Model-free adaptive integral sliding mode predictive control for nonlinear time-delay processes

Authors:
Publisher website
Google Scholar
Abstract
Driven by the robust control requirements of complex time-delay systems in industrial processes, this paper investigates a model-free adaptive integral sliding mode predictive control algorithm for a class of nonlinear unknown time-delay systems affected by external disturbances. A one-step forward prediction error is utilized to obtain information on the delay present in the system, which is then used within the output predictor. Then, an output predictor based optimal extended parameter estimator is designed to establish the dynamic linearization model. An integral sliding mode predictive control algorithm is then proposed, which provides robustness to the impacts of the unknown time-delay and the external disturbances. The convergence of the estimated parameters and the stability of the closed-loop system are proved mathematically. Finally, the effectiveness of the proposed method is demonstrated via both simulation and experimental testing.
Funding Information
  • National Natural Science Foundation of China (61973315)
  • National Natural Science Foundation of China (61473312)
  • Science and Technology Program of Qingdao, China (22-3-7-cspz-15-nsh)

This publication has 26 references indexed in Scilit: