A class of weak Kharitonov regions for robust stability of linearuncertain systems

Kharitonov's theorems are generalized to the problem of so-called weak Kharitonov regions for robust stability of linear uncertain systems. Given a polytope of (characteristic) polynomials P and a stability region D in the complex plane, P is called D-stable if the zeros of every polynomial in P are contained in D. It is of interest to know whether the D-stability of the vertices of P implies the D-stability of P. A simple approach is developed which unifies and generalizes many known results on this problem     

The minimal dimension of stable faces required to guaranteestability of a matrix polytope

Considers the problem of determining whether each point in a polytope n×n matrices is stable. The approach is to check stability of certain faces of the polytope. For n⩾3, the authors show that stability of each point in every (2n-4)-dimensional face guarantees stability of the entire polytope. Furthermore, they prove that, for any k⩽n², there exists a k-dimensional polytope containing a strictly unstable point and such that all its subpolytopes of dimension min {k-1,2n-5} are stable     

Robust Schur stability of a polytope of polynomials

The main objective of the authors is to provide a necessary and sufficient condition for a polytope of polynomials to have all its zeros inside the unit circle. The criterion obtained serves as a discrete-time counterpart for results in S. Bialas (1985) and F. Fu and B.R. Barmish (1987) for the continuous case. Also, the results are reduced to operations on (n-1)×(n-1) matrices. It is concluded that, by the edge result of A.C. Bartlett et al. (1987), it suffices to check the exposed edges in order to determine whether a polytope of polynomials has all its zeros in a simply connected region D     

n-D polynomial matrix equations

Linear matrix equations in the ring of polynomials in n indeterminates (n-D) are studied. General- and minimum-degree solutions are discussed. Simple and constructive, necessary and sufficient solvability conditions are derived. An algorithm to solve the equations with general n-D polynomial matrices is presented. It is based on elementary reductions in a greater ring of polynomials in one indeterminate, having as coefficients polynomial fractions in the other n-1 indeterminates, which makes the use of Euclidean division possible     

On time mapping of uniform dependence algorithms into lowerdimensional processor arrays

Most existing methods of mapping algorithms into processor arrays are restricted to the case where n-dimensional algorithms, or algorithms with n nested loops, are mapped into (n-1)-dimensional arrays. However, in practice, it is interesting to map n-dimensional algorithms into (k-1)-dimensional arrays where k<n. A computational conflict occurs if two or more computations of an algorithm are mapped into the same execution time. Based on the Hermite normal form of the mapping matrix, necessary and sufficient conditions are derived to identify mapping without computational conflicts. These conditions are used to find time mappings of n-dimensional algorithms into (k-1)-dimensional arrays, k<n , without computational conflicts. For some applications, the mapping is time-optimal     

Kharitonov regions: it suffices to check a subset of vertexpolynomials

The authors deal with the D-stability property of interval polynomials. In particular, they show that certain D-domains are Kharitonov regions. That is, the D-stability of interval polynomials is implied by the D-stability of all its vertex polynomials. They then proceed to show that it suffices to check the D-stability of a subset of the vertex polynomials     

Computing the width of a set

For a set of points P in three-dimensional space, the width of P, W (P), is defined as the minimum distance between parallel planes of support of P. It is shown that W(P) can be computed in O(n log n +I) time and O(n) space, where I is the number of antipodal pairs of edges of the convex hull of P, and n is the number of vertices; in the worst case, I=O( n²). For a convex polyhedra the time complexity becomes O(n+I). If P is a set of points in the plane, the complexity can be reduced to O(nlog n). For simple polygons, linear time suffices     

An efficient distributed knot detection algorithm

A distributed knot detection algorithm for general graphs is presented. The knot detection algorithm uses at most O(n log n+m) messages and O(m+n log n) bits of memory to detect all knots' nodes in the network (where n is the number of nodes and m is the number of links). This is compared to O(n²) messages needed in the best algorithm previously published. The knot detection algorithm makes use of efficient cycle detection and clustering techniques. Various applications for the knot detection algorithms are presented. In particular, its importance to deadlock detection in store and forward communication networks and in transaction systems is demonstrated     

Parallel implementation of the extended square-root covariancefilter for tracking applications

Parallel implementations of the extended square-root covariance filter (ESRCF) for tracking applications are developed. The decoupling technique and special properties used in the tracking Kalman filter (KF) are employed to reduce computational requirements and to increase parallelism. The application of the decoupling technique to the ESRCF results in the time and measurement updates of m decoupled (n/m)-dimensional matrices instead of one coupled n-dimensional matrix, where m denotes the tracking dimension and n denotes the number of state elements. The updates of m decoupled matrices are found to require approximately m fewer processing elements and clock cycles than the updates of one coupled matrix. The transformation of the Kalman gain which accounts for the decoupling is found to be straightforward to implement. The sparse nature of the measurement matrix and the sparse, band nature of the transition matrix are explored to simplify matrix multiplications     

Parallel binary search

Two arrays of numbers sorted in nondecreasing order are given: an array A of size n and an array B of size m, where n<m. It is required to determine, for every element of A, the smallest element of B (if one exists) that is larger than or equal to it. It is shown how to solve this problem on the EREW PRAM (exclusive-read exclusive-write parallel random-access machine) in O(logm logn/log log m) time using n processors. The solution is then extended to the case in which fewer than n processors are available. This yields an EREW PRAM algorithm for the problem whose cost is O(n log m, which is O(m)) for n⩽m/log m. It is shown how the solution obtained leads to an improved parallel merging algorithm     

An algorithm computing the general entry of the nthKronecker power of a matrix

The number of distinct entries among the m²ⁿ entries of the nth Kronecker power of an m×m matrix is derived. An algorithm to find the value of each entry of the Kronecker power is presented     

