Implementation and Analysis of Offset-Free Explicit Model Predictive Controller on FPGA

It is well-known that the real-time implementation of Model Predictive Control (MPC) is cumbersome because of the huge burden of solving optimization problem on-line at each sample time. Due to this, MPC has been mainly restricted to processes with rather slow dynamics, such as the ones encountered in the oil and gas refineries. However, recent algorithmic advances (such as the explicit MPC) allowed usage of MPC to problems arising in the automotive or power electronics industry where the time scales are in the milli- to microsecond range. This paper focuses on the Field Programmable Gate Array (FPGA) implementation of offset-free explicit MPC and its detailed analysis for the position control of PMDC motor. We show the analysis of controller computational complexity in terms of memory, resource utilization, clock and power consumption. Along that effects of various tuning parameters on the number of regions is also presented with respect to the changing prediction horizon length. Finally, the performance of implemented offset-free explicit MPC is compared with the standard explicit MPC and Proportional-Integral controller for reference-tracking, constraints handling, and disturbance rejection. Results indicate that the performance of offset-free explicit MPC is superior but at the cost of increased memory footprint.