Abstract
The motion of an underwater vehicle is prone to be affected by time-varying model parameters and the actuator limitation in control practice. Adaptive control is an effective method to deal with the general system dynamic uncertainties and disturbances. However, the effect of disturbances control on transient dynamics is not prominent. In this paper, we redesign the L 1 adaptive control architecture (L1AC) with anti-windup (AW) compensator to guarantee robust and fast adaption of the underwater vehicle with input saturation and coupling disturbances. To reduce the fluctuation of vehicle states, the Riccati-based AW compensator is utilized to compensate the output signal from L1AC controller via taking proper modification. The proposed method is applied to the pitch channel of REMUS vehicle’s six Degrees Of Freedom (DOF) model with strong nonlinearities and compared with L1AC baseline controller. Simulations show the effectiveness of the proposed control strategy compared to the original L1AC. Besides, the fluctuation in roll channel coupled with pitch channel is suppressed according to the performances of control tests.
Highlights
Underwater vehicle has been widely used in applications such as underwater oil and gas extraction, resource exploration, and monitoring operations, which bring practical challenges for developing underwater systems with better performance
A control strategy is put forward to deal with challenges in underwater vehicle control practice
Considering unmodeled uncertainties and coupling disturbances in underwater vehicle system, L1 adaptive control is employed as the control architecture to guarantee robustness and fast adaption
Summary
Underwater vehicle has been widely used in applications such as underwater oil and gas extraction, resource exploration, and monitoring operations, which bring practical challenges for developing underwater systems with better performance. Underwater vehicle working system is prone to be affected by many factors including system dynamics, navigation, motion control and path planning [1]. The controller is required to have the ability to deal with fundamental problems such as actuator saturation, adaptation to changes in model parameters along with the vibrations caused by coupling motions [1,2,3]. PID (Proportional–Integral–Derivative) control with simple structure regarded as model free control has been widely used in the attitude and position control of autonomous vehicles operating underwater or flying in the air. The accuracy of the tasks performed and the complexity of underwater environments, as well as dynamic nonlinearities of model and measurement errors caused by sensors, make adaptive control a better solution [5,6,7,8,9]
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