**1. Introduction**

146 Autonomous Underwater Vehicles

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Unmanned underwater vehicles (UUVs) are increasingly being used by civilian and defence operators for ever more complex and dangerous missions. This is due to the underlying characteristics of safety and cost effectiveness when compared to manned vehicles. UUVs require no human operator be subject to the conditions and dangers inherent in the underwater environment that the vehicle is exposed to, and therefore the risk to human life is greatly minimised or even removed. Cost effectiveness, in both time and financial respects, comes from a much smaller vehicle not containing the various subsystems required to sustain life whilst underwater, as well as smaller, less powerful actuators not placing the same levels of stress and strain on the vehicles as compared to a manned vehicle. This leads to a much smaller team required to undertake the regular maintenance needed to keep a vehicle operational. Taking these two main factors into account, the progression from manned vehicles to unmanned vehicles is a logical step within the oceanographic industry.

Within the broad class of UUVs are the remotely operated vehicles (ROVs) and the autonomous underwater vehicles (AUVs). Both of these types of vehicles have been successfully used in industry, and their fundamental differences determine which type of vehicle is suited to a particular mission. The key difference between the two is that an ROV requires a tether of some description back to a base station, whereas an AUV does not. This tether connects the ROV to a human operator who can observe the current state of the vehicle and therefore provide the control for the vehicle while it executes its mission. This tether, depending on the configuration of the vehicle, can also provide the electricity to power the vehicles actuators, sensors and various internal electronic systems.

AUVs have an advantage over ROVs of not requiring this tether, which leads to two main benefits. Firstly, an AUV requires little or no human interaction while the vehicle is executing its mission. The vehicle is pre-programmed with the desired mission objectives and, upon launch, attempts to complete these objectives without intervention from personnel located at the base station. This minimises the effect of human error while the vehicle is operational. The second benefit is the increased manoeuvrability that is possible without a cable continuously attached to the AUV. This tether has the potential to become caught on underwater structures, which could limit the possible working environments of an ROV, as well as cause drag on the motion of the vehicle, thus affecting its manoeuvring

Fully Coupled 6 Degree-of-Freedom Control of an Over-Actuated Autonomous Underwater Vehicle 149

As previously stated, the various components that make up the autonomy architecture of AUVs are the guidance system, navigation system, and control system. All three of these systems have their own individual tasks to complete, yet must also work cooperatively in order to reliably allow a vehicle to complete its objectives. Figure 1 shows a block diagram

The guidance system is responsible for producing the desired trajectory for the vehicle to follow. This task is completed by taking the desired waypoints defined pre-mission and, with the possible inclusion of external environmental disturbances, generates a path for the vehicle to follow in order to reach each successive waypoint (Fossen, 1994, 2002). Information regarding the current condition of the vehicle, such as actuator configuration and possible failures, can also be utilised to provide a realistic trajectory for the vehicle to follow. This trajectory then forms the desired state of the vehicle, as it contains the desired

The navigation system addresses the task of determining the current state of the vehicle. For surface, land and airborne vehicles, global positioning system (GPS) is readily available and is often used to provide continuous accurate positioning information to the navigation system. However, due to the extremely limited propagation of these signals through water, GPS is largely unavailable for underwater vehicles. The task of the navigation system is then to compute a best estimate of the current state of the vehicle based on multiple measurements from other proprioceptive and exteroceptive sensors, and to use GPS only when it is available. This is completed by using some form of sensor fusion technique, such as Kalman filtering or Particle filtering (Lammas et al., 2010, 2008), to obtain a best estimate of the current operating condition, and allow for inclusion of a correction mechanism when GPS is available, such as when the vehicle is surfaced. Overall, the task of the navigation system is to provide a best estimate of the current state of the vehicle, regardless of what

**2.1 Requirements** 

**2.1.1 Guidance** 

**2.1.2 Navigation** 

sensor information is available.

of how these various systems interact.

Fig. 1. Guidance, Navigation and Control Block Diagram.

position, orientation, velocity, and acceleration information.

performance. The possible range of the vehicle from the base station is also restricted, depending on the length of this tether. These two main benefits of AUVs over ROVs lead, in principle, to autonomous vehicles being selected for survey tasks in complex, dynamic and dangerous underwater environments, and therefore AUVs are the subject of this chapter. Furthermore, combining the desired performance characteristics of AUVs, with the aforementioned complex operation environment, leads to the conclusion that controllers implemented within AUVs must be precise and accurate, as well as robust to disturbances and uncertainties. Hence, the focus of this chapter will primarily be on the precise and robust control of AUVs.

Within the autonomy architecture of AUVs are three main systems. These are:- the *guidance system*, which is responsible for generating the trajectory for the vehicle to follow; the *navigation system*, which produces an estimate of the current state of the vehicle; and the *control system*, which calculates and applies the appropriate forces to manoeuvre the vehicle (Fossen, 2002). This chapter will focus on the control system and its two principal subsystems, namely the *control law* and the *control allocation*.

The chapter will be divided into three main parts with the first part focusing on the design and analysis of the control law, the second looking at control allocation, and the third providing an example of how these two systems combine to form the overall control system. Within the control law design and analysis section, the requirements of how the various systems within an AUV interact will be considered, paying particular attention to how these systems relate to the control system. An overview of the underwater environment will be given, which depicts the complexity of the possible disturbances acting on a vehicle. This will be followed by an analysis of the equations of motion, namely the kinematic and kinetic equations of motion that determine how a rigid body moves through a fluid. A summary of the relevant frames of reference used within the setting of underwater vehicles will be included. A review of the control laws that are typically used within the context of underwater vehicles will be conducted to conclude this section of the chapter.

The second section will look at the role of control allocation in distributing the desired control forces across a vehicle's actuators. An analysis of the principal types of actuators currently available to underwater vehicles will be conducted, outlining their useful properties, as well as their limitations. This section will conclude with an overview of various techniques for performing control allocation, with varying degrees of computational complexity.

The third and final section of this chapter will present an example of an overall control system for implementation within the architecture of AUVs. This example will demonstrate how the control law and control allocation subsystems interact to obtain the desired trajectory tracking performance while making use of the various actuators on the vehicle.
