This project deals with the design and implementation of advanced control methods on embedded microprocessor platforms used in the industry. In order to explore the possibilities of wider industrial implementation of the given advanced control methods. The methods are based on optimization and are able to certify the safety of the operation. Furthermore, the given methods can take into account the requirements for control performance and constraints for controlled and manipulated variables, which leads to an increase in the quality of production, and to a reduction in operating costs and negative impacts on the environment. The implementation of the given methods on embedded platforms is also in accordance with the concept of Industry 4.0. Selected advanced control methods implementable on embedded microprocessor platforms are (i) robust control based on convex lifting, (ii) explicit model predictive control, (iii) predictive control based on neural networks. The control performance of the given methods will be analyzed and compared by means of various laboratory equipment, considering the embedded platforms. Selected equipment is (i) laboratory plate heat exchanger, (ii) laboratory chemical reactor, (iii) laboratory air conditioning-heating unit (from the English heating, ventilation, and air conditioning HVAC system). These plants represent important parts of operations from various industries from chemical and pharmaceutical to manufacturing industry. And the implementation of advanced control methods considering embedded platforms would have the potential to significantly contribute to the development of the industrial operation.