Nonlinear control of an autonomous underwater vehicle: A RISE-based approach

Abstract

Autonomous and remotely operated marine vehicles such as ships and submarines are becoming a key component in several aspects of maritime industry and defense. This paper explores the development of a nonlinear controller for a fully actuated autonomous underwater vehicle (AUV) using a robust integral of the sign of the error (RISE) feedback term with a neural network (NN) based feedforward term to achieve semi-global asymptotic tracking results in the presence of complete model uncertainty and unknown disturbances. A simulation is provided to demonstrate the proposed controller on an experimentally validated AUV model.

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.…”

“…From (25), [45,Corollary 1] can be invoked to show that c z (t) 2 → 0 as t → ∞ ∀y (0) ∈ S D . Based on the definition of z in (15), e 1 (t) → 0 as t → ∞ ∀y (0) ∈ S D .…”

“…Motivated by our previous work in [24] and preliminary efforts in [25], a continuous robust integral of the sign of the error (RISE) control structure is used to compensate for uncertain, nonautonomous disturbances for a class of coupled, fully-actuated underwater vehicles. A Lyapunov-based stability analysis is provided to show that the control method yields semiglobal asymptotic tracking.…”

Flatness-Based Adaptive Fuzzy Control of Autonomous Submarines

“…Moreover, submersible autonomous robots and submarines are exposed to strong perturbations due to variable sea conditions and sea currents. Therefore, it is important to develop feedback control schemes for AUVs and submarines that will be little dependent on prior and exact knowledge of the associated dynamic model and will exhibit sufficient robustness to perturbation inputs [4][5][6][7][8][9][10][11]. To this end, in the recent years several research results have been presented, in particular on robust control [12][13][14][15] and on adaptive control of AUVs [16][17][18][19].…”

A self tuning RISE controller formulation

“…In this methodology the integral of the sign of the error was utilized instead of the sign of error used in standard sliding mode controllers. This method was then referred as RISE (short for Robust Integral of Sign of Error) feedback [5] and have been successfully applied to a variety of nonlinear dynamical systems including autonomous flight control [6], underwater vehicle control [7], control of special classes of multiple input multiple output (MIMO) nonlinear systems [8], [9], and even time delay compensation [10]. Similar to that of most robust-type controllers, the RISE feedback makes use of a constant high gain to compensate the overall uncertainties in the continuously differentiable system dynamics.…”