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The purpose of this paper is to present an improved particle filter-based attitude estimator for a quadrotor unmanned aerial vehicle (UAV) that addresses the degeneracy issues.

Control of a quadrotor is not sufficient enough without an estimator to eliminate the noise from low-cost sensors. In this work, particle filter-based attitude estimator is proposed and used for nonlinear quadrotor dynamics. But, since recursive Bayesian estimation steps may rise degeneracy issues, the proposed scheme is improved with four different and widely used resampling algorithms.

Robustness of the proposed schemes is tested under various scenarios that include different levels of uncertainty and different particle sizes. Statistical analyses are conducted to assess the error performance of the schemes. According to the statistical analysis, the proposed estimators are capable of reducing sensor noise up to 5x, increasing signal to noise ratio up to 2.5x and reducing the uncertainty bounds up to 36x with root mean square value of as low as 0.0024, mean absolute error value of 0.036, respectively.

To the best of the authors’ knowledge, the originality of this paper is to propose a robust particle filter-based attitude estimator to eliminate the low-cost sensor errors of quadrotor UAVs.

The purpose of this paper is to introduce an artificial bee colony-based Kalman filter algorithm along with an extended objective function to ensure the optimality of the estimator of the quadrotor in the presence of unknown measurement noise statistics.

Six degree-of-freedom mathematical model of the quadrotor is derived. Position controller for the quadrotor is designed. Kalman filter-based estimation algorithm is implemented in the sensor feedback loop. Artificial bee colony-based hybrid algorithm is used as an optimization method to handle the unknown noise statistics. Existing objective function is extended with a penalty term. Mathematical proof of the extended objective function is derived. Results of the proposed algorithm is compared with de facto genetic algorithm-based Kalman filter.

Artificial bee colony algorithm-based Kalman filter and extended objective function duo are able to optimize the measurement noise covariance matrix with an absolute error as low as 0.001 [m²]. Proposed method and function is capable of reducing the noise from 2 to 0.09 [m] for x-axis, 3.4 to 0.14 [m] for y-axis and 3.7 to 0.2 [m] for z-axis, respectively.

The motivation behind this paper is to bring a novel optimization-based solution for the estimation problem of the quadrotor when the measurement noise statistics are unknown along with an extended objective function to prevent the infeasible solutions with mathematical convergence analysis.

The purpose of this paper is to develop, extend and propose an improved proportional integral derivative (PID) rate control of a quadrotor unmanned aerial vehicle based on a convexity-based surrogated firefly algorithm.

An improved PID controller structure is proposed for the rate dynamics of the quadrotor. Optimality of the controller is ensured by a recent, simple yet efficient firefly optimization method. The hybrid structure is further enhanced with a convexity-based surrogated model function.

Monte Carlo, transient response, error metrics and histogram distribution analyzes are conducted to show the performance of the proposed controller. The performance of the proposed method is evaluated under various convex combination values to further investigate the effect of the proposed surrogated model. According to the results, the proposed method is capable of controlling the rate quadrotor dynamics with the steady-state error of 0.0023 (rad/s) for P, −0.0024 (rad/s) for Q and 0 (rad/s) for the R state, respectively. Also, the least mean objective value is achieved at = 0 value of convexity in Monte Carlo trials.

The originality of this paper is to propose an improved PID rate controller with a convexity-based surrogated firefly algorithm.

The purpose of this study is to describe precisely the wind speed regime and characteristics of a runway of an International Airport, the north-western part of Turkey.

Three different probability distributions, namely, Inverse Gaussian (IG), widely used two-parameter Weibull and Rayleigh distributions in the literature, are used to represent wind regime and characteristics of the runway. The parameters of each distribution are estimated by the pattern search (PS)-based heuristic algorithm. The results are compared with the other three methods-based numerical computation, including maximum-likelihood method, moment method (MoM) and power density method, respectively. To evaluate the fitting performance of the proposed method, several statistical goodness tests including the mostly used root mean square error (RMSE) and chi-squared (X²) are conducted.

