title: Neural regulator design.
abstract: Design of a neural-net-based regulator for nonlinear plants is considered. Both state and output feedback regulators with deterministic and stochastic disturbances have been investigated. A Multilayered Feedforward Neural Network (MFNN) has been employed as the nonlinear controller. The training of the MFNN utilizes the recently developed concept of Block Partial Derivatives (BPDs).
authors.affiliation: Department of Systems Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia
authors.forename: M S.
authors.initials: MS
authors.lastname: Ahmed
authors.forename: M A.
authors.initials: MA
authors.lastname: Al-Dajani