Genetic tuned FPGA based PD fuzzy LUT controller

This paper presents the development of an FPGA-based proportional-differential (PD) fuzzy look-up table (LUT) controller. The fuzzy inference uses a 256-value LUT. This method has been used due to its reduced computation time cost. The controller architecture is focused on the treatment of errors and changes in errors with tuning gains in order to regulate the control system dynamics using a traditional method in industrial processes. The controller has been probed with several nonlinear plants, like an inverted pendulum and magnetic levitation, but the tuning of the system is too difficult using an iterative modification of the gains. A genetic algorithm was therefore used as a tuning tool to obtain a particular overshoot in the transient response of the control system.