P050

Robust Adaptive Control of AUVs :an Application to the CR-02 Vehicle

A0025 Y. Zhang Shenyang Institute of Automation, Chinese Academy of Sciences

A0014 H. H. Chen Shenyang Institute of Automation, Chinese Academy of Sciences

A0013 X. S. Feng Shenyang Institute of Automation, Chinese Academy of Sciences

Currently, most of AUVs are survey research vehicles. It is difficult

for AUVs to perform complicated subsea tasks such as subsea oil field

inspection and intervention, docking and recovery. Highly accuracy

dynamic positioning and target tracking of AUVs is one of the keys of

performing above tasks. Due to the poor precision of common control

method, new control methods must be adopted.

Affected by the hydrodynamics and the environment disturbance,

dynamics of AUVs are highly nonlinear, multi-! freedom coupled, and

time varying. Due to the uncertainty of the hydrodynamics and the

complexity of ocean environment, it is difficult to establish highly

accurate dynamics model of AUVs.

The environmental disturbance of the ocean includes wave, ocean

current and imbalance force. The imbalance force is brought from the

imbalance of vehicle structure and hydrodynamics, the imbalance force

model and the ocean current model both are 1st-order and slowly-

varying disturbance. Wave forces can be divided into 1st-order wave

disturbance and 2st-order wave drift force. In this paper, we

supposed the environmental disturbance of the ocean as the combination

of fundamental harmonic, 1st-order harmonic and 2nd-order harmonic.

Dynamics model of AUVs possesses two kinds of uncertainties: model

parameter uncertainty and model structure uncertainty. Aimed at above

uncertainties and the environmental disturbance, there are three

fundamental control methods: robust control, adap! tive control and

feed-forward control.

This paper presented a ro bust adaptive control law based on

backstepping in order to satisfy with dynamic positioning and target

tracking of highly accuracy. In this control system, environmental

disturbances are looked as an uncertain parameter, the state variable

and uncertain parameter enter the control system through the control

channel, and they satisfy with the matching conditions. The control

law is obtained by replacing the uncertain parameter with its

estimated parameter. The control law guarantees not only that the

state of the control system remains bounded, but also that it tends to

a desired constant value or asymptotically tracks a reference signal.

In this paper, the control system is based on full state feedback, the

state variables are acquired by filter from sensors data. In these

measurements, displacement data are available from Ultra-short base

line, Gyro and Glinometer, velocity data are measured by Doppler,

horizontal and vertical rate Gyro. Finally, full state variables!

are received by filter.

In this paper, this control law is applied to horizontal and vertical

closed-loop control of AUV CR-02.We made some simulations, and

compared with traditional PID controller, the performance has

obviously been improved on precision of dynamic positioning and target

tracking, especially under serious disturbance. Based on simulation,

we will carry out a pool test of AUV CR-02.