Fault-tolerant embedding of complete binary trees in hypercubes

The focus is on the following graph-theoretic question associated with the simulation of complete binary trees by faulty hypercubes: if a certain number of nodes or links are removed from an n-cube, will an (n-1)-tree still exists as a subgraph? While the general problem of determining whether a k-tree, k< n, still exists when an arbitrary number of nodes/links are removed from the n-cube is found to be NP-complete, an upper bound is found on how many nodes/links can be removed and an (n-1)-tree still be guaranteed to exist. In fact, as a corollary of this, it is found that if no more than n-3 nodes/links are removed from an (n-1)-subcube of the n-cube, an (n-1)-tree is also guaranteed to exist     

Bicoprime factorizations of the plant and their relation to right and left-coprime factorizations

In a general algebraic framework, starting with a bicoprime factorization P=N_prD^-1 N_pl, a right-coprime factorization N_p D_p^-1, a left-coprime factorization D^-1_pN_p, and the generalized Bezout identities associated with the pairs (N_p, D_p) and (D˜ _p, N˜_p) are obtained. The set of all H-stabilizing compensators for P in the unity-feedback configuration S(P, C) are expressed in terms of (N_pr, D, N _pt) and the elements of the Bezout identity. The state-space representation P=C(sI-A)^-1B is included as an example     

Balanced parallel sort on hypercube multiprocessors

A parallel sorting algorithm for sorting n elements evenly distributed over 2^d p nodes of a d-dimensional hypercube is presented. The average running time of the algorithm is O((n log n)/p+p log 2n). The algorithm maintains a perfect load balance in the nodes by determining the (kn/p)th elements (k1,. . ., (p-1)) of the final sorted list in advance. These p-1 keys are used to partition the sorted sublists in each node to redistribute data to the nodes to be merged in parallel. The nodes finish the sort with an equal number of elements (n/ p) regardless of the data distribution. A parallel selection algorithm for determining the balanced partition keys in O(p log2n) time is presented. The speed of the sorting algorithm is further enhanced by the distance-d communication capability of the iPSC/2 hypercube computer and a novel conflict-free routing algorithm. Experimental results on a 16-node hypercube computer show that the sorting algorithm is competitive with the previous algorithms and faster for skewed data distributions     

Complete instability of a box of polynomials

The authors study the converse of V.L. Kharitonov's polynomial problem (1978) by asking whether the complete instability of a box of polynomials can be determined from extreme sets. They show that it is not enough to check the (n-4)-dimensional boundary, but prove that the complete instability of the (n-1)-dimensional boundary is sufficient     

A novel discrete relaxation architecture

The discrete relaxation algorithm (DRA) is a computational technique that enforces arc consistency (AC) in a constraint satisfaction problem (CSP). The original sequential AC-1 algorithm suffers from O(n³m³) time complexity, and even the optimal sequential AC-4 algorithm is O (n²m²) for an n-object and m-label DRA problem. Sample problem runs show that these algorithms are all too slow to meet the need for any useful, real-time CSP applications. A parallel DRA5 algorithm that reaches a lower bound of O(nm) (where the number of processors is polynomial in the problem size) is given. A fine-grained, massively parallel hardware computer architecture has been designed for the DRA5 algorithm. For practical problems, many orders of magnitude of efficiency improvement can be reached on such a hardware architecture     

An efficient digital search algorithm by using a double-arraystructure

An efficient digital search algorithm that is based on an internal array structure called a double array, which combines the fast access of a matrix form with the compactness of a list form, is presented. Each arc of a digital search tree, called a DS-tree, can be computed from the double array in 0(1) time; that is to say, the worst-case time complexity for retrieving a key becomes 0(k) for the length k of that key. The double array is modified to make the size compact while maintaining fast access, and algorithms for retrieval, insertion, and deletion are presented. If the size of the double array is n+cm, where n is the number of nodes of the DS-tree, m is the number of input symbols, and c is a constant particular to each double array, then it is theoretically proved that the worst-case times of deletion and insertion are proportional to cm and cm², respectively, and are independent of n. Experimental results of building the double array incrementally for various sets of keys show that c has an extremely small value, ranging from 0.17 to 1.13     

On reliable computation with formal neurons

The authors investigate the computing capabilities of formal McCulloch-Pitts neurons when errors are permitted in decisions. They assume that m decisions are to be made on a randomly specified m set of points in n space and that an error tolerance of ϵm decision errors is allowed, with 0⩽ϵ<1/2. The authors are interested in how large an m can be selected such that the neuron makes reliable decisions within the prescribed error tolerance. Formal results for two protocols for error-tolerance-a random error protocol and an exhaustive error protocol-are obtained. The results demonstrate that a formal neuron has a computational capacity that is linear in n and that this rate of capacity growth persists even when errors are tolerated in the decisions     

One more counterexample in n-D systems-unimodular versuselementary operations

By a simple counterexample, it is shown that there are unimodular matrices which cannot be written as products of elementary matrices in the ring of n-D polynomials. As a consequence, some methods for the solution of n-D matrix polynomial equations published recently, which are based on the elementary operations in the ring of n-D polynomials, do not work     

Parameter convergence and stability in continuous-time indirectadaptive control

The author considers an indirect adaptive unity feedback controller consisting of an mth-order SISO (single input, single output) compensator controlling an nth-order strictly proper SISO plant. It is shown that exponential convergence of the plant parameter estimation error as well as asymptotic time invariance and global exponential stability of the controlled closed-loop system can be guaranteed by requiring that the reference input has at least 2n+m points of spectral support