The multi-criteria predictive control of nonlinear dynamical systems based on Artificial Neural Networks (ANNs) and genetic algorithms (GAs) are considered. The (ANNs) are used to determine process models at each operating level; the control action is provided by minimizing a set of control...

A model predictive control design for nonlinear systems based on artificial neural networks is discussed. The Feedforward neural networks are used to describe the unknown nonlinear dynamics of the real system. The backpropagation algorithm is used, offline, to train the neural networks model....

This paper deals with the impact study of the choice of conjunctive operator between input variables of TSK fuzzy models, t-norm, on stability domain estimation. The approach is based on stability conditions issued from vector norms corresponding to a vector-Lyapunov function. In particular, for...