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M.Ing. / Linear control system theory is well developed and has lead to a number of control system types with well-defined design methods that can be applied to any linear system. Unfortunately, no system in nature is truly linear. As a result, such non-linear systems must be represented by a linear model that is accurate over some region of the operating states of the system. The success of linear control theory in commercial applications is testament to the fact that some types of systems can be adequately represented by a linear model. However, systems with time-varying dynamics or non-linearities such as input or operating state saturation cannot always be adequately controlled by linear control systems. For that reason, non-linear control techniques must be investigated. This project aims to investigate Non-linear Model Predictive Control theory and practical implementation in the context of developing an autopilot for an Unmanned Aerial Vehicle based on a miniature helicopter. A non-linear model of the dynamics of an X-Cell Spectra G radio-controlled helicopter was developed based on the existing literature. A number of experiments were performed to determine the parameters of this model. Significant future work exists in designing additional ground experiments since certain parameters are difficult to measure safely in the laboratory. Additional work to improve the accuracy of the model at high airspeeds, as well as incorporating a more accurate yaw dynamics model, is also required. Following this, a Non-linear Model Predictive Control autopilot was simulated using MATLAB®. The simulation tested the effects of control system parameters such as control horizon and sampling period, as well as the sensor noise susceptibility and its ability to handle wind as a random disturbance. The results determined adequate control system parameters for level flight as well as landing the helicopter under ideal conditions. Simulations in which sensor noise and wind were added showed that the control system is significantly affected by sensor noise and that it cannot hover in the presence of wind. A real-time implementation was not achieved during this work; however, several directions for future research have been discussed.

In the Spring of 1998, the Virtual Corporation at Virginia Tech demonstrated the ability of Linear Switched Reluctance Propulsion (LSRP) to propel a vehicle on a track using only the interaction of a passive magnetic component carried on the vehicle with electromagnets built into the track. The Mark II project was a follow-on effort to complete a thorough design analysis of a second iteration vehicle which features the complete functionality of the original vehicle, with the addition of the ability to enter and exit the LSRP track system using remote control and an electric motor. The new vehicle also features certain design improvements in communications and structural rigidity. This paper elaborates on the process of design and analysis of the vehicle and ramp systems, including detail design drawings, finite element analysis of the vehicle chassis, powertrain subsystem analysis, and detailed analysis of the ramp surface contour design. / Master of Engineering

A dissertation submitted to the Faculty of Engineering and the Built Environment, School of Mechanical, Industrial and Aeronautical Engineering, University of the Witwatersrand, in fulfilment of the requirements for the degree of Master of Science in Engineering. Johannesburg, May 2016 / The present work describes the practical implementation of systems identification techniques to the development of a linear aerodynamic model for a small low-cost UAV equipped with a basic navigational and inertial measurement systems. The assessment of the applicability of the techniques were based on determining whether adequate aerodynamic models could be developed to aid in the reduction of wind tunnel testing when characterising new UAVs. The identification process consisted of postulating a model structure, flight test manoeuvre design, data reconstruction, aerodynamic parameter estimation, and model validation. The estimators that were used for the post-flight identification were the output error maximum likelihood method and an iterated extended Kalman filter with a global smoother. SIDPAC and FVSysID systems identification toolboxes were utilised and modified where appropriate. The instrumentation system on board the UAV consisted of three-axis accelerometers and gyroscopes, a three-axis vector magnetometer and GPS tracking while data was logged at 25 Hz. The angle of attack and angle of sideslip were not measured directly and were estimated using tailored data reconstruction methods. Adequate time domain lateral model correlation with flight data was achieved for the cruise flight condition. Adequacy was assessed against Theil’s inequality coefficients and Theil’s covariance. It was found that the simplified estimation algorithms based on the linearized equations of motion yielded the most promising model matches. Due to the high correlation between the pitch damping derivatives, the longitudinal analysis did not yield valid model parameter estimates. Even though the accuracy of the resulting models was below initial expectations, the detailed data compatibility analysis provided valuable insight into estimator limitations, instrumentation requirements and test procedures for systems identification on low-cost UAVs. / MT2016

Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2009. / This thesis describes the successful development of an autopilot for an unmanned radio controlled helicopter. It presents a non-linear helicopter model. An adaptive linearised model is derived and used to design a controller. The adaptive full state controller is tested in various ways, including two aerobatic manoeuvres. A number of analyses are performed on the controller, including its robustness to parameter changes, noisy estimates, wind and processing power. The controller is compared with a non-adaptive counterpart, which leads to the conception, design and analysis of a much improved control structure. Practical flight test results are presