Decoupling of Multivariable Control Systems Using Mod-ICA / Dissociação de sistemas de controle multivariável usando Mod-ICA - Cruz, Fábio George Nogueira (2021)
Sensors usage in process control systems is of vital importance for industrial plants proper operation and monitoring. In turn, process signals may have interference from other sources, and in some cases, it is not possible to observe the individual signs of the sources directly. Because of this, techniques of processing and separation of signals has been used to extract the information from the sources contained in mixed signals. The main signal separation techniques are associated with the technique ICA (Independent Component Analysis), which has undergone significant evolution since its creation in the 80’s. This growth had also received contributions from PCA technique (Principal Component Analysis), and the development of computational processing power. However, these methods have two fundamental problems, which are the deviation of amplitude, and phase change, with issues such as limiting its use in control systems. Thus, this work aims to present a solution to the amplitude problem of ICA's techniques for use in obtaining uncoupling of multivariable systems. The proposed correction, based on the stage of whitening of ICA algorithms, generating the technique MOD-ICA, has been used as an alternative to the breaking of the correlation between variables of multivariate systems, with the goal of achieving the decoupling of MIMO (Multiple Input Multiple Output) systems. In the study case, proposed in this work, it was observed a better estimation of the parameters of decoupling models for the control system. The variables, after using the ICA modified technique, are independent and do not present the influence of disturbances arising from other variables in the process, resulting in a more robust control system for process variations.