Design, implementation and experimental validation of explicit MPC in programmable logic controller

This paper describes the model predictive control (MPC) in terms of an explicit controller without on-line optimization problem solving and its implementation in the programmable logic controller (PLC). For this purpose the multi-parametric quadratic programming (MPQP) approach with binary search tree (BST) is used. The optimal values are computed off-line for all possible system states and then stored in the form of appropriate table, while the computation of current system states and the search for proper control output are performed on-line. The task is to control the temperature in an incubator unit with the PLC, which executes an explicit MPC algorithm. Setting the reference value and monitoring of the processes are carried out by the human machine interface (HMI) which communicates with the PLC via Ethernet network. So, the objective is to show that the MPC control can adequately be adapted in PLC, which is commonly used for the control of industrial processes. The effectiveness and robustness of this approach are verified through experiments.