A model-free control method for big time delay system based on improved iterative feedback tuning

Iterative feedback tuning (IFT) method is a model-free technique for controller parameters tuning and control performance optimization with no system identification. In this paper, combined with Smith predictor, a model-free closed-loop parameters optimization method for big time delay system is presented, called IFT-Smith algorithm. An improved efficient performance criterion is proposed, which includes the weighting part of predictive error as well as output signal and control effort. It turns out that the convergence and stability of the algorithm outperform the classical IFT when dealing with an anti-big-delay system. Three closed-loop experiments are carried out to perform the gradient descent optimization of the cost function, and the parameters of controller and predictor are tuned simultaneously. Simulation studies are conducted to demonstrate the effectiveness of the scheme.