Optimizing a Kalman filter with an evolutionary algorithm for nonlinear quadrotor attitude dynamics

Kaba, Aziz; Kiyak, Emre

doi:10.1016/j.jocs.2019.101051

Cited by 25 publications

(12 citation statements)

References 19 publications

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“…Define the unknown variables a = Y 2 + 1 Z and b = − 1 Z . Equations (30)-(33) can be written using Kirchhoff's Current Law (KCL) for each node Based on (30) and (31), V R can be eliminated, Based on (32) and (33), V G can be eliminated, Multiply V T to (34) and V S to (35) and then subtract the resultant equations. Then a can be expressed in terms of b,…”

Section: Mid-compensated Line With Known Current Through Series Compementioning

confidence: 99%

Kalman filter based method for tracking dynamic transmission line parameters

Zhang

Liao

2021

SN Appl. Sci.

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Transmission line parameters are required by various power system applications. Thus, it is important to develop accurate transmission line parameter estimation methods. This paper puts forward Kalman filter based methods to track the dynamically changing line parameters. The proposed methods can overcome the estimation inaccuracy problem caused by the effect of the noise in the measurements. The proposed methods are based upon the equivalent- circuit of long line and utilize voltage and current data recorded by the Phasor Measurement Units at both ends of the line. Non-compensated and differently configured series compensated lines have been considered in this paper. The case studies demonstrate that the proposed methods have the capability of dynamically tracking changing line parameters and yield accurate estimates with the presence of measurement noises.

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Section: Mid-compensated Line With Known Current Through Series Compementioning

confidence: 99%

Kalman filter based method for tracking dynamic transmission line parameters

Zhang

Liao

2021

SN Appl. Sci.

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“…The majority of quadrotors designs take advantage of the extended Kalman filter (EKF) for optimal full state vector estimation from measurements, especially in autonomous navigation under disturbance or in the presence of white Gaussian noise, as shown in [31,32]. Guo et al experimented with an EKF observer to enhance PID based H infinity control of multiple quadrotors [20], an evolutionary algorithm with principles of KF to tune unknown noises was optimized in [33], and other researchers have used virtual sensing based on EKF observer to develop a quadrotor controller [22]. Trajectory tracking and obstacle avoidance were tackled by many quadrotor projects.…”

Section: Introductionmentioning

confidence: 99%

A Novel Framework of Modelling, Control, and Simulation for Autonomous Quadrotor UAVs Utilizing Arduino Mega

Tran

Nguyen³

et al. 2022

Wireless Communications and Mobile Computing

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In recent decades, there has been a constant increase in the use of unmanned aerial vehicles (UAVs). There has also been a huge growth in the number of control algorithms to support the many applications embodied by the vehicles, including challenges and open issues to develop. This paper focuses on three major classes of control methods applied to quadrotors in order to create an open-source model based on the Arduino Mega that allows for the derivation and design of quadrotor control strategies. We consider the perspective classes, including linear, nonlinear, and intelligent methods representing in details with applications in developing an open-source controller for the quadrotor using the Arduino Mega and the BNO055 9 DOF sensor. We propose Proportional Integral Derivative (PID), backstepping integrator, and model predictive control (MPC) to track a generated Lissajous curve for surveillance. Simulations in the Matlab–Simulink environment with 3D visualization of a developed quadrotor model using CAD software, with robustness and performance discussion, are provided. Our experimental work is developed with an extensive illustration of the hardware and algorithm design and by demonstrating the effectiveness of the proposed architectures. The results show promise in practical and in intelligent applications.

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“…Traditional observer systems use several tuning parameters and most of them perform a linearization, e.g. [9], [10]. Also, some works consider more than 4 (out of 12) elements of the state vector as measured output, e.g.…”

Section: Introductionmentioning

confidence: 99%

Filtered Observer-Based IDA-PBC Control for Trajectory Tracking of a Quadrotor

et al. 2021

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In this paper, a new filtered observer-based IDA-PBC (Interconnection and Damping Assignment-Passivity Based Control) strategy is developed for trajectory tracking of a quadrotor in the presence of disturbances and model uncertainties. The proposed algorithm allows the control of the quadrotor in all its states. It can deal with the noisy output measurements and uncertainties in the translational and rotational dynamics, as unmodeled dynamics inherent to real systems or unknown external signals (exogenous signals). The designed filtered observer estimates the state from noisy output measurements, and it depends only on two design parameters. Numerical simulation tests are carried out to highlight the overall controller approach in a realistic scenario.

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Optimizing a Kalman filter with an evolutionary algorithm for nonlinear quadrotor attitude dynamics

Cited by 25 publications

References 19 publications

Kalman filter based method for tracking dynamic transmission line parameters

Kalman filter based method for tracking dynamic transmission line parameters

A Novel Framework of Modelling, Control, and Simulation for Autonomous Quadrotor UAVs Utilizing Arduino Mega

Filtered Observer-Based IDA-PBC Control for Trajectory Tracking of a Quadrotor

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