Asymptotically Stable Observer-based Controller for Attitude Tracking with Systematic Convergence

Abstract

This paper proposes a novel unit-quaternion observer-based controller for attitude tracking (attitude and angular velocity) with guaranteed transient and steady-state performance. The proposed approach is computationally cheap and can operate based on measurements provided, for instance by a typical low-cost inertial measurement unit (IMU) or magnetic, angular rate, and gravity (MARG) sensor without the knowledge of angular velocity. First, an observer evolved on ${\mathbb{S}}^3\times {\mathbb{R}}^3$ is developed guaranteeing asymptotic stability of the closed loop error signals starting from any initial condition. Afterwards, the observer is combined with the proposed controller such that the observer-based controller ensures asymptotic stability of the closed loop error signals starting from any initial condition. Simulation performed in discrete form at low sampling rate reveals the robustness and effectiveness of the proposed approach. Keywords: Observer-based controller, attitude, estimation, control, MARG, IMU, asymptotic stability.

References in corpus (6)

• Systematic Convergence of Nonlinear Stochastic Estimators on the Special Orthogonal Group SO(3)
• Geometric Stochastic Filter with Guaranteed Performance for Autonomous Navigation based on IMU and Feature Sensor Fusion
• Landmark and IMU Data Fusion: Systematic Convergence Geometric Nonlinear Observer for SLAM and Velocity Bias
• A Geometric Nonlinear Stochastic Filter for Simultaneous Localization and Mapping
• Nonlinear Filter for Simultaneous Localization and Mapping on a Matrix Lie Group using IMU and Feature Measurements
• Attitude Determination and Estimation using Vector Observations: Review, Challenges and Comparative Results