Abstract
The properties of different self-tuning algorithms are studied and evaluated using a phenomenological dynamic simulator of the flotation process. The problem of controlling a system with constant but unknown parameters is considered. In the beginning the analysis is restricted to discrete-time single input-single output systems. An explicit algorithm obtained by combining a least squares estimator with a minimum variance regulator computed from the estimated model is analyzed. The corresponding implicit generalized minimum variance algorithm is also tested. A multivariable self-tuning regulator based on the minimum variance strategy is represented. The conclusions are drawn upon these simulation results and on practical experience for the use of these algorithms in flotation control.
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