Abstract
The self tuning regulator is applied to multivariable systems with unknown constant parameters. The disturbances acting on the system and the uncertainty about the parameter values prevent application of deterministic control strategies. Based upon the certainty equivalence principle, the parameters of the process model are estimated using the least squares method and then the estimated parameters are used in the control algorithm of the regulator. The control signal is then augmented with a random signal. The transient properties of this combination are considerably improved over the basic multivariable self tuning regulator (MVSTR). For systems with white noise disturbances, random signals with different characteristics are tested.
The results of these tests are compared against the basic MVSTR. It is evident from the investigation that an improvement of the response could be achieved. This is also reflected in the reduction of the performance criterion
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El-Bagoury, M.A., Bayoumi, M.M. (1980). Multivariable self tuning augmented regulator. In: Unbehauen, H. (eds) Methods and Applications in Adaptive Control. Lecture Notes in Control and Information Sciences, vol 24. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0003253
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DOI: https://doi.org/10.1007/BFb0003253
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