing control to a distributed parameter observer
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