Towards Online Model Predictive Control on a Programmable Logic Controller: Practical Considerations

Given the growing computational power of embedded controllers, the use ofmodel predictive control MPC strategies on this type of devices becomes more and more attractive. This paper investigates the use of online MPC, in which at each step, an optimization problem is solved, on both a programmable automation controller PAC and a programmable logic controller PLC . Three different optimization routines to solve the quadratic program were investigated with respect to their applicability on these devices. To this end, an air heating setup was built and selected as a small-scale multi-input single-output system. It turns out that the code generator CVXGEN is not suited for the PLC as the required programming language is not available and the programming concept with preallocatedmemory consumes too muchmemory. The Hildreth and qpOASES algorithms successfully controlled the setup running on the PLC hardware. Both algorithms perform similarly, although it takes more time to calculate a solution for qpOASES. However, if the problem size increases, it is expected that the high number of required iterations when the constraints are hit will cause the Hildreth algorithm to exceed the necessary time to present a solution. For this small heating problem under test, the Hildreth algorithm is selected as most useful on a PLC.