3D path-following control of robotic penguin: an ETFLMPC approach

Abstract

Path-following (PF) control is a critical technique in various underwater scenarios. This paper investigates the 3D path-following control problem of a robotic penguin propelled by median and paired fin (MPF), in which an event-triggered fuzzy linear model predictive control (ETFLMPC) method is presented. According to the discrete linear time-varying model, the LMPC controller based on line-of-sight (LOS) guidance and linear extended state observer (LESO) is further developed. Furthermore, using the appropriate back propagation neural network (BPNN) and fuzzy rules, the thrust is estimated, while the yaw moment is transformed into a controllable offset feathering angle of the pectoral fins. Then, an event-triggered condition is designed for reducing optimization frequency with strict feasibility and stability proof. Finally, numerical simulations are performed to demonstrate the effectiveness of the proposed control algorithm. Notably, this work contributes to the constrained underactuated 3D PF control issue of an MPF-propelled robotic penguin which has been rarely explored.