We investigate a new class of nonlinear control systems of O.D.E., which are not feedback linearizable in general. Our class is a generalization of the well-known feedback linearizable systems, and moreover it is a generalization of the triangular (or pure-feedback) forms studied before. The definition of our class is global, and coordinate-free, which is why the problem of the equivalence is s...

The identification of multivariable state space models in innovation form is solved in a subspace identification framework using convex nuclear norm optimization. The convex optimization approach allows to include constraints on the unknown matrices in the data-equation characterizing subspace identification methods, such as the lower triangular block-Toeplitz of weighting matrices constructed ...

We consider a multi-class G/G/1 queue with a finite shared buffer. There is task admission and server scheduling control which aims to minimize the cost which consists of holding and rejection components. We construct a policy that is asymptotically optimal in the heavy traffic limit. The policy stems from solution to Harrison-Taksar (HT) free boundary problem and is expressed by a single free ...

This paper deals with ridge estimation of fuzzy nonparametric regression models using triangular fuzzy numbers. This estimation method is obtained by implementing ridge regression learning algorithm in the La- grangian dual space. The distance measure for fuzzy numbers that suggested by Diamond is used and the local linear smoothing technique with the cross- validation procedure for selecting t...

We give an elementary proof that the H p spaces over the unit disc (or the upper half plane) are the interpolation spaces for the real method of interpolation between H 1 and H ∞. This was originally proved by Peter Jones. The proof uses only the boundedness of the Hilbert transform and the classical factorisation of a function in H p as a product of two functions in H q and H r with 1/q + 1/r ...

The identification of multivariable state space models in innovation form is solved in a subspace identification framework using convex nuclear norm optimization. The convex optimization approach allows to include constraints on the unknown matrices in the data-equation characterizing subspace identification methods, such as the lower triangular block-Toeplitz of weighting matrices constructed ...

In this paper, a closed-loop subspace identification approach through an orthogonal projection and subsequent singular value decomposition is proposed. As a by-product of this development, it explains why some existing subspace methods may deliver a bias in the presence of the feedback control and suggests a remedy to eliminate the bias. Furthermore, as the proposed method is a projection based...

i=1 gijXi, g = (gij) ∈ Gl(n,k)), given any term-ordering< and homogeneous ideal a ⊆ P(n), there exists a non-empty open subset U of Gl(n,k) such that as g ranges in U, gin(a) := in(g(a)) is constant. Moreover, gin(a) is fixed by the group B of upper-triangular invertible matrices, if X1 > · · · > Xn, while gin(a) is fixed by the group B′ of lower-triangular invertible matrices if X1 < · · · < X...

This paper is about the existence and regularity of the transition probability matrix of a nonhomogeneous continuous-time Markov process with a countable state space. A standard approach to prove the existence of such a transition matrix is to begin with a continuous (in t) and conservative matrix Q(t) = [qij(t)] of nonhomogeneous transition rates qij(t), and use it to construct the transition ...

Recently, the number of researches aiming at showing real world objects from arbitrary viewpoint have been steadily growing. The processing method is divided into three stages: 3D shape reconstruction by the visual cone intersection method, conversion of 3D shape representation from a voxel form into a triangular patch form, and coloring triangular patches. If the surface area of the object bec...