Modeling of quadruple tank system using support vector regression

In this paper, ε — Support Vector Regression (SVR) method is employed to model a quadruple tank system. For a successful and reliable analysis and synthesis in control engineering, primarily, the correct estimation of system model is of great significance. SVR can be used as an important tool in modeling, since it has a good generalization ability, owing to its basic properties of structural risk minimization and ensuring global minima. This suggests the use of SVR in intelligent modeling of nonlinear systems and in tuning of controller parameters based on this system model. In this work, we employ SVR to model a quadruple tank system, as an example of MIMO process modeling. We present and discuss our simulation results.

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