Robust predictive scheme for input delay systems subject to nonlinear disturbances
- 146 Downloads
The predictor-based control is known as an effective method to compensate input delays. Yet the traditional predictors, like Smith predictor, have poor robustness with respect to system disturbances. In this paper, with the consideration of future disturbances, a novel robust predictive scheme is developed for input delay systems subject to nonlinear disturbances. The Artstein reduction method is used to provide performance analysis of different predictor-based controllers, which shows that the proposed predictor-based controller can provide better disturbance attenuation than previous approaches in the literature for a wide range of disturbances.
KeywordsInput delay Nonlinear disturbances Predictor Robust control
This work was supported in part by the NSFC 61673215, 61673169, 61374087, 61773191 the Natural Science Foundation of Jiangsu Province under Grant BK20140770, the Fundamental Research Funds for the Central Universities 30916015105, the 333 Project (BRA2017380), the Program for Changjiang Scholars and Innovative Research Team in University (No. IRT13072), PAPD, the Key Laboratory of Jiangsu Province, Shandong Provincial Natural Science Foundation for Distinguished Young Scholars under Grant JQ201515 and the Taishan Scholarship Project of Shandong Province.
- 6.Feng, H., Xu, H., Xu, S., Chen, W.: Distributed control design for spatially interconnected markovian jump systems with timevarying delays. Asian J. Control, 1–10 (2018)Google Scholar
- 9.Smith, O.J.M.: Closer control of loops with dead time. Chem. Eng. Prog. 53(5), 217–219 (1957)Google Scholar
- 29.Levant, A.: Globally convergent fast exact differentiator with variable gains. In: Proceedings of the European Control Conference (2014)Google Scholar
- 30.Moreno, J.A., Osorio, M.: A Lyapunov approach to second-order sliding mode controllers and observers. In: Proceedings of the 47th IEEE Conference on Decision and Control (2008)Google Scholar
- 32.Khalil, H.K.: Nonlinear Systems. Prentice-Hall, New Jersey (1996)Google Scholar