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

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

Clinical phenotypes and constipation severity in Parkinson’s disease: Relation to Prevotella species

Background: The gut microbiome is speculated to play a crucial role in its pathogenesis of Parkinson’s disease as a triggering factor. Recent hypotheses suggested that Prevotella species regulate gut permeability, exert a neuroprotective effect, and interestingly, has been suspected to be deficient in PD patients, and so may play a role in this disease. Aim: This study was designed to compare between PD patients and their healthy controls as regards relative Prevotella abundance, prevalence of Prevotella-dominant Enterotype, and constipation severity. Also, to correlate Prevotella changes with the clinical phenotypes and  severity of motor and non-motor symptoms of PD. Methods: Twenty-five PD cases were enrolled in this study and cross-matched to 25 healthy subjects representing the control group. Overall NMS severity was assessed using the Non-Motor Symptoms Scale (NMSS). Quantitative SYBR green Real Time PCR was performed for the identification and quantitation of Prevotella in stool. Results: Prevotella relative abundance was 4-fold decreased in cases when compared to controls with PIGD phenotype showing the lowest abundance, however the difference was not statistically significance. Prevotella-dominant Enterotype was less presented in cases compared to controls, the result was statistically significant. Severe and very severe constipation grades presented 64% of cases group Vs 12% of control group. There was statistically significant positive correlation between total constipation score and UPDRS total score and motor symptoms phenotypes. Conclusion: Relative low Prevotella abundance in PD patients appears to be related to severe phenotypes of the disease; PIGD and mixed phenotypes. Severe constipation was more presented in PD cases which may be considered  as a preclinical biomarker for PD

Epigenetic harnessing of HCV via modulating the lipid droplet-protein, TIP47, in HCV cell models

AbstractThis study aimed at identifying potential microRNAs that modulate hepatic lipid droplets (LD) through targeting the Tail interacting protein of 47kDa (TIP47) in HCV infection.Bioinformatics analysis revealed that miR-148a and miR-30a potentially target TIP47. Expression profiling showed that both microRNAs were downregulated, while TIP47 was upregulated in liver biopsies of HCV-infected patients. Forcing the expression of both microRNAs in JFH-I infected, oleic acid-treated Huh7 cells, significantly suppressed TIP47 expression and reduced cellular LDs with marked decrease in viral RNA. This study shows that miR-148a and miR-30a, regulate TIP47 expression and LDs in HCV infected cells

Miscellaneous Rheumatic Diseases [73-83]: 73. Is There a Delay in Specialist Referral of Hot Swollen Joint?

Background: Patients with acute, hot, swollen joints commonly present to general practitioners, emergency departments and/or acute admitting teams rather than directly to rheumatology. It is imperative to consider septic arthritis in the differential diagnosis of these patients. The British Society of Rheumatology (BSR) has produced guidelines for the management of this condition, which include recommendations for early specialist referral and joint aspiration of all patients with suspected septic arthritis. We examined whether the initial management of patients with acute hot swollen joint(s) at University College London Hospital (UCLH) follows BSR guidelines. Methods: For the period Feb to Nov 2009, appropriate patients were identified by searching the UCLH database using the diagnostic terms, "pyogenic arthritis”, "septic arthritis” and "gout”; and from all joint aspirate requests sent to microbiology. Medical notes were obtained and any patients who had elective arthroscopies or chronic (> 6 weeks) symptoms were excluded. Data were collected on the time taken from the onset of symptoms to specialist (orthopaedic/rheumatology) referral and joint aspiration, collection of blood cultures and antibiotic treatment with or without microbiology advice. Results: Twenty patients were identified with hot swollen (18 monoarticular, 3 prosthetic) joint(s) of < 2 weeks duration. Of whom, 3/20 (15%) were admitted directly to rheumatology, 7/20 (35%) to the acute admissions unit, 3/20 (15%) to orthopaedic, 4/20 (20%) to a medical team and 1/20 (5%) to general surgery. In 19 (95%) cases, specialist (rheumatology/orthopaedic) advice was sought. Of 14 cases not seen directly by specialists 9 (64%) were referred at 24-48 h and 5 (36%) at 48-192 h. All 20 patients had joint aspiration. In 9/20 (45%) of cases, joint aspiration was performed in less than 6 h, 3/20 (15%) cases at 6-24h and 6/20 (30%) cases at 24-192 h and was not recorded in two patients. Of these, crystals were identified in two and one was culture positive. Blood cultures were received for only 6/20 (30%) of cases and only clearly documented to have been taken prior to antibiotic therapy and none were positive. Of 14/20 (70%) started on antibiotic treatment empirically, only 6 (42%) were preceded by joint aspiration. In the 6 patients not treated with antibiotics due to low index of suspicion of septic arthritis, synovial fluid and blood cultures were negative. Microbiology advice was sought in 10/20 (50%) of cases by the admitting teams but the timing of this advice is unclear. Conclusions: Despite the provision of 24 h rheumatology and orthopaedic cover at UCLH, we found a significant delay in acute medical firms seeking specialist advice on the management of patients with acute, hot swollen joints with subsequent deviation from BSR guidelines. Consequently, we plan to increase awareness of these guidelines amongst medical firms at UCLH. Disclosure statement: All authors have declared no conflicts of interes

