For the solution of the single-input pole placement problem we derive explicit expressions for the feedback gain matrix as well as the eigenvector matrix of the closed-loop system. Based on these formulas we study the conditioning of the pole-placement problem in terms of perturbations in the data and show how the conditioning depends on the condition number of the closed loop eigenvector matri...

An improved method is developed for eigenvalue and eigenvector placement of a closed-loop control system using either state or output feedback. The method basically consists of three steps. First, the singular value or QR decomposition is used to generate an orthonormal basis that spans admissible eigenvector space corresponding to each assigned eigenvalue. Second, given a unitary matrix, the e...

Optimal feedback controls of PDor PID-type can be approximated very efficiently by optimal open-loop feedback controls based on optimal open-loop controls. Extending the standard construction, stochastic optimal open-loop feedback controls are constructed by taking into account still the random parameter variations in the control system. Hence, corresponding to the standard deterministic case, ...

An [n, k, r]-hypergraph is a hypergraph :Yf = (V, E) whose vertex set V is partitioned into n k-element sets V1, V2, ... , Vn and for which, for each choice of r indices, 1 :::;; i1 < i2 < ... < ir :::;; n, there is exactly one edge e E E such that len Vii = 1 if i E {i1, i2, ... , ir} and otherwise le n Vii = 0. An independent transversal of an [n, k, r ]-hypergraph is a set T = {a1,a2, .. . ,...

We give a derivation of the loop equation for two-dimensional gravity from the KdV equations and the string equation of the one matrix model. We find that the loop equation is equivalent to an infinite set of linear constraints on the square root of the partition function satisfying the Virasoro algebra. We give an interpretation of these equations in topological gravity and discuss their exten...

This paper shows how a sparse hypermatrix Cholesky factorization can be improved. This is accomplished by means of efficient codes which operate on very small dense matrices. Different matrix sizes or target platforms may require different codes to obtain good performance. We write a set of codes for each matrix operation using different loop orders and unroll factors. Then, for each matrix siz...