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• W786295772 abstract "Although non linearity characterizes most real control problems, methods for analysis and control design are considerably more powerful and theoretically founded for linear systems than for non linear ones. However, a wide variety of approaches are present in literature which aim to extend linear methodologies to non linear cases. In this paper we propose a hybrid architecture for the indirect control of non linear discrete time plants from their observed input-output behaviour. This approach combines a memory based learning identification procedure with control techniques borrowed from conventional adaptive control. We show how memory-based methods are an effective way to employ linear methods in non linear cases and we discuss the stability properties of the resulting controller in a simplified case. Experimental results in the control of some non linear benchmarks are presented." @default.
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• W786295772 date "1997-01-01" @default.
• W786295772 modified "2023-09-27" @default.
• W786295772 title "Lazy learning indirect control for discrete time non-linear systems" @default.
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