Parameter Identification and Adaptive PI Control using SLD-UBB

The design of accurate control system can take a lot of effort, especially when its dynamics are fairly complex or unknown and a desired outcome is critical. To estimate the real parameters of the dynamic model, the least squares estimation method can be used, even for nonlinear systems using the input and output measurements. The time differential equation of nonlinear model can be linearized to obtain the transfer function in the frequency domain. Thus, it is possible to adjust the controller gains based on the online parameters estimation to get an accurate controller contemplating real system constants. In this work, both, the estimation method and adaptive control method are tested using the remote laboratory SLD-UBB (Remote Laboratory System of the Universidad del Bio-Bio).