Global optimum spacecraft orbit control subject to bounded thrust in presence of nonlinear and random disturbances in a low earth orbit

The primary objective of this work is to develop an effective spacecraft orbit control algorithm suitable for spacecraft orbital maneuver and/or rendezvous. The actual governing equation of a spacecraft orbiting the earth is merely nonlinear. Disturbance forces resulting from aerodynamic drag, oblateness of the earth till the fourth order (i.e. J4), and random disturbances are modeled for the initial and target orbits. These disturbances increase the complexity of nonlinear governing equations. Global optimum solutions of the control algorithm parameters are determined throughout real coded genetic algorithms such that the steady state difference between the actual and desired trajectories is minimized. The resulting solutions are constrained to avoid spacecraft collision with the surface of the earth taking into account limited thrust budget

Combined spacecraft orbit and attitude control through extended Kalman filtering of magnetometer, gyro, and GPS measurements

The main goal of this research is to establish spacecraft orbit and attitude control algorithms based on extended Kalman filter which provides estimates of spacecraft orbital and attitude states. The control and estimation algorithms must be capable of dealing with the spacecraft conditions during the detumbling and attitude acquisition modes of operation. These conditions are characterized by nonlinearities represented by large initial attitude angles, large initial angular velocities, large initial attitude estimation error, and large initial position estimation error. All of the developed estimation and control algorithms are suitable for application to the next Egyptian scientific satellite, EGYPTSAT-2. The parameters of the case-study spacecraft are similar but not identical to the former Egyptian satellite EGYPTSAT-1. This is done because the parameters of EGYPTSAT-2 satellite have not been consolidated yet. The sensors utilized are gyro, magnetometer, and GPS. Gyro and magnetometer are utilized to provide measurements for the estimates of spacecraft attitude state vector where as magnetometer and GPS are utilized to provide measurements for the estimates of spacecraft orbital state vector

Concurrent Spacecraft Attitude and Orbit Estimation with Attitude Control Based on Magnetometer, Gyro, and GPS Measurements through Extended Kalman Filter

The main objective of this research is to provide attitude estimation, orbit estimation, and attitude control algorithms suitable for application to the next Egyptian scientific satellite. Concurrent spacecraft orbit and attitude estimates must be suitable for usage by the attitude control algorithm. The developed estimation algorithms are able to deal with sever tumbling conditions characterized by large initial attitude, angular velocity and position estimation errors. The estimation algorithms could provide attitude estimates within 0.5o(3-σ) and 60 m (3-σ) for the position estimation errors. The attitude control algorithm developed is able to bring the spacecraft from its initial tumbling conditions to nadir pointing within an error of only 0.5o (3-σ)

Simultaneous spacecraft orbit estimation and control based on GPS measurements via extended Kalman filter

The primary aim of this work is to provide simultaneous spacecraft orbit estimation and control based on the global positioning system (GPS) measurements suitable for application to the next coming Egyptian remote sensing satellites. Disturbance resulting from earth’s oblateness till the fourth order (i.e., J4) is considered. In addition, aerodynamic drag and random disturbance effects are taken into consideration

Fast converging with high accuracy estimates of satellite attitude and orbit based on magnetometer augmented with gyro, star sensor and GPS via extended Kalman filter

The primary goal of this work is to extend the work done in, Tamer (2009), to provide high accuracy satellite attitude and orbit estimates needed for imaging purposes and also before execution of spacecraft orbital maneuvers for the next Egyptian scientific satellite. The problem of coarse satellite attitude and orbit estimation based on magnetometer measurements has been treated in the literature. The current research expands the field of application from coarse and slow converging estimates to accurate and fast converging attitude and orbit estimates within 0.1°, and 10 m for attitude angles and spacecraft location respectively (1-σ). The magnetometer is used for both spacecraft attitude and orbit estimation, aided with gyro to provide angular velocity measurements, star sensor to provide attitude quaternion, and GPS receiver to provide spacecraft location. The spacecraft under consideration is subject to solar radiation pressure forces and moments, aerodynamics forces and moments, earth’s oblateness till the fourth order (i.e. J4), gravity gradient moments, and residual magnetic dipole moments. The estimation algorithm developed is powerful enough to converge quickly (actually within 10 s) despite very large initial estimation errors with sufficiently high accuracy estimates