Control law partitioning via fuzzy logic control

Abstract

Control law partitioning is a widely used concept that incorporates a mathematical model of the plant into the control system. This is both an advantage and disadvantage. With an accurate model, the system control is much more robust and easy to manage. However, with a complex nonlinear system, an accurate mathematical model can be very difficult to obtain. A fuzzy logic controller can be developed that makes use of empirically derived data thereby accurately modeling the plant without the necessity of a mathematical model. Tuning such a controller to the empirical data can be problematic, so a tuning algorithm is used to adjust the controller parameters for optimal performance. In this paper, a fourth-order system is used as a demonstration plant, a fuzzy logic controller is developed using a very fast offline tuning algorithm, and the performance of the resulting controller is examined.