A Tuning Method via Borges Derivative of a Neural Network-Based Discrete-Time Fractional-Order PID Controller with Hausdorff Difference and Hausdorff Sum

In this paper, the fractal derivative is introduced into a neural network-based discrete-time fractional-order PID controller in two areas, namely, controller’s structure and parameter optimization algorithm. The first use of to reconstruct by using Hausdorff difference sum derived from integral. It can avoid derivation Gamma function for order updating realize tuning based on networks. other parameters Borges derivative. kind as local chain rule composite consistent with integral-order suitable This paper improves aspects, which accelerates response speed control accuracy. Two illustrative examples are given verify effectiveness proposed scheme derivatives.