Model Identification and Controller Parameter Optimization for an Autopilot Design for Autonomous Underwater Vehicles

TL;DR

This paper develops a detailed nonlinear model of an autonomous underwater vehicle and uses it to optimize autopilot controller parameters through sea trial data, enhancing control accuracy.

Contribution

It introduces a comprehensive nonlinear model for AUVs and applies optimization algorithms for controller tuning based on real sea trial data.

Findings

Accurate nonlinear model of AUV developed

Optimized PID controller parameters via sea trial data

Successful autopilot performance verified in closed-loop trials

Abstract

Nowadays an accurate modeling of the system to be controlled is essential for reliable autopilot. This paper presents a non-linear model of the autonomous underwater vehicle 'CWolf'. Matrices and the corresponding coefficients generate a parameterized representation for added mass, Coriolis and centripetal forces, damping, gravity and buoyancy, using the equations of motion, for all six degrees of freedom. The determination of actuator behaviour by surge tests allows the conversion of propeller revolutions to the respective forces and moments. Based on geometric approximations, the coefficients of the model can be specified by optimization algorithms in 'open loop' sea trials. The realistic model is the basis for the subsequent design of the autopilot. The reference variables used in the four decoupled adaptive PID controllers for surge, heading, pitch and heave are provided a 'Line of Sight' - guidance system. A constraint criteria optimization determines the required controller parameters. The verification by 'closed loop' sea trials ensures the results.