Design and Implementation of an Artificial Neural Network Controller for Quadrotor Flight in Confined Environment

Quadrotors offer practical solutions for many applications, such as emergency rescue, surveillance, military operations, videography and many more. For this reason, they have recently attracted the attention of research and industry. Even though they have been intensively studied, quadrotors still suffer from some challenges that limit their use, such as trajectory measurement, attitude estimation, obstacle avoidance, safety precautions, and land cybersecurity. One major problem is flying in a confined environment, such as closed buildings and tunnels, where the aerodynamics around the quadrotor are affected by close proximity objects, which result in tracking performance deterioration, and sometimes instability. To address this problem, researchers followed three different approaches; the Modeling approach, which focuses on the development of a precise dynamical model that accounts for the different aerodynamic effects, the Sensor Integration approach, which focuses on the addition of multiple sensors to the quadrotor and applying algorithms to stabilize the quadrotor based on their measurements, and the Controller Design approach, which focuses on the development of an adaptive and robust controller. In this research, a learning controller is proposed as a solution for the issue of quadrotor trajectory control in confined environments. This controller utilizes Artificial Neural Networks to adjust for the unknown aerodynamics on-line. A systematic approach for controller design is developed, so that, the approach could be followed for the development of controllers for other nonlinear systems of similar form. One goal for this research is to develop a global controller that could be applied to any quadrotor with minimal adjustment. A novel Artificial Neural Network structure is presented that increases learning efficiency and speed. In addition, a new learning algorithm is developed for the Artificial Neural Network, when utilized with the developed controller. Simulation results for the designed controller when applied to the Qball-X4 quadrotor are presented that show the effectiveness of the proposed Artificial Neural Network structure and the developed learning algorithm in the presence of variety of different unknown aerodynamics. These results are confirmed with real time experimentation, as the developed controller was successfully applied to Quanser’s Qball-X4 quadrotor for the flight control in confined environment. The practical challenges associated with the application of such a controller for quadrotor flight in confined environment are analyzed and adequately resolved to achieve an acceptable tracking performance

Magnetometer-Only Kalman Filter Based Algorithms for High Accuracy Spacecraft Attitude Estimation (A Comparative Analysis)

Kalman Filter (KF) based algorithms are the most frequently employed attitude estimation algorithms. Typically, a fully observable system necessitates the use of two distinct sensor types. Therefore, relying on a single sensor, such as a magnetometer, for spacecraft attitude estimation is deemed to be a challenge. The present investigation centers on utilizing magnetometers as the exclusive sensor. Several KF based estimation algorithms have been designed and evaluated to give the designer of spacecraft Attitude and Orbit Control System (AOCS) the choice of a suitable algorithm for his mission based on quantitative measures. These algorithms are capable of effectively addressing nonlinearity in both process and measurement models. The algorithms under examination encompass the Extended Kalman Filter (EKF), Sequential Extended Kalman Filter (SEKF), Pseudo Linear Kalman Filter (PSELIKA), Unscented Kalman Filter (USKF), and Derivative Free Extended Kalman Filter (DFEKF). The comparison of the distinct algorithms hinges on key performance metrics, such as estimation error for each axis, computation time, and convergence rate. The resulting algorithms provide numerous benefits, such as diverse levels of high estimation accuracy (with estimation errors ranging from 0.014o to 0.14o), varying computational demands (execution time ranges from 0.0536s to 0.0584s), and the capability to converge despite large initial attitude estimation errors (which reached 170o). These properties render the algorithms appropriate for utilization by spacecraft designers in all operational modes, supplying high-precision attitude estimations better than (0.5o) despite high magnetometer noise levels, which reached (200 nT)

