A new model predictive controller with swarm intelligence implemented on FPGA

Model predictive control (MPC) is an established control strategy used in the process industry, its computational efficiency becomes the main hindrance to its application in fast sampled systems, such as in motion control problems. Unlike controllers for process industries, the motion controller must have specific properties, including limited size and high sampling frequency. To meet these requirements, we explore the implementation of a specified new MPC with swarm intelligence, called PSO-MPC, on a field programmable gate array (FPGA) chip. Standard PSO is modified so as to be applied in MPC. The FPGA chip addresses size constraints, and the PSO-MPC -on-chip strategy satisfies the need for high sampling frequency by exploiting the parallel features of both the PSO-MPC and the FPGA chip. A constrained control problem with 3 controlled variables and a prediction horizon of 10 is solved in 1 ms. This verifies the applicability and effectiveness of PSO-MPC-on-chip strategy.