A fractional model for robust fractional order Smith predictor
Volume 73, pages1557–1563, 2013
In this paper, we propose to use a fractional order model to predict the process output in Smith predictor. The parameters of the model are determined by minimizing the error between its output and one of the processes using a genetic algorithm. After determining the model’s parameters, a fractional PID controller is proposed to improve the controlled system performances. The parameters of the controller are also determined in an optimal way by minimizing the position error taking into account the sensitivity and the complementary sensitivity conditions. Applications on a dead time and multiple lags processes have been performed, where the simulation results show that the proposed Smith predictor enhance the closed loop control system.
Smith predictor, Fractional calculus, Fractional controller, Fractional model, Sensitivity function, Complementary sensitivity function, Optimization