Attitude Estimation and Control Using Linear-Like Complementary Filters: Theory and Experiment

This paper proposes new algorithms for attitude estimation and control based on fused inertial vector measurements using linear complementary filters principle. First, n-order direct and passive complementary filters combined with TRIAD algorithm are proposed to give attitude estimation solutions. These solutions which are efficient with respect to noise include the gyro bias estimation. Thereafter, the same principle of data fusion is used to address the problem of attitude tracking based on inertial vector measurements. Thus, instead of using noisy raw measurements in the control law a new solution of control that includes a linear-like complementary filter to deal with the noise is proposed. The stability analysis of the tracking error dynamics based on LaSalle's invariance theorem proved that almost all trajectories converge asymptotically to the desired equilibrium. Experimental results, obtained with DIY Quad equipped with the APM2.6 auto-pilot, show the effectiveness and the performance of the proposed solutions.Comment: Submitted for Journal publication on March 09, 2015. Partial results related to this work have been presented in IEEE-ROBIO-201

A global observer for attitude and gyro biases from vector measurements

We consider the classical problem of estimating the attitude and gyro biases of a rigid body from vector measurements and a triaxial rate gyro. We propose a simple "geometry-free" nonlinear observer with guaranteed uniform global asymptotic convergence and local exponential convergence; the stability analysis, which relies on a strict Lyapunov function, is rather simple. The excellent behavior of the observer is illustrated through a detailed numerical simulation

Non-linear Symmetry-preserving Observer on Lie Groups

In this paper we give a geometrical framework for the design of observers on finite-dimensional Lie groups for systems which possess some specific symmetries. The design and the error (between true and estimated state) equation are explicit and intrinsic. We consider also a particular case: left-invariant systems on Lie groups with right equivariant output. The theory yields a class of observers such that error equation is autonomous. The observers converge locally around any trajectory, and the global behavior is independent from the trajectory, which reminds of the linear stationary case.Comment: 12 pages. Submitted. Preliminary version publicated in french in the CIFA proceedings and IFAC0

Rigid Body Attitude Estimation: An Overview and Comparative Study

The attitude estimation of rigid body systems has attracted the attention of many researchers over the years. The development of efficient estimation algorithms that can accurately estimate the orientation of a rigid body is a crucial step towards a reliable implementation of control schemes for underwater and flying vehicles. The primary focus of this thesis consists in investigating various attitude estimation techniques and their applications. Two major classes are discussed. The first class consists of the earliest static attitude determination techniques relying solely on a set of body vector measurements of known vectors in the inertial frame. The second class consists of dynamic attitude estimation and filtering techniques, relying on body vector measurements as well other measurements, and using the dynamical equations of the system under consideration. Various attitude estimation algorithms, including the latest nonlinear attitude observers, are presented and discussed, providing a survey that covers the evolution and structural differences of these estimation methods. Simulation results have been carried out for a selected number of such attitude estimators. Their performance in the presence of noisy measurements, as well as their advantages and disadvantages are discussed