ANN-based-MPC-controller

This project presents a Model Predictive Control for autonomous car-like vehicles in which the model used for the prediction is obtained from a feedforward neural network in place of a mathematical model. The car's kinematic model is used in the controller for low speed applications. A two-layer feed-forward network with sigmoid hidden neurons and linear output neurons is used for model generation. The network was trained with Levenberg-Marquardt backpropagation algorithm. The model states the current position of the vehicle in terms of x and y coordinates from the last position coordinates of vehicle along with the velocity and steering angle of the car. Using this model, the controller outputs the control signal, i.e., velocity and steering angle of the car. Simulation were done on MATLAB to validate the results of the modelling and controller.