Robust trajectory tracking control for an underactuated autonomous underwater vehicle based on bioinspired neurodynamics

Abstract

This article investigates the three-dimensional trajectory tracking control problem for an underactuated autonomous underwater vehicle in the presence of parameter perturbations and external disturbances. An adaptive robust controller is proposed based on the velocity control strategy and adaptive integral sliding mode control algorithm. First, the desired velocities are developed using coordinate transformation and the backstepping method, which is the necessary velocities for autonomous underwater vehicle to track the time-varying desired trajectory. The bioinspired neurodynamics is used to smooth the desired velocities, which effectively avoids the jump problem of the velocity and simplifies the derivative calculation. Then, the dynamic control laws are designed based on the adaptive integral sliding mode control to drive the underactuated autonomous underwater vehicle to sail at the desired velocities. At the same time, the auxiliary control laws and the adaptive laws are introduced to eliminate the influence of parameter perturbations and external disturbances, respectively. The stability of the control system is guaranteed by the Lyapunov theorem, which shows that the system is asymptotically stable and all tracking errors are asymptotically convergent. At the end, numerical simulations are carried out to demonstrate the effectiveness and robustness of the proposed controller.

Underactuated robotics: A review

“…It studies the 3-D trajectory tracking control problems for underactuated AUVs in the presence of parametric disturbances and external disturbances. 185 Based on the speed control strategy and the adaptive integral SMC algorithm, an adaptive robust controller is proposed. 186 Based on a novel Nussbaum-type function, Huang et al 187 proposed an adaptive control scheme for a class of strictly feedback nonlinear systems.…”

Platoon control design for unmanned surface vehicles subject to input delay

“…Parameters A , B , and D are nonnegative constants, namely, the passive decay rate, the upper and the lower bounds of the neural activity, respectively. The variables and represent the excitatory and inhibitory inputs, respectively 28 – 30 . The bioinspired model can be regarded as a low-pass filter.…”

Fuzzy observer‐based tracking control of an underactuated underwater vehicle with linear velocity estimation

“…In [24], based on the theory of complementary filters, a current velocity observer was designed. Readers can refer to [25][26][27][28][29][30][31] for more information about Lyapunov, observer and sliding mode controlbased disturbance rejection etc. Moreover, the authors in [32] proposed a reference-shaping adaptive control method to deal with disturbances.…”

“…(ii) Developing an observer to estimate the linear velocity. Unlike the controllers reported in [17,18,30,31], where all the states of the system are available, we consider the condition that linear velocity is unachievable. Moreover, modelling uncertainties and external time-varying disturbances are considered in our work, while the authors in [22,23] assumed external disturbances are constants.…”