Optimally-robust nonlinear control of a class of robotic underwater vehicles

Abstract

The subject of this dissertation is the optimally-robust nonlinear control of a class
\nof robotic underwater vehicles (RUVs). The RUV class is characterized by high fineness
\nratios (length-to-diameter), axial symmetry, and passive roll stability. These vehicles are
\noptimized for robotic applications needing power efficiency for long-range autonomous
\noperations and motion stability for sensor performance improvement. A familiar example
\nis the REMUS vehicle.
\nThe particular robot class is further identified by an inconsistent actuator
\narrangement where the number of inputs is fewer than the number of degrees of freedom,
\nby the loss of controllability at low surge speeds due to the use of fin-based control
\nactuation, and by an inherent heading instability. Therefore, this important type of RUV
\ncomprises an interesting and challenging class of systems to study from a control
\ntheoretic perspective. 
\nThe optimally-robust nonlinear control method combines sliding mode control
\nwith stochastic state and model uncertainty estimation. First a regular form sliding mode
\ncontrol law is developed for the heading and depth control of the RUV class. The
\nParticle Filter algorithm is then modified and applied to the particular case of estimating
\nnot only the RUV state for control feedback but also the functional uncertainty associated
\nwith partially modeled shallow water wave disturbances. The functional uncertainty
\nestimate is used to dynamically adjust the sliding mode controller performance term gain
\naccording to the estimate of the wave phase and the RUV’s orientation with respect to the
\npredominate wave direction. As a result, the RUV experiences increased performance
\nover constant gain and Kalman Filter methods in terms of heading stability which
\nincreases effectiveness and decreased actuator power consumption which increases the
\nRUV mission time. The proposed technique is general enough to be applied to other
\nsystems.
\nAn experimental RUV was designed and constructed to compare the performance
\nof the regular form sliding mode controller with the conventional PID-type controller. It
\nis demonstrated that the more complicated formulas of the regular form sliding mode
\ncontroller can still be implemented real-time in an embedded system and that the
\ncontroller’s performance with regard to modeling uncertainty justifies the added
\ncomplexity.