Dynamic Damping-Based Terminal Sliding Mode Event-Triggered Fault-Tolerant Pre-Compensation Stochastic Control for Tracked ROV

Abstract

Due to the unknown disturbance caused by the harsh environment in deep water, the stability of Underwater Tracked Remotely Opreated Vehicle (UTROV) trajectory tracking control is affected; especially the resistance forces of random vibrations caused by non-differentiable random disturbance resistance, which has become one of the main problems in controller design. Considering engineering practice, a stochastic model and new dynamic damping-based terminal sliding mode event-triggered fault-tolerant controller were designed in this paper. Firstly, based on the random resistance pre-compensation theory for the first time, a stochastic model was designed for differential drive UTROV. Meanwhile, a new nonsingular terminal sliding mode and dynamic damping reaching law were designed to achieve global finite-time convergence and reduce chattering with better robust response speed. Furthermore, to deal with the wear and tear caused by actuator failure and fixed sampling rate transmission, a new dynamic event trigger mechanism was designed and the faults analyzed. On this basis, combined with the finite-time adaptive on-line estimation technology, it can not only better reduce the transmission frequency, but also the finite-time dynamic active fault-tolerant compensation. The control scheme has semi-globally finite-time stability in probability and is proved by theory, which is compliant with engineering requirements. Then, according to characteristics of innovation, the three groups of simulation of control methods are designed to compare the methods in this paper. Finally the advantages of the method are verified by simulation to achieve the design expectations.

Enhancing Underwater Robot Manipulators with a Hybrid Sliding Mode Controller and Neural-Fuzzy Algorithm

“…This study emphasizes the significance of unmanned underwater machines. These scholarly documents collectively explore remotely operated vehicles (ROVs) for inspection purposes, encompassing a comprehensive review of inspection-class ROVs, the development of an intelligent support system for ROV operators to enhance real-world performance, and the introduction of a novel control method utilizing terminal sliding mode and dynamic damping to improve fault tolerance and predictive capabilities for tracked ROVs [1][2][3], highlighting the roles of robotic arms. These studies also investigate the impact of machining trajectory on grinding force for complex-shaped stone by a robotic manipulator, apply adaptive neural-PID visual servoing tracking control using an Extreme Learning Machine (ELM), and model impedance control with limited interaction power for a 2R planar robot arm [4][5][6] or manipulators [7,8] in conducting complex underwater tasks beyond human reach.…”