Abstract
Model Predictive Control techniques offer favorable characteristics for the process control sector and have been used in industry since the 1980s. Some of the advantages of the Model Predictive Control techniques are that the process model can capture both static and dynamic interactions between input, output, and disturbance variables; the existing constraints on inputs and outputs are considered systematically, and the control calculations can be coordinated with the calculation of optimum set-points. This study aims to design and implement a Model Predictive controller for the flowrate control loop of the FESTO MPS PA Compact Workstation. The designed Model Predictive controller has an important advantage because it is easy to conFig. how much energy should be used using well-designed tuning parameters. First, a dynamic model of the plant is obtained using Pseudo-Random Binary Signal input. The obtained model is used to define the objective function, determine the aspects to be optimized and analyze and identify the restrictions and limitations of the control algorithm. For the implementation of the model predictive control algorithm, LabVIEW software was used because it can execute a graphic visualization of the operation of the plant, and it offers ActiveX controls that are needed for interfacing with the MPS PA compact workstation. Finally, the controller's behavior was analyzed, and comments about the obtained results and conclusions on this line of research are presented.