Diseño de un sistema de control inteligente para el banco de presión del laboratorio de automatización. - Sotomayor Japón, Jhandry Fernando (2024)
This curriculum integration work covers the design of an intelligent control system for the pressure measurement and control bench located in the industrial automation laboratory of the Faculty of Energy, Industries and Non-Renewable Natural Resources. As a first point of the work, a bibliographic search and review is performed, corresponding to the topics of experimental identification of dynamic systems, fuzzy intelligent control system, manual of use of the pressure bench, MATLAB® tools in design and simulation of control systems. Subsequently, the procedure of experimental identification of systems is performed to obtain a mathematical model that adequately represents the dynamics of the system. A model with a fit percentage >80% is sought. For this purpose, communication between the bench and the computer is established by means of an Ethernet cable for data acquisition and control. Then, FieldPoint 2010 modules are used for the acquisition and control of signals in real time in control applications such as LabVIEW 2011 software, thus, tests are performed under the same conditions equally. Later MATLAB® software is used to carry out the experimental identification of systems through System Identification, using the data obtained to create several models of the system and by means of the method of Zeros and Poles and the percentage of adjustment, the one that best represents the plant is chosen. For the design process of the Fuzzy controller is performed by means of tools such as Fuzzy Logic Toolbox and Simulink of MATLAB®, the control system of the plant is created which will represent the mathematical model, in the controller input and output variables are taken into account, making a fuzzy rule base that relates the variables, likewise it is added to the control system made to perform the simulation. Tests of disturbance, sound and variations in the setpoint in the simulation are performed to demonstrate the behavior and performance that will exercise the fuzzy controller. Finally, a comparison is made by simulation of the performance of the fuzzy controller versus conventional controllers, the simulations show the curves, jumps, stabilization times in order to verify the optimal controller that performs its work better. Keywords: Pressure Bench, Fuzzy Intelligent Control System, MATLAB® tools, system identification, mathematical model.