Frequency‐shifting‐based algebraic approach to stable on‐line parameter identification and state estimation of multirotor UAV

Self Cite

In this paper, a frequency-shifting-based (FSB) algebraic approach to the extended state observer (ESO) design is proposed. The proposed algebraic approach provides almost instantaneous convergence toward the exact values of the system states and disturbances. The main benefit of the proposed approach is the elimination of the peaking phenomenon, which is inevitable in the case of the conventional observer design. In comparison with the linear ESO, the proposed algebraic ESO is less sensitive to the choice of the observer bandwidth, and it is more robust to the measurement noise. The simulation and experimental results illustrate the efficiency of the proposed algebraic approach in comparison with the linear ESO.

“…The singularity of the matrix C(t) in the time instant t = 0 can be avoided by the evaluation in t ≥ > 0, where is some small positive parameter [22,31].…”

Section: Output Equationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Frequency‐shifting‐based algebraic approach to extended state observer design

Kasač

Pender

Pranjic

et al. 2021

Self Cite

“…The past decade has seen a steady increase of interest in nonlinear system identification [1][2][3][4]. Popular nonlinear model structures are, among others, nonlinear state space models [5][6][7], NARX and NARMAX models [8], and block-oriented nonlinear models [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Identification of nonlinear system composed of parallel coupling of Wiener and Hammerstein models

Brouri

Kadi

Lahdachi

2021

In this paper, a new method for the identification of nonlinear system composed by the Wiener and Hammerstein models connected in parallel is presented. This block-oriented nonlinear system is a more general nonlinear model than Wiener and Hammerstein ones. The proposed nonlinear structure can easily describe the Wiener and Hammerstein models. Then, most of existing works are focused on the identification of one of the two models or the cascade connection of these two models. In this study, the parameters identification of linear and nonlinear blocks can be performed using one stage. Then, simple sine or multi-sine waves were applied to the system input. Unlike several other methods, the linear elements can be parametric or not.

“…However, despite its great advantages, there are issues commonly encountered while implementing LSM in real time applications, for example, disturbances and noise in the inertial measurements, which are used by the algorithm as inputs to estimate the system parameters. Authors in [9] developed a frequency-shifting-based (FSB) algebraic approach to stable on-line parameter identification and state estimation applied to a multirotor adaptive-like tracking control assuming that only position measurement is available.…”

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confidence: 99%

Parameter estimation and control of an unmanned aircraft‐based transportation system for variable‐mass payloads

Alatorre

Espinoza

Sanchez

et al. 2021

This paper deals with the development of an adaptive robust controller for an Unmanned Aircraft System with variable mass. The goal is to improve trajectory tracking and energy performance while the aircraft mass is gradually reducing due to payload release. To improve the trajectory tracking performance, we propose an algorithm that merges the concepts of least squares method and sliding mode observer for the estimation of the vehicle mass. The nonlinear observer estimates the linear velocities and accelerations, which are further used to obtain the vehicle mass. A robust adaptive pole placement controller based on the Attractive Ellipsoid Method uses this estimation to update the controllers gains due to the mass variation. To validate the effectiveness of the proposed algorithm for performing aerial transportation and deployment of payloads, we present a numerical example comparing the performance of the proposed method with respect to using Proportional Derivative controllers as well as Robust Controllers. KEYWORDSload transportation, model in the loop, nonlinear observer, robust adaptive control, UAS, variable mass 1 INTRODUCTION Diverse research works have explored original solutions for the Unmanned Aircraft System (UAS)-based payload transportation problem for constant and variable mass payloads. As a few examples, the authors in Kui et al. [1]developed an autonomous vehicle to transport a payload by using a tensor embedded in the vehicle, while the authors in Geng and Langelaan [2] designed strategies for load transportation that involves a team of cooperative vehicles. Previously, the authors in Haus et al. [3] presented the MORUS project where they conducted the