Thanks to their road safety potential, automated vehicles are rapidly becoming a reality. In
the last decade, automated driving has been the focus of intensive automotive engineering …

Model predictive control (MPC) is advantageous for designing an electrical vehicle path-
tracking controller, but the high computational complexity, mathematical problem, and …

An adaptive-prediction-horizon model prediction control-based path tracking controller for a
four-wheel independent control electric vehicle is designed. Unlike traditional model …

An asymptotic expression of the orthonormal polynomials PN (z) as N→∞, associated with
the singularly perturbed Laguerre weight w α (x; t)= x α e− x− tx, x∈[0,∞), α>− 1, t≥ 0⁠, is …

An asymptotic expression for the polynomials $\mathcal {P} _n (z) $, $ z\notin (-\infty,\infty) $,
orthonormal with respect to a singularly perturbed Gaussian weight, $\exp (-z^ 2-t/z^ 2),~ z\in …

We propose a novel parallel numerical algorithm for calculating the smallest eigenvalues of
highly ill-conditioned Hankel matrices. It is based on the LDLT decomposition and involves …

We study the asymptotic behavior of the smallest eigenvalue, λ N, of the Hankel (or
moments) matrix denoted by, with respect to the weight. An asymptotic expression of the …

In this paper, we study the large N behavior of the smallest eigenvalue λ N of the (N+ 1)×(N+
1) Hankel matrix, HN=(μ j+ k) 0≤ j, k≤ N, generated by the γ dependent Jacobi weight w (z …

We investigate the large N behavior of the smallest eigenvalue, λ N, of an (N+ 1)×(N+ 1)
Hankel (or moments) matrix HN, generated by the weight w (x)= x α (1− x) β, x∈[0, 1], α>− 1 …

Krylov subspace method is an effective method for large-scale eigenproblems. The shift-and-
invert Arnoldi method is employed to compute a few eigenpairs of a large Hankel matrix …