The main aim of the proposed research project is to investigate and design new advanced methods of automatic control in process industries to improve efficiency profitability, stability, and competitiveness of process plants. We will focus on processes with heat and mass transfer where efficiency can be improved significantly. These processes are inherently complex, exhibit nonlinear and hybrid behavior that has consequences in control quality and performance. The aim of the project can be effectively achieved by implementing model predictive control (MPC). We will focus on robust and numerically efficient design of MPC including modern research directions using data-based models. Also, important will be software implementation of proposed solutions, available to a larger community in open-source code as well as verification of the proposed methods in laboratory conditions and with our industrial partners.