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This paper solves the general ~(~ control problem by a purely algebraic approach. Existence conditions for an ~(® controller are given in terms of linear matrix inequalities, and all ~® controllers are parametrized explicitly in state space. Abstrad-This paper presents all controllers for the general ~'® control problem (with no assumptions on the plant(More)
OBJECTIVE To compare the effectiveness of routine neonatal examination performed by senior house officers (SHOs) and advanced neonatal nurse practitioners (ANNPs). DESIGN A prospective study of all infants referred to specialist orthopaedic, ophthalmology, and cardiology clinics. A standardised proforma was used to record details of the professional(More)
Computational techniques that exploit the geometry of the design space are proposed to solve fixed-order control design problems described in terms of linear matrix inequalities and a coupling rank constraint. Abstract-Computational techniques based on alternating projections are proposed to solve control design problems described by linear matrix(More)
— This paper presents a new algorithm for the design of linear controllers with special structural constraints imposed on the control gain matrix. This so called SLC (Structured Linear Control) problem can be formulated with linear matrix inequalities (LMI's) with a nonconvex equality constraint. This class of problems includes fixed order output feedback(More)
— This paper provides algorithms for numerical solution of convex matrix inequalities (MIs) in which the variables naturally appear as matrices. This includes, for instance, many systems and control problems. To use these algorithms, no knowledge of linear matrix inequalities (LMIs) is required. However, as tools, they preserve many advantages of the linear(More)
This paper gives a theory of noncommutative functions which results in an algorithm for determining where they are " matrix convex ". Of independent interest is a theory of noncommutative quadratic functions and the resulting algorithm which calculates the region where they are " matrix positive semidef-inite ". This is accomplished via a theorem on writing(More)