Time delay always exists in real processes due to the distribution of a system and the data transport and communication lags, which might lead to worse and even unstable system performance.
Particularly, measurement delay usually degrades the overall system performance, and therefore, this factor should be minimized as much as possible.
With the purpose of improving the performance and effectiveness of a control system taking into account the characteristics of model predictive control (MPC), one of the control methods widely used in practice, Kim Hun Chol, a researcher at the Faculty of Automation Engineering, has proposed a method of eliminating the influence of measurement delay and applied it to the typical nonlinear system, ball & plate system, by combining it with MPC.
He designed an augmented state observer for a nonlinear discrete-time system with measurement delay to estimate delay-perturbed term, and implemented the state feedback to eliminate it. Then, he combined it with MPC to verify the effectiveness of the entire control system via simulations by MATLAB and real experiments by applying it to the ball & plate system.
In addition, he applied MPC to the control of machines and found out that the control was smooth and there was no strong oscillation that affects servomotors.