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In this paper, a new frequency-weighted model reduction method with an a priori error bound is proposed. The method is a generalization of Enns technique and yields stable models even when both input and output weightings are included. The proposed method is compared with other existing methods using numerical examples.
The most widely used configuration of DC machines is series-wound type. The main advantages are simpler control system design and no separately excited field windings. However, the use of DC motors in electric vehicles has declined dramatically in the current decade. Unless the efficiency of such a system can be improved significantly the use of DC motors(More)
Stability margin of singular perturbation systems via state feedback control, " Int. Improvement on stability bounds for singularly perturbed systems via state feedback, " Int. Robust stabilization of linear systems with norm-bounded time-varying uncertainty, " Syst. A brief summary of the bounds on the solution of the algebraic matrix equations in control(More)
—An improved frequency domain interval Gramian-based model reduction scheme for discrete time systems is presented. It is first shown that two of the main results presented in the model reduction method of [20] are incorrect. Improved methods which overcomes these shortcomings are then presented. Improved methods not only yields stable reduced-order models(More)