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Neural-net-based direct adaptive control for a class of nonlinear plants

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1 Author(s)
Ahmed, M.S. ; E/E Eng., DaimlerCrysler Corp., Auburn Hills, MI, USA

A direct adaptive control algorithm is presented for a class of nonlinear plants. No restriction has been imposed on the plant structure. The only condition the plant must satisfy is that the instantaneous input-output gain be positive. An artificial neural network (ANN)-based nonlinear controller structure has been employed. In line with the gain scheduling principle, however, the controller also has a pseudolinear time-varying structure with the parameters being the functions of the operating point. Simulation studies are also presented to validate the theoretical findings

Published in:

Automatic Control, IEEE Transactions on  (Volume:45 ,  Issue: 1 )