an adaptive version of growing and pruning rbf neural network has been used to predict the system output and implement linear model-based predictive controller (lmpc) and non-linear model-based predictive controller (nmpc) strategies. a radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.an unscented kalman filter (ukf) algor...

This work presents an application of the previously proposed Support Vector Machines Based Generalized Predictive Control (SVM-Based GPC) method [1] to the problem of controlling chaotic dynamics with small parameter perturbations. The Generalized Predictive Control (GPC) method, which is included in the class of Model Predictive Control, necessitates an accurate model of the plant that plays v...

This paper is concerned with generalized predictive control based on state-space model for networked control systems. Both the network-induced time delay and packet loss are taken into account. The networked predictive controller design is discussed with respect to three network cases, which are related to packet loss, network-induced delay, and both packet loss and network-induced delay, respe...

This paper presents an algorithm for predictive control using fuzzy models.This strategy is a Predictive Control Strategy for Nonlinear systems. The algorithm takes advantage of the already well known methods for linear systems (like Generalized Predictive Control). Analysis of the modiied algorithm is presented and performance comparisons are shown. The performance comparisons are made using a...