Underwater walking robot (UWR) is a kind of autonomous underwater vehicles which can walk underwater. In this work, the fixed-time tracking control problem of UWR with external disturbances, error constraints, and actuator faults is investigated. An interval type-2 fuzzy neural network approximator is designed to tackle nonlinear uncertainties, and a novel prescribed performance terminal sliding-mode surface is proposed to handle error constraints. Furthermore, two fault-tolerant controllers are given, where one is nonsingular and the other has higher steady-state precision. According to Lyapunov theory, the proposed controllers can guarantee that system states will converge to the expected values in a fixed time. Simulation results demonstrate the effectiveness of the proposed control strategies.

水下步行机器人（UWR）是一种可以在水下行走的自主水下航行器。在这项工作中，研究了具有外部干扰，误差约束和执行器故障的UWR的固定时间跟踪控制问题。设计了一种区间2型模糊神经网络逼近器来解决非线性不确定性问题，提出了一种新型的规定性能终端滑模曲面来处理误差约束。此外，给出了两个容错控制器，其中一个是非奇异的，另一个具有更高的稳态精度。根据李雅普诺夫理论，提出的控制器可以保证系统状态在固定时间内收敛到期望值。仿真结果证明了所提出的控制策略的有效性。