Predictive Control of Temperature in a Batch Reactor with Discrete Inputs

The paper deals with model predictive control (MPC) of systems with discrete inputs based on reachability analysis. The basic algorithm is - due to its MPC nature - suitable for controlling a wide spectrum of systems, provided that they have discrete inputs only, therefore its advantages are especially evident when dealing with relatively complex systems. The tree of evolution used by the algorithm is tackled, cost function selection is discussed and a universal cost function form is proposed. Computational complexity of the control method is treated thoroughly and an approach for reducing it by holding the inputs through a number of time steps is presented. Usability of the algorithm is verified on a batch reactor simulation example. The basic approach and the approach with holding the inputs through a number of time steps are compared. The results suggest that the latter can significantly improve control, especially when dealing with stiff systems such as the batch reactor