Prediction-Based Adaptive Sliding Mode Control for Remotely Piloted System With Time Delay and Parameter Uncertainty

• Main Authors: Hongyang Xu, Yonghua Fan, Quancheng Li, Fan Wang, Jie Yan
• Format: Article
• Language: English
• Published: IEEE 2019-01-01
• Series: IEEE Access
• Subjects: Remotely piloted system (RPS); remotely piloted vehicle (RPV); time delay; state prediction; adaptive sliding mode control
• Online Access: https://ieeexplore.ieee.org/document/8744268/

This paper proposes a state prediction adaptive sliding mode (SPASM) control method for the remotely piloted system (RPS). With consideration of the time delay caused by the large transmission delay existing in the RPS, a prediction algorithm is proposed to provide the state prediction by using the state transition matrix. To approximate the uncertain lag of the remotely piloted vehicle (RPV) control augmentation system, an adaptive law is proposed to estimate the parameter uncertainties, and the overestimating problem is resolved efficiently. Meanwhile, to deal with the unmodeled dynamics and the predicted errors, a sliding mode controller is designed to guarantee the robustness of the whole closed-loop system. The simulation results show that the SPASM controller can not only guarantee the stability of the RPS in the presence of large time delay but also has a desirable performance of tracking the pilot's inputs while existing the unmodeled dynamics and parameter uncertainties.