Command governor adaptive control for unmanned underwater vehicles with measurement noise and actuator dead-zone

Abstract

Unmanned Underwater Vehicles (UUVs) are being deployed in advanced applications that require precise manoeuvring close to complex underwater structures such as oilrigs and subsea installations or moving objects such as submarines. The effect of vehicle hydrodynamic parameter variations is significant in such scenarios and in extreme conditions the UUV may experience loss of control. In addition, external disturbances present in these environments degrade the controllability of the UUV. Adaptive control has been identified as a promising solution that can improve the controllability in such situations. Nevertheless, adaptive control is not widely used within the industry mainly due to the trade-off between fast learning and smooth control signals. The Command Governor Adaptive Control (CGAC) has recently been proposed as a better compromise between the two extremes. In this paper, the performance of CGAC is investigated in the presence of measurement noise and actuator dead-zone. Simulation results show that that the CGAC is highly effective in retaining good tracking performance even in the presence of significant noise within the feedback signals and an unknown dead-zone in the actuator.