Multivariable self-tuning autopilots for autonomous and remotely operated underwater vehicles

Abstract

The effectiveness of subsea intervention has been found to be dependent upon the capability of an Autonomous Underwater Vehicle's (AUV's) or Remotely Operated Underwater Vehicle's (ROV's) autopositioning system. However, these vessels' dynamics vary considerably with operating condition, are strongly coupled, and are expensive and difficult to derive, theoretically or by conventional testing, making the design of conventional autopilots difficult to achieve. Multi-inputhultioutput self-tuning controllers are a possible solution. Two such schemes are presented; the first is an implicit linear quadratic on-line self-tuning controller, and the other uses a robust control law based on a first-order approximation of the open-loop dynamics and on-line recursive identification. The performance of these controllers is evaluated by examining their behavior when controlling a comprehensive nonlinear simulation of an ROV and its navigation system. An interesting off-shoot of this study is the application of recursive system identification techniques to the derivation of ROV models from trials data; the potential advantages of this method are discussed.

Modelling, Design and Robust Control of a Remotely Operated Underwater Vehicle

“…The control shows asymptotic tracking of the motion trajectory without requiring current measurements and a priori exact system dynamics knowledge. Self-tuning autopilots are suggested in [15], wherein two schemes are presented: the first one is an implicit linear quadratic online self-tuning controller and the other one uses a robust control law based on a first-order approximation of the open-loop dynamics and online recursive identification. Controller performance is evaluated by simulation.…”

Nonlinear RISE-Based Control of an Autonomous Underwater Vehicle

“…where U : R 19 → R is positive definite function defined as U c z 2 , for some positive constant c ∈ R. The inequalities in (20) and (25) can be used to show that V L ∈ L ∞ , thus, e 1 , e 2 , r, P ∈ L ∞ . Given that e 1 , e 2 ∈ L ∞ , standard linear analysis can be used to show thatė 1 ,ė 2 ∈ L ∞ from (6) and Assumption 1.…”

Nonlinear Control Methodologies for Tracking Configuration Variables

“…The equations of motion of such vehicles are highly nonlinear, time-varying and coupled due to hydrodynamic added mass, lift, drag, Coriolis and centripetal forces, which are acting on the vehicle and generally include uncertainties (Fossen & Sagatun, 1991b). Detailed discussions on modeling and system identification techniques are given in (Fossen, 1994) and (Goheen & Jefferys, 1990). It is convenient to write the equations of motion in accordance with the Society of National Architects and Marine Engineers (SNAME, 1950).…”