A comparative study of several control techniques applied to a boost converter

In this paper a comparison among three control strategies is presented, with application to a boost DC-DC converter. The control strategies are developed on the switched boost circuit model and validated on the nonlinear model by use of simulations. The classical PID, a 2dof-IMC (two degree of freedom internal model controller) and an alternative controller - MAC (uprocessor advanced control) are applied, tested and compared on the nonlinear system. Additional tests show the robustness of the controllers on the highly nonlinear circuit

A convexity-based homotopy method for nonlinear optimization in model predictive control

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A Convex Approximation for Parameter Estimation Involving Parameter-Affine Dynamic Models

This paper presents a convex approach for parameter estimation problems (PEPs) involving parameter-affine dynamic systems. By using the available state measurements, the nonconvex PEP is modified such that a convex approximation is obtained. The optimum delivered by this approximation is subsequently used to linearize the original PEP such that a refined solution is obtained. An assessment of the distance between the actual solution and the one delivered by the refined approximation is provided using perturbation analysis. Comparative results using a classical nonlinear parameter estimation procedure and the proposed approach are presented for two benchmark examples where the theoretical assessment of errors in solutions is corroborated numerically.[**]status: publishe

An automatic initialization procedure in parameter estimation problems with parameter-affine dynamic models

This paper proposes an initialization approach for parameter estimation problems (PEPs) involving parameter-affine dynamic models. By using the state measurements, the nonconvex PEP is modified such that a convex approximation to the original PEP is obtained. The modified problem is solved by convex optimization methods yielding an approximate solution to the original PEP. The approximate solution can be further refined by linearizing the original problem around the obtained minimum. An assessment of the distance between the real solution and the one provided by the linearization of the problem around the convex approximation is presented. The optimum obtained by the convex approximation is used to subsequently initialize a simultaneous Gauss-Newton (SGN) approach on the original nonconvex PEP. Comparative results for the SGN with arbitrary initialization and with the proposed approach are presented using three benchmark examples in the chemical and biological fields. © 2009 Elsevier Ltd. All rights reserved.[**]status: publishe