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Zhu et al. Intell Robot 2022;2(3):200­222 I http://dx.doi.org/10.20517/ir.2022.13 Page 214

Figure 7. Tracking trajectory comparison of the bio-inspired model-based control and conventional backstepping control for the underwater
robots: (A) curve tracking; and (B) helix tracking [108] .

GA methods are also applied in the intelligent control of UUVs. They are usually applied based on the aim
of addressing the most optimal solution during the control process owing to their feature of self-evolution.
However, the computation cost of the GA methods always adds a burden to the tracking control algorithms
such that they are usually combined with other intelligent algorithms to reach a more efficient control strategy.
Tavanaei–Sereshki applied the quantum genetic algorithm (QGA), an optimization algorithm based on the
probability that combines the idea of quantum computing and traditional genetic algorithm to realize the
UUV’s tracking along desired paths [110] . Zhang described a route planner that enables an AUV to selectively
complete part of the predetermined tasks in the operating ocean area when the local path cost is stochastic
through a greedy strategy-based GA (GGA), which includes a novel rebirth operator that maps infeasible
individuals into the feasible solution space during evolution to improve the efficiency of the optimization and
uses a differential evolution planner for providing the deterministic local path cost [111] .

A brief summary of intelligent controls on UUVs can be found in Table 4. The details of various intelligent
methods for tracking control of UUV are described in Section 3.2.

3.3. Fault­tolerant control
Regarding the unpredictability of the underwater environment, it is of high possibility for the UUV to meet
unexpectedaccidentsthataffectthepresetmodelofthevehicle. Forexample, insomecases, oneormoreofthe
UUV’sthrustersareoutoforder,andthemodelneedstobemodifiedtocontinuethedesiredtrajectorytracking
designed as before. Fault-tolerant control (FTC) is usually applied to alleviate abrupt errors and provides the
most feasible solution when inevitable damages happen to the equipment in different fields [115] . However,
the FTC of underwater vehicles has not been thoroughly investigated due to the complexity brought by the
underwater environment and the UUV system [116–118] .

Several techniques on the FTC have been developed in the 21st century [119–122] . Based on these studies, the
design of the excessive number of thrusters compared to the number of degrees of freedom (DOF) is raised
and accepted as a resolution to the UUV FTC problem, which is called the thruster control matrix reconfigura-
tion [123,124] . For example, as shown in Figure 8, the Falcon and URIS UUVs have five thrusters while only four
DOFs are considered such that the reconfiguration method can be applied. For example, when an unexpected
fault of the vehicle’s thrusters occurs, the thrusters installed on the vehicle that exceed the number of DOFs
(six, i.e., surge, sway, heave, row, pitch, and yaw) have enough flexible space to be retuned to provide the re-
quired propulsion in the corresponding DOFs. To implement the thruster control matrix configuration theory