Modelling and Control of a nonlinear distillation column: A, using fractional-order controllers

This paper takes up the challenge of modelling a complex nonlinear distillation column type-A and designs four optimal controllers for the same. The nonlinear plant is first linearized into a linear higher-order model. Thereafter, it is reduced into a lower-order model. Subsequently, the controllers are designed for the lower-order linear model. The controllers are designed by reducing the error cost functions, namely Integral Square Error (ISE), Integral Absolute Error (IAE) and Integral Time Absolute Error (ITAE). The process of optimization is done heuristically using the Genetic Algorithm method of tuning. The four controllers designed are Proportional Integral Derivative, Fractional-order Proportional Integral Derivative, Tilt Integral Derivative and Fractional-order Internal Model Control. A thorough comparison is made between the three designed controllers, first on the Single Input Single Output (SISO), then to the reduced-order linear model and finally to the main plant. The FO-IMC controller is shown as an exhibition controller designed using GA to demonstrate the novelty of its kind. It has also been compared, but the results show poor performances as it has not been tuned with the same parameters as the rest.