Three Essays on Environmental and Energy Economics

In this dissertation, three related topics are investigated about environmental and energy economics. The research in these essays utilize panel data and regression models. The overall theme of these essays is to explore the relationships between energy and the environment in the United States (U.S.). In the first essay, using data from fifty U.S. states between 2012 and 2020, the impacts of three types of state level policies on electric vehicles (EV) adoption are examined: 1) policies that mitigate the environmental impacts from energy production, 2) policies that provide financial incentives to consumers for EV purchase, and 3) policies that provide publicly available EV charging infrastructure. With a dependent variable of EV registration per 100,000 population, impacts are assessed with a panel data, fixed effects model. Evidence is found that policies which either increase low greenhouse gas (GHG) energy through increasing the renewable and nuclear energy sources in the energy mix or reduce carbon dioxide (CO2) emissions from electricity generation by reducing the reliance on fossil fuels in the electric sector result in statistically significant increases in EV adoption rate. Financial incentives are important as the presence of a state income tax credit positively impacts EV adoption rate. Comparable elasticities on EV adoption rate from statistically significant coefficients show that per capita income has the largest effect on adoption (+10.1), while impacts of low GHG energy and per capita CO2 emissions elasticities are much smaller at + 0.64 and -1.0, respectively. Since state policies that enhance low GHG and provide tax credits positively impact EV adoption rates, our research demonstrates the need to nationalize both types of policies in order to uniformly improve adoption across all states. In the second essay, the impact of climate change on U.S. electricity consumption, production, and efficiency is examined using annual state-level data for 48 states over 30 years (1990 – 2019). Research results show that an increase in averaged maximum ambient air temperatures increases electricity demand and decreases generation efficiency. The electric sector in the U.S. is found to be vulnerable to climate change, such that a rise in the ambient temperature increases demand for electricity and decreases supply and efficiency of power plants. On the demand side, the per capita electricity consumption at the state level is responsive to the climate change, such that when the averaged maximum ambient temperature increases by 1 ͦ F (0.56 ͦ C), the per capita electricity consumption increases by a 0.52%. However, the most powerful impact on the per capita electricity consumption was found to be from the electricity retail prices such that a one cent increase in average per kilowatt-hours (kWh) price will result in a decrease of 7.1% in the per capita electricity consumption. On the supply side, power generation is also responsive to climate change such that increasing the average maximum temperature by 1 ͦ F (0.56 ͦ C) results in a reduction of 3.9% in the total electricity generation at the state level. Estimates for fossil fuels weighted average price consistently agree with law of demand as increasing fossil fuels weighted average price by $1 per million British Thermal Unit (MMBtu)[1] results in reduction of demand for fossil fuels and accordingly will result in a reduction of electricity supply by 10.2In the third essay, the existence of the Environmental Kuznets Curve (EKC) in the presence of low GHG energy consumption is empirically examined using state level data in the U.S. This research explores whether the per capita income still retains an inverted U shape impact on per capita CO2 emissions in the presence of state level environmental and energy policies which promote reduced fossil fuel use in the electricity sector. An Autoregressive Distributive Lag (ARDL) econometric model is employed using panel data for 50 U.S. states during the period of 1990 to 2018. The findings provide statistically significant evidence for the presence of the EKC for CO2 emissions at the state level. Regression estimates find a turning point of$50,766.5 in the relationship between per capita income and CO2 emissions. For the Low GHG energy variable, increased primary energy consumption for electricity from renewable and nuclear energy sources has a negative impact on per capita CO2 emissions. When the per capita average low GHG energy consumption increases by one MMBtu[2], per capita CO2 emissions reduces by 0.05%. With these findings, the existence of the EKC hypothesis for CO2 emissions at the state level is supported. The conclusion from essay three is that implementation of new energy technologies serves to reduce CO2 emissions. However, these technologies do not diminish the entire impact of increasing per capita income on reducing these emissions. Other factors, in addition to new energy technologies, are at work in reducing CO2 emissions with increasing per capita income past the turning point. These factors may include changes associated with higher levels of per capita income including an economic structure more heavily dependent upon services involving renewable energy source and increasing the adoption of green technologies such as EV, movement of production locations to other locations with lower income in helps stimulating the economic growth which in turn has a positive impact on the reduction of CO2, and enhanced consumer awareness about climate change and behavioral changes related fossil fuel consumption. [1] In average, this increase is equal to an increase of 2 cents per short ton of coal, $1.02 per 1000 CF of natural gas, or 12 cents per gallon of petroleum. [2] One million Btu is equal to 293 kWh

Modeling, Identification, Validation and Control of a Hybrid Maglev Ball System

In this thesis, the electrodynamics of a single axis hybrid electromagnetic suspension Maglev system was modeled and validated by applying it to a single axis hybrid maglev ball experiment. By exploring its linearized model, it was shown that the single axis hybrid Maglev ball has inherently unstable dynamics. Three control scenarios were explored based on the linearized model; (1) Proportional, Deferential (PD) control, (2) Proportional, Deferential, Integral (PID) and (3) PID controller with pre-filtering. This thesis has shown that a PID controller with a pre-filtering technique can stabilize such a system and provide a well-controlled response. A parametric system identification technique was applied to fit the theoretically derived model to a single axis hybrid maglev ball experiment. It is known that the identified model has different model parameters than the theoretically derived parameters. This thesis has examined and discussed the deviation from the theoretical model. Importantly, it was shown that such a system can be identified by estimating the values of two parameters instead of five to increase the accuracy. A Numerical nonlinear simulation was developed for the experiment based on the theoretically derived and experimentally identified model. This simulation was validated by real-time experiment outputs

The Power of Stakeholder Input: How Bringing Diverse Voices to the Table Helps Your Equity Journey

The General Assembly finds that this State has an urgent and collective responsibility to achieve educational equity by ensuring that all policies, programs, and practices affirm the strengths that each and every child brings with diverse background and life experiences and by delivering the comprehensive support, programs, and educational opportunities children need to succeed

Analisis Pengaruh Fasilitas Kampus dan Pelayanan Akademik Terhadap Kepuasan Mahasiswa Institut Teknologi dan Bisnis Trenggalek

