Predictive Control And Application Of Genetic Algorithm-based Neural Network

This paper studied on the combination of predictive control, artificial neural network and genetic algorithm, and applied it to unmanned vehicles.Predictive control is an optimizing control algorithm which developed in 1970s. It has the advantage of convenience of modeling and good robust characteristic. With simple or low-precise predictive model, this control strategy can let control system gain high control quality. However, applied predictive control algorithm mostly is based on linear stable system. The nonlinearity of unmanned vehicles requires a nonlinear model in predictive control. It is convenient to use artificial neural network to model such a nonlinear system. This paper used neural network as the predictive model, and genetic algorithm as optimizing algorithm, to simulate the unmanned vehicle's ascending process. In addition, this paper also studied on optimizing neural networks utilizing the global searching mechanism of genetic algorithm.