Indirect adaptive output feedback control of a biorobotic AUV using pectoral-like mechanical fins

Abstract

This paper treats the question of servoregulation of autonomous underwater vehicles (AUVs) in the yaw plane using pectoral-like mechanical fins. The fins attached to the vehicle have oscillatory swaying and yawing motion. The bias angle of the angular motion of the fin is used for the purpose of control. Of course, the design approach considered here is applicable to AUVs for other choices of oscillation patterns of the fins, which produce periodic forces and moments. It is assumed that the vehicle parameters, hydrodynamic coefficients, as well the fin forces and moments are unknown. For the trajectory control of the yaw angle, a sampled-data indirect adaptive control system using output (yaw angle) feedback is derived. The control system has a modular structure, which includes a parameter identifier and a stabilizer. For the control law derivation, an internal model of the exosignals (reference signal (constant or ramp) and constant disturbance) is included. Unlike the direct adaptive control scheme, the derived control law is applicable to minimum as well as nonminimum phase biorobotic AUVs (BAUVs). This is important, because for most of the fin locations on the vehicle, the model is a nonminimum phase. In the closed-loop system, the yaw angle trajectory tracking error converges to zero and the remaining state variables remain bounded. Simulation results are presented which show that the derived modular control system accomplishes precise set point yaw angle control and turning maneuvers in spite of the uncertainties in the system parameters using only yaw angle feedback.

Multi-input submarine control via ℒ1 adaptive feedback despite uncertainties

“…With larger G, the pitch angle deviation gets smaller, but it is not decreasing monotonically. Of course, use of extremely large G is not preferred because it causes numerical difficulty while integrating the stiff differential equation (25). To examine the robustness of the control system, simulation is done in the presence of random disturbance force Z d (t) and moment M d (t) for a u = 0:4 (60% lower uncertainty) and a u = 1:6 (60% higher uncertainty), respectively.…”

“…In view of equation ( 25), one finds that the choice of large adaptation gain G yields rapid changes in the estimated parameters (m,ŝ,V i ), and thereby achieves fast adaptation. Substituting equation (25) in equation (24) gives…”

“…21 An indirect adaptive control method for an AUV based on an extended Kalman filter has been proposed. 22 Control systems for biorobotic autonomous underwater vehicles (BAUVs) using pectoral fins 23–25 have also been designed. These adaptive sampled-data pectoral fin control systems are for yaw-plane as well as dive-plane control of BAUVs.…”

Nonlinear adaptive trajectory control of multi-input multi-output submarines with input constraints

“…17–20 Attempts have also been made to design biology-inspired control systems for the control of AUVs using pectoral-like oscillating fins. 23–25 For AUVs optimal-trajectory-planning using genetic algorithms has also been proposed. 26…”

Biology‐Inspired Robust Dive Plane Control of Non‐Linear AUV Using Pectoral‐Like Fins

“…Based on exact discrete-time models of BAUVs (Singh et al 2004;Narasimhan et al 2006), sampled-data control systems have been developed. For BAUV models with parametric uncertainties, discrete-time adaptive laws have been also designed (Naik and Singh 2007;Naik et al 2009). Of course, exact discretisation is not possible for non-linear models of BAUVs.…”