Unscented Kalman-filter-based sliding mode control for an underwater gliding snake-like robot

Abstract

With its strong endurance and high maneuverability, an underwater gliding snake-like robot (UGSR) is a strong potential candidate for aquatic exploration and monitoring. The major feature of the UGSR, which distinguishes it from other snake-like robots, is long range and long operation duration by gliding. This study establishes a gliding motion control system for the UGSR based on a sliding mode controller (SMC). The control system stabilizes the system and suppresses the uncertainties and unknown disturbances. In this strategy, chattering is reduced based on the reaching law method. To circumvent the difficulty of velocity measurements, a nonlinear observer based on an unscented Kalman filter (UKF) is employed for state estimation and random noise handling. The effectiveness of the proposed controller and observer is verified by simulating the UKF-based SMC closed-loop system.

Research on multi-source information collaborative anti-interference technology

“…To obtain the motion information and guidance law, the measured data need to be processed by the Kalman filter. For data link information, the linear Kalman filter (KF) is selected, while for missile angle information, we choose the Unscented Kalman filter (UKF) [10].…”

Disturbance-observer-based finite time sliding mode controller with unmatched uncertainties utilizing improved cubature Kalman filter

“…But not much concentration was given to noise and matched disturbances. Later in 2020, Tang et al (2020) suggested an unscented Kalman filter (UKF) with SMC to enhance the robustness and tracking even in the presence of noise parameters for the underwater gliding snake-like robot. Thus, it can be seen that most of the works in SMC and K for disturbance observer were applied to mostly electrical processes.…”