Application Of Nonlinear Predictive Control Research Articles

Application of nonlinear predictive control for charging the battery using wind energy with permanent magnet synchronous generator

Wind energy is an important renewable source which is used for power generation for a stand-alone as well as grid connected applications. In many remote areas, loads are usually connected away from the grid. In such cases, isolated wind energy systems can be considered as an effective way to provide continuous power to electrical loads.In this paper, a robust nonlinear predictive control (NLPC) for an isolated wind energy conversion system is implemented using a variable speed permanent magnet synchronous generator (PMSG) with pulse with modulation (PWM) rectifier connect to a battery. The turbine is employed with Optimal Torque control (OTC) to achieve a maximum level of wind power extraction.The main of control is to adjust the rectifier voltage amplitude in order to charge battery and this despite the presence of disturbance which manifests in the variation of wind speed and load changes varying. This control it has-been experimentally Implemented using Dspace1104 hardware driving in real-time the studied system.Practical and simulation results show that the NLPC imposes the voltage under wind conditions. The controller shows a good performance during dynamic and steady state condition.

A neural predictive controller for non-linear systems

Design and implementation are studied for a neural network-based predictive controller meant to govern the dynamics of non-linear processes. The advantages of using neural networks for modeling non-linear processes are shown together with the construction of neural predictors. The resulting implementation of the neural predictive controller is able to eliminate the most significant obstacles encountered in non-linear predictive control applications by facilitating the development of non-linear models and providing a rapid, reliable solution to the control algorithm. Controller design and implementation are illustrated for a plant frequently referred to in the literature. Results are given for simulation experiments, which demonstrate the effectiveness of the proposed approach.