Elastic fuzzy logic for self-learning control systems

In this paper, an adaptive network based on elastic fuzzy logic for control systems has been proposed. An expert initializes the network and then network´s weights are obtained by using neural network methods. An example of truck backer is given to illustrate the proposed method. In this example, we used the widrow´s method for calculating the controller output error