In the light of the statistical goodness tests, the results of the IG-based PS attain better performance than the classical Weibull and Rayleigh functions. Both the RMSE and X² values achieved by the IG-based PS method lower than that of Weibull and Rayleigh distributions. It exhibits a better fitting performance with 0.0074 for RMSE and 0.58 × 10⁻⁴ for X² for probability density function (PDF) in 2012 and with RMSE of 0.0084 and X² of 0.74 × 10⁻⁴ for PDF in 2013. As regard the cumulative density function of the measured wind data, the best results are found to be Weibull-based PS with RMSE of 0.0175 and X² of 3.25 × 10⁻⁴ in 2012. However, Weibull-based MoM shows more excellent ability in 2013, with RMSE of 0.0166 and X² of 2.94 × 10⁻⁴. Consequently, it is considered that the results of this study confirm that IG-based PS with the lowest error value can a good choice to model more accurately and characterize the wind speed profile of the airport.

This paper presents a realistic point of view regarding the wind regime and characteristics of an airport. This study may cast the light on researchers, policymakers, policy analysts and airport designers intending to investigate the wind profile of a runway at the airport in the world and also provide a significant pathway on how to determine the wind distribution of the runway.

Instead of the well-known Weibull distribution for the representing of wind distribution in the literature, in this paper, IG distribution is used. Furthermore, the suitability of IG to represent the wind distribution is validated when compared with two-parameter Weibull and Rayleigh distributions. Besides, the performance and efficiency of PS have been evaluated by comparing it with other methods.

The purpose of this study is to build a high accuracy thrust model under various small turbojet engine shaft speeds by using robust, ordinary, linear and nonlinear least squares estimation methods for target drone applications.

The dynamic shaft speeds from the test experiment of a target drone engine is conducted. Then, thrust values are calculated. Based on these, the engine thrust is modeled by robust linear and nonlinear equations. The models are benefited from quadratic, power and various series expansion functions with several coefficients to optimize the model parameters.

The error terms and accuracy of the model are given using sum of squared errors, root mean square error (RMSE) and R-squared (R²) error definitions. Based on the multiple analyses, it is seen that the RMSE values are no more than 17.7539 and the best obtained result for robust least squares estimation is 15.0086 for linear at all cases. Furthermore, the R² value is found to be 0.9996 as the highest with the nonlinear Fourier series expansion model.

The motivation behind this paper is to propose robust nonlinear thrust models based on power, Fourier and various series expansion functions for dynamic shaft speeds from the test experiments.

The purpose of this study is to establish an effective tracking algorithm for small unmanned aerial vehicles (UAVs) based on interacting multiple model (IMM) to take timely countermeasures against illegal flying UAVs.

In this paper, based on the constant velocity model (CV), the maneuvering adaptive current statistical model (CS) and the angular velocity adaptive three-dimensional (3D) fixed center constant speed rate constant steering rate model, a small UAV tracking algorithm based on adaptive interacting multiple model (AIMM-UKF) is proposed. In addition, an adaptive robust filter is added to each model of the algorithm. The linear Kalman filter algorithm is attached to the CV model and the CS model and the unscented Kalman filter algorithm (UKF) is attached to the CSCDR model to solve the nonlinearity of the 3D turning model.

Monte-Carlo simulation comparison with the other two IMM tracking algorithms shows that in the case of different movement modes and maneuvering strength of the UAV, the AIMM-UKF algorithm makes a good trade-off between the amount of calculation and filtering accuracy, which can maintain more accurate and stable tracking and has strong robustness. At the same time, after testing the actual observation data of the UAV, the results show that the AIMM-UKF algorithm state estimation trajectory can be regarded as an actual trajectory in practical engineering applications, which has good practical value.