Penelitian ini bertujuan untuk mengetahui pengaruh fasilitas kampus dan pelayanan akademik terhadap kepuasan mahasiswa  Institut Teknologi dan Bisnis Trenggalek. Penelitian merupakan penelitian kuantitatif dengan pendekatan ex post facto. populasi dalam penelitian ini adalah seluruh mahasiswa Institut Teknologi dan Bisnis Trenggalek dengan rumus slovin didapatkan sampel sebesar 116 mahasiswa. Instrumen penelitian ini meggunakan kuesioner dengan lima klasifikasi skala likert. Teknik analisis data yang digunakan untuk menguji hipotesis menggunakan analisis regresi linier berganda. Berdasarkan hasil analisis regresi diperoleh persamaan regresi Y= 1,619 + 0,390 X1 + 0,684 X2 + ε. Dari persamaan ini menunjukkan terjadihubungan positif antara fasilitas kampus dan pelayanan akademik terhadap kepuasan mahasiswa. Kenaikanfasilitas kampus dan  pelayanan akademik akan diikuti dengan peningkatan kepuasan mahasiswa, begitupula sebaliknya. Dari hasil pengujian hipotesis dapat disimpulkan bahwa fasilitas kampus pelayanan akademik berpengaruh positif terhadap kepuasan mahasiswa Institut Teknologi dan Bisnis Trenggalek sebesar 56,8% dan sisanya 43,2% dijelaskan variabel lain yang tidak dikaji dalam penelitian ini

Podcasting as an Effective Pedagogy for Teaching Chemistry During the COVID-19 Pandemic and Beyond

The COVID-19 pandemic has forced all educational institutions worldwide to switch their active routine to ONLINE. With students attending classes virtually, a number of problems arose including the absence of social interaction and the imposed difficulty of digesting the materials of different courses, especially for those with a scientific background. General chemistry (GC), as an introductory course, is usually registered by students from different backgrounds, including Science, Engineering, and Agriculture. At the United Arab Emirates University, the second level of GC (GCII) is more focused on problem-solving as related to various topics. With the absence of face-to-face experience because of the COVID-19 circumstances, students’ understanding of the chemical concepts and implementing that in problem-solving has become a challenge. The current work investigates the effect of using professionally-made podcasts of GCII on the extent of understanding of students registered for this course during the period of 2020-2020 over a course of four semesters. The results of surveying the usage and feedback of students engaged in this experiment are outlined. Conclusively, this pedagogy is fully supported by most of the students who regard it as a suitable alternative to face-to-face settings

EXPLORATORY AND CONFIRMATORY FACTOR ANALYSIS OF PERCEIVED SELF-EFFICACIES AMONG TEACHERS STUDENTS AT FACULTY OF EDUCATION, HELWAN UNIVERSITY, EGYPT: FROM BANDURA’S THEORY TO PROPOSED MODEL

The purpose of this study is to examine the validity and reliability of perceived self-efficacies questionnaire (PSE) which is designed for university students at faculty of education. A total of 472 students participated, selected by using cluster random sampling. In order to examine the construct validity of the PSE, Quantitative data were analysed using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) using SPSS 23 and AMOS 23. EFA revealed similar structures from prior research and the present study. The CFA approach verified the questionnaire of perceived self-efficacies was satisfactory for university students’ context. This work concludes the perceived self-efficacies of university students have a nine-factor structure: Planning perceived self-efficacy, Moral and emotional perceived self-efficacy, Social leadership perceived self-efficacy, Academic perceived self-efficacy, Reading perceived self-efficacy, Technology perceived self-efficacy, Research perceived self-efficacy, Motivated perceived self-efficacy and Creative perceived self-efficacy. The goodness of fit indices values shows good fit for self-efficacies with nine factors. According to these findings, the PSE is appropriate for researchers or teaching staff whose aim is to measure his/her students perceived self-efficacies beliefs. Article visualizations

TOTAL POLYPHENOLIC CONTENT AND ANTIOXIDANT ACTIVITY OF SILYBUM MARIANUM CULTURES GROWN ON DIFFERENT GROWTH REGULATORS

Objective: The present study was designed to study the effect of supplementing Silybum marianum cultures with different combinations and concentrations of growth regulators on the total phenolic content and the antioxidant activity of the produced cultures.Methods: The total polyphenolic content of 23 extracts of calli was calculated as µg of gallic acid/mg of dry weight extract (DWE) using Folin–Ciocalteu reagent. The antioxidant activity was calculated as trolox equivalent antioxidant capacity using 1,1-Diphenyl-2-picryl-hydrazyl (DPPH) assay for extracts containing more than 10 µg gallic acid/mg DWE.Results: Most of the combinations showed an increase in the total polyphenolic concentration compared to the wild plant. However, cultures grown on media supplemented with combinations of benzyl aminopurine (BAP) and gebberellic acid (Gb), adenine (Ad) and kinetin (Kin), BAP and indole acetic acid (IAA) possessed the highest total polyphenolic contents 20.5, 13.09 and 12.15 µg gallic acid/mg DWE, respectively. However, only (BAP+Gb), (BAP+1-Naphthaleneacetic acid (NAA), IAA, kin and (BAP+Ad) showed a significant increase in the antioxidant activity calculated as trolox equivalent with 2.65, 1.56, 1.56, 1.35 and 1.22 folds increase over the wild plant, respectively.Conclusion: The results obtained clearly indicated that changing the growth regulator system of Silybum marianum cultures serves as an easy and reliable method for increasing the total phenolic content and the antioxidant activity of cultures