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This paper deals with the estimation of the parameters of a model from experimental data. The aim of the method presented is to characterize the set S of all values of the parameter vector that are acceptable in the sense that all errors between the experimental data and the corresponding model outputs lie between known lower and upper bounds. This corresponds to what is known as bounded-error estimation...
In this paper we will apply interval methods to solve the problem of robust localization of an underwater robot. The localization problem is cast into a constraint satisfaction problem (CSP) where constraint propagation algorithms are particularly efficient. The method is designed to work in real environments with numerous outliers. Besides, we used a new approach to represent the map by a binary...
Uncertainties are commonly present in optimization systems, and when they are considered in the design stage, the problem usually is called a robust optimization problem. Robust optimization problems can be treated as noisy optimization problems, as worst case minimization problems, or by considering the mean and standard deviation values of the objective and constraint functions. The worst case scenario...
This paper presents a new approach for solving non-linear passive location problems. It is based on a high level interval modeling language named Quimper. Whereas classical passive location resolutions do not provide any guarantee of convergence to a solution, interval analysis, constraint propagation and contractor programming allow us to avoid any approximations and any linearization. Besides, Quimper...
We present a new approach for computing with fuzzy sets based on interval analysis techniques. Our proposed method is capable of managing multi-dimensional continuous membership functions of arbitrary form, such as, piecewise affine functions or non-linear expressions without any restrictions regarding convexity. We present a formal representation of fuzzy sets that allows to easily cast fuzzy problems...
This paper introduces a new formalism to deal with constrained dynamic systems. It shows that, when the constraints are linear, the controller can take advantage of linear programming algorithms (such as the simplex) to guarantee that the constraints will be satisfied. To illustrate the contribution of the approach, the control problem of a wheeled stair-climbing robot is considered. Masses supported...
This paper describes a new reliable method, based on modal interval analysis (MIA) and set inversion (SI) techniques, for the characterization of solution sets defined by quantified constraints satisfaction problems (QCSP) over continuous domains. The presented methodology, called quantified set inversion (QSI), can be used over a wide range of engineering problems involving uncertain nonlinear models...
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