Robustness properties of output predictive dead-beat control: SISO case

The "dead beat" or "discrete minimum time" control law for sampled data systems is formulated as an output predictive linear equation problem rather than an eigenvalue/eigenvector assignment problem. Using the contraction mapping principle and a singular value analysis of this linear equation problem, then allows one to derive very general bounds for closed loop stability under conditions of both model and prediction, large scale errors. Furthermore, a direct design procedure is provided for selection of the "optimal" sample time to maximize closed loop robustness.

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