A neural approach for control of nonlinear systems with feedback linearization
1Lehrstuhl für Allgemeine und Theoretische Elektrotechnik, Universität Erlangen-Nürnberg, 91058 Erlangen, Germany.
Abstract:
In this paper several schemes for feedback linearization using neural networks have been investigated and compared. Then an approach to design a neurocontroller in the sense of feedback linearization is introduced. The contents include: 1) full input-output linearization when a system has relative degree n; 2) partial input-output linearization when a system has relative degree r (r < n); and 3) approximate linearization when the involutivity condition does not hold. Corresponding programs and examples are given to illustrate the proposed methodology.
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