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 Kal...

this paper presents a novel indirect adaptive power system stabilizer (pss) via a developed synergetic control methodology and fuzzy systems. fuzzy system is utilized in an adaptive scheme to estimate the system using a nonlinear model. the synergetic control guarantees robustness of the controller and makes the controller easy to implement because of using a chatter free continuous control law...

In this paper, a neural network model reference adaptive system speed observer is designed, which can be used in speed control of linear induction motors (LIMs). Dynamical equations of LIM have been considered accurate. In other words, the end effect and the electrical losses of the motor have been included in the motor equivalent circuit. Then equations of the reference model and adaptive mode...

in this paper, controlling the gyros with linear plus cubic damping is considered. hence, an adaptive control algorithm is proposed to overcome the uncertainties in model parameters and the chaotic behavior of gyroscopes. it is noted that for general applications dynamic model coefficient of gyros is not precisely determined, on the other hand, with respect to a particular coefficient gyroscope...