FPGA-based control architecture integration for multiple-axis tracking motion systems

This paper addresses the integration of a multi-loop PI and neural fuzzy control system for multiple-axis motion positioning and tracking via the use of the Field Programmable Gate Array (FPGA) technology. The controlled plant here is an X-Y table driven by permanent magnet linear synchronous motors. The control system comprises two programmable servo-control systems for both axes, each includes a motion planner, a PI speed controller in the inner loop and a neural fuzzy controller (NFC) in the position loop. Here, to increase the tracking performance in dealing with unmodelled dynamics and cross-axis interferences, the NFC is designed by using a radial basis function neural network in combination with a parameter adjusting mechanism. The very high speed integrated circuit-hardware description language (VHDL) is adopted to describe advantageous behaviors of the proposed control system. To implement the whole control paradigm, the FPGA chip is developed in Quartus II and Nios II software environment, provided by Altera for analysis and synthesis of VHDL designs. Simulation results of the software/hardware co-design have verified the high performance and effectiveness of the proposed chip-based control system in positioning and trajectory tracking for the X-Y table motion.