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A new vs/adaptive controller for plants of any relative degree
Author(s) -
Bartolini Giorgio,
Ferrara Antonella
Publication year - 1996
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/(sici)1099-1115(199607)10:4/5<451::aid-acs374>3.0.co;2-o
Subject(s) - control theory (sociology) , controller (irrigation) , feed forward , adaptive control , convergence (economics) , mathematics , variable (mathematics) , variable structure control , degree (music) , exponential function , computer science , control (management) , sliding mode control , nonlinear system , control engineering , engineering , mathematical analysis , artificial intelligence , physics , quantum mechanics , economic growth , acoustics , agronomy , economics , biology
A new controller for LTI SISO plants is presented which is characterized by the use of a combined variable structure/adaptive control strategy. The scheme, which is derived from a previous proposal by the authors, can be applied to plants with any relative degree without increasing the order of the filters which constitute the controller. However, it requires a subset of the parameters of the feedback part of the controller to be identified in order to indirectly determine the parameters of the feedforward part. As a consequence, the convergence of the parameters is mandatory to exactly assign the plant dynamics because of the intrinsic direct/indirect nature of the scheme. What is shown in the paper is that if a pure variable structure approach were followed to design the control strategy, the explicit identification of the coefficients of the filters would not be allowed but only the identification of the so‐called ‘equivalent control’ coinciding with the ideal control. However, by coupling the variable structure control strategy with a continuous parameter adjustment mechanism, it is possible to obtain an equivalent control which, during the sliding motion, turns out to be equal to a suitably constructed prediction error. The latter can be used to drive a parameter adjustment mechanism which, under the usual assumption of a persistently exciting regressor signal, guarantees the exponential convergence to zero of the parameter error.