Active fault-tolerant anti-input saturation control of a cross-domain robot based on a human decision search algorithm and RBFNN - Wang, Ke; Liu, Yong; Huang, Chengwei (Frontiers in Neurorobotics, 2023)
This paper presents a cross-domain robot (CDR) that experiences drive efficiency degradation non-singular terminal sliding mode controller (NTSMC) and a RBFNN. The RBFNN is used to estimate the impact of drive faults, water resistance and model parameter uncertainty on the robot and the output value compensates the controller. Additionally, an anti-input saturation control algorithm is designed to prevent driver saturation. To optimize the controller parameters, a human decision search algorithm (HDSA) is proposed, which mimics the decision-making process of a crowd. Simulation results demonstrate the effectiveness of the proposed control methods. when operating on water surfaces, similar to drive faults. Moreover, the CDR mathematical model has uncertain parameters and non-negligible water resistance. To solve these problems, a radial basis function neural network (RBFNN)-based active fault tolerant control (AFTC) algorithm is proposed for the robot both on land and water surfaces. The proposed algorithm consists of a fast