Implementation of control algorithms in Field Programmable Gate Arrays

The paper presents problems related to implementation of control algorithms in FPGA. Proposed solution is based on System-on-Programmable-Chip architecture with soft-processor that allows for mixed, hardware/software implementation and exploration of possible control algorithm realizations, and semi-automatic implementation of custom components in FPGA. The case study is a neural controller for 3-DOF parallel robot for milling. The controller is based on neural model of the inverse dynamics of the manipulator, trained on data collected with the use of a computed torque stabilizing controller. For comparison, both controllers were implemented in a system of the same.