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A general state-space representation is used to allow a complete formulation of the H optimization problem without any invertibility condition on the system matrix, unlike existing solutions. A straightforward approach is used to solve the one-block H optimization problem. The parameterization of all solutions to the discrete-time H suboptimal one-block problem is first given in transfer function form in terms of a set of functions in H that satisfy a norm bound. The parameterization of all solutions is also given as a linear fractional representation  相似文献   
2.
In this paper, a computational scheme for the H∞ model reduction problem is introduced. The scheme is illustrated by three examples. The algorithm is based on the recent characterization of the solution to the H∞ model reduction problem. A suboptimal computational procedure for the general multivariable continuous-time rth order optimal H model reduction problem is developed  相似文献   
3.
In this note, a new formulation and solution to the simultaneous stabilization problem (SSP) is given. The new method is based on finding a central plant from a set of plants to be simultaneously stabilized. The theory of robust stabilization can then be applied to the central plant with a bounded perturbation, which encapsulates the plants to be stabilized, in order to solve the SSP  相似文献   
4.
In this work the H-norm approximation of a given stable proper rational transfer function by a constant matrix is considered. A new improved bound on H-norm of a given stable transfer function is derived. Optimal approximation for relaxation systems is given  相似文献   
5.
The characterization of the solution to the problem of approximating a given stable, proper, rational transfer function, in L norm sense, by a rational function with prescribed number of stable and unstable modes is developed. A simple state-space suboptimal computational algorithm for the solution is presented  相似文献   
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