A neural approach for control of nonlinear systems with feedback linearization
Shouling He, K. Relf, Rolf Unbehauen · IEEE Transactions on Neural Networks · 1998
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.