Convergence of control performance by unfalsification of models - levels of confidence
International Journal of Adaptive Control and Signal Processing, 15, (5), . (doi:10.1002/acs.685).
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A general framework is introduced for iterative/adaptive controller design schemes by model unfalsification. An important feature of the schemes is their convergence near to the best possible controller given a set of model and controller structures. The problem of stability assured controller tuning is examined through unfalsified Riemannian bands of the Nyquist plot. Instability tolerant H(?) and l(1)-norm-based controller tuning schemes are introduced. Computational problems are discussed and a simulation is used to illustrate the new scheme.
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