Towards an Optimal Learning for Robust Iterative-Based Intelligent PID

This contribution considers a model-free control method based on an optimal iterative learning control framework to design a suitable controller. Using this framework, the controller requires neither the information about the systems dynamical structure nor the knowledge about system physical behaviors. The task is solved using only the system outputs and inputs, which are assumed as measurable. The structure of the proposed method consists of three parts. The first part is implemented through an intelligent PID controller on the system. In the second part, a robust second order differentiator via sliding mode is applied in order to estimate accurately the evolution of the state function. In the third part, an optimal iterative learning control is chosen to improve the performance. Numerical examples are shown to demonstrate the successful application and performance of the method.