Erik-Jan van Kampen

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In science and engineering there often is a need for the approximation of scattered multi-dimensional data. A class of powerful scattered data ap-proximators are the multivariate simplex B-splines. Multivariate simplex B-splines consist of Bernstein basis polynomials that are defined on a geometrical structure called a triangulation. Multivariate simplex(More)
Bio-inspired methods can provide efficient solutions to perform autonomous landing for Micro Air Vehicles (MAVs). Flying insects such as honeybees perform vertical landings by keeping flow divergence constant. This leads to an exponential decay of both height and vertical velocity, and allows for smooth and safe landings. However, the presence of noise and(More)
The design of unknown-input decoupled observers and filters requires the assumption of an existence condition in the literature. This paper addresses an unknown input filtering problem where the existence condition is not satisfied. Instead of designing a traditional unknown input decoupled filter, a Double-Model Adaptive Estimation approach is extended to(More)
We define a SDP framework based on the RLS TD algorithm and multivariate simplex B-splines. We introduce a local forget factor capable of preserving the continuity of the simplex splines. This local forget factor is integrated with the RLS TD algorithm, resulting in a modified RLS TD algorithm that is capable of tracking time-varying systems. We present the(More)
When using interval analysis, the bounds of an inclusion function are often non-tight due to dependency effects. The benefit of Taylor Models (TMs) or Verified Taylor Series (VTSs) is the use of higher order derivatives terms, significantly reducing the dependency effect. In this paper, it is assumed that the required information to derive these inclusion(More)
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