This paper presents a new small UAV tracking algorithm based on IMM and the advantages and practicability of this algorithm compared with existing algorithms are proved through experiments.

The purpose of this paper is to identify and investigate the awareness level of non-Muslim consumers to purchasing halal food products. Research on the non-Muslim consumers’ awareness towards purchasing halal food products is poorly understood so far in South Africa.

An exploratory case study was adopted to explore new points of views about a particular issue, which is unknown, or not much known about it, to formulate ideas or propositions. Semi-structured interviews were the major primary data collection method. Four non-Muslim consumers from different settings purposively were selected. Thematic data analysis procedures were used.

The study found that non-Muslim consumers in Cape Town have a positive awareness of halal food, including its benefits and the production processes involved in producing it. The study also concluded that halal is not merely a commercial name using as a trademark in the global market. However, halal has several dimensions; primarily, for non-Muslim consumers, it is a mark of health and hygiene. With regard to psychological aspect, halal is considered as a sign of trust, comfortable and safe. It gives consumers a peace of mind when they consume food products that carry the halal label.

Limitations in the study should be acknowledged. The main limitation of the study is that a small sample size was selected for this study. Another limitation is that the study was only conducted in the city of Cape Town.

This is the first qualitative study of its kind that presents an empirical evidence about the awareness of the non-Muslim consumers towards purchasing halal food products in South Africa, in general, and in Cape Town, in particular.

The purpose of this paper is to determine the factors that affect foreign consumers’ purchase intention towards purchasing halal food products in South Africa. These factors are halal awareness, halal logo and attitude, which are important factors in affecting the intention of consumers.

Data were collected via a self-questionnaire with a sample of 230 foreign consumers. For analysing these data, a structural equation modelling technique was used in this study.

Based on the study’s results, all factors significantly influence foreign consumers’ intention towards purchasing halal food products and, subsequently, their buying behaviour. Interestingly, the study found that attitudes and halal awareness of non-Muslim consumers are very high compared with those of the Muslim consumers. Although the study addressed halal food consumers, most of the respondents participated in the study were non-Muslims and the majority of them were Christians.

The respondents were only limited to the Cape Town city in South Africa, and the focus was only on five variables related to halal food consumers, namely, halal awareness halal logo, attitude, purchase intention and buying behaviour.

This study can be used to develop halal food products to attract both Muslim and non-Muslim consumers, who are foreigners to a particular country.

This study is one of the first studies seeking to determine the factors that affect foreign consumers with regard to the purchase of halal food products in South Africa. It is regarded one of the first attempts to determine halal awareness, halal logo and attitude and how purchase intention and buying behaviour can be influenced.

This study aims to explore the challenges of getting halal certification for restaurants in north-eastern Thailand.

Qualitative research approach was adopted to analyse the collected data. The research procedures and the interview questions were examined by the Ethics Committee for Research involving human subjects. In total, 10 restaurant owners were interviewed. Then, the interviews were transcribed, coded and grouped by using thematic analysis while the ATLAS ti. software was used for qualitative data analysis. The theme was finalised by three intercoder agreements.

The three challenges of obtaining halal certification among restaurants in north-eastern Thailand were the complicated process of getting halal certification, lack of restaurant owner commitment and high halal certification fee.

The number of halal-certified restaurants are limited. Some restaurants refused to renew halal status but their information is still displayed on the halal authority website. Not only the number of restaurants but also time-limited. Further, a quantitative phase for prioritising was suggested.

The study can be beneficial to the halal authority and business holders as the two main stakeholders. The findings can be used to plan or develop halal strategies to increase the quality of halal restaurants. As informants mentioned common challenges, the findings could be applied as guidelines for a new business holder keen on halal implementation.

This research demonstrated the challenges of halal certification in a non-Muslim country, focussing on the north-eastern region of Thailand. The findings will add value to a potential business area. Therefore, the highlighted challenges could provide a novelty and be useful for Muslim marketing.