3 research outputs found
Guidance and control of an autonomous underwater vehicle
Merged with duplicate record 10026.1/856 on 07.03.2017 by CS (TIS)A cooperative project between the Universities of Plymouth and Cranfield was aimed
at designing and developing an autonomous underwater vehicle named Hammerhead.
The work presented herein is to formulate an advance guidance and control system
and to implement it in the Hammerhead. This involves the description of Hammerhead
hardware from a control system perspective. In addition to the control system,
an intelligent navigation scheme and a state of the art vision system is also developed.
However, the development of these submodules is out of the scope of this thesis.
To model an underwater vehicle, the traditional way is to acquire painstaking mathematical
models based on laws of physics and then simplify and linearise the models to
some operating point. One of the principal novelties of this research is the use of system
identification techniques on actual vehicle data obtained from full scale in water
experiments. Two new guidance mechanisms have also been formulated for cruising
type vehicles. The first is a modification of the proportional navigation guidance for
missiles whilst the other is a hybrid law which is a combination of several guidance
strategies employed during different phases of the Right.
In addition to the modelling process and guidance systems, a number of robust control
methodologies have been conceived for Hammerhead. A discrete time linear
quadratic Gaussian with loop transfer recovery based autopilot is formulated and integrated
with the conventional and more advance guidance laws proposed. A model
predictive controller (MPC) has also been devised which is constructed using artificial
intelligence techniques such as genetic algorithms (GA) and fuzzy logic. A GA
is employed as an online optimization routine whilst fuzzy logic has been exploited
as an objective function in an MPC framework. The GA-MPC autopilot has been
implemented in Hammerhead in real time and results demonstrate excellent robustness
despite the presence of disturbances and ever present modelling uncertainty. To
the author's knowledge, this is the first successful application of a GA in real time
optimization for controller tuning in the marine sector and thus the thesis makes an
extremely novel and useful contribution to control system design in general. The
controllers are also integrated with the proposed guidance laws and is also considered
to be an invaluable contribution to knowledge. Moreover, the autopilots are used in
conjunction with a vision based altitude information sensor and simulation results
demonstrate the efficacy of the controllers to cope with uncertain altitude demands.J&S MARINE LTD., QINETIQ,
SUBSEA 7 AND SOUTH WEST WATER PL
AN INTELLIGENT NAVIGATION SYSTEM FOR AN AUTONOMOUS UNDERWATER VEHICLE
The work in this thesis concerns with the development of a novel multisensor data fusion
(MSDF) technique, which combines synergistically Kalman filtering, fuzzy logic
and genetic algorithm approaches, aimed to enhance the accuracy of an autonomous
underwater vehicle (AUV) navigation system, formed by an integration of global positioning
system and inertial navigation system (GPS/INS).
The Kalman filter has been a popular method for integrating the data produced
by the GPS and INS to provide optimal estimates of AUVs position and attitude. In
this thesis, a sequential use of a linear Kalman filter and extended Kalman filter is
proposed. The former is used to fuse the data from a variety of INS sensors whose
output is used as an input to the later where integration with GPS data takes place.
The use of an adaptation scheme based on fuzzy logic approaches to cope with the
divergence problem caused by the insufficiently known a priori filter statistics is also
explored. The choice of fuzzy membership functions for the adaptation scheme is first
carried out using a heuristic approach. Single objective and multiobjective genetic
algorithm techniques are then used to optimize the parameters of the membership
functions with respect to a certain performance criteria in order to improve the overall
accuracy of the integrated navigation system. Results are presented that show
that the proposed algorithms can provide a significant improvement in the overall
navigation performance of an autonomous underwater vehicle navigation.
The proposed technique is known to be the first method used in relation to AUV
navigation technology and is thus considered as a major contribution thereof.J&S Marine Ltd.,
Qinetiq, Subsea 7 and South West Water PL