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Velocity and Disturbance Robust Non-linear Estimator for Autonomous Surface Vehicles with Reduced Sensing Capabilities

Guillermo Bejarano, Sufiyan N-Yo, Luis Orihuela

Abstract

This paper presents a robust non-linear state estimator for autonomous surface vehicles, where the movement is restricted to the horizontal plane. It is assumed that only the vehicle position and orientation can be measured, being the former affected by bounded noises. Then, under some fair standard assumptions concerning the maximum velocities and acceleration rates of the vehicle, the estimator is able to reconstruct not only the velocities, but also the lumped generalised disturbances, that cluster external disturbances, non-linearities, and unmodelled dynamics. The observer is easily tunable by the user, with a set of four scalars, two of them related to the velocity of convergence of the estimator, and the other two parameters to set the desired trade-off between noise sensitivity and disturbance rejection. Several simulations with a well-known test-bed craft are provided to show how the proposed algorithm outperforms previous ones in the literature.

Velocity and Disturbance Robust Non-linear Estimator for Autonomous Surface Vehicles with Reduced Sensing Capabilities

Abstract

This paper presents a robust non-linear state estimator for autonomous surface vehicles, where the movement is restricted to the horizontal plane. It is assumed that only the vehicle position and orientation can be measured, being the former affected by bounded noises. Then, under some fair standard assumptions concerning the maximum velocities and acceleration rates of the vehicle, the estimator is able to reconstruct not only the velocities, but also the lumped generalised disturbances, that cluster external disturbances, non-linearities, and unmodelled dynamics. The observer is easily tunable by the user, with a set of four scalars, two of them related to the velocity of convergence of the estimator, and the other two parameters to set the desired trade-off between noise sensitivity and disturbance rejection. Several simulations with a well-known test-bed craft are provided to show how the proposed algorithm outperforms previous ones in the literature.
Paper Structure (12 sections, 2 theorems, 49 equations, 7 figures, 4 tables)

This paper contains 12 sections, 2 theorems, 49 equations, 7 figures, 4 tables.

Table of Contents

  1. Introduction
  2. Problem formulation
  3. Preliminaries
  4. ASV Dynamics
  5. Proposed Observer Structure
  6. Observer Design and Analysis
  7. Rotational Observer Design and Analysis
  8. Positional Observer Design and Analysis
  9. Simulation results
  10. Comparison with Similar Approaches
  11. Tuning Capabilities of the Proposed Observer
  12. Conclusions and future work

Key Result

Theorem III.1

Problem Problem_2 (i) is solved provided that the constant observer gain $\bm{L}_{\psi}$ is computed by solving the optimization problem eqRotationalOptimizationProblem and then applying eqRotationalObserverGain.

Figures (7)

  • Figure 1: Block diagram of the complete system
  • Figure 2: Estimation performance of the surge $u$ for two different estimators
  • Figure 3: Estimation performance of the sway disturbance $\sigma_v$ for two different estimators
  • Figure 4: Estimation performance of the surge $u$ for two different values of $\delta_{p,1}$
  • Figure 5: Estimation performance of the surge disturbance $\sigma_u$ for two different values of $\delta_{p,1}$
  • ...and 2 more figures

Theorems & Definitions (12)

  • Definition 1
  • Remark 1
  • Remark 2
  • Theorem III.1
  • proof
  • Remark 3
  • Remark 4
  • Remark 5
  • Theorem III.2
  • proof
  • ...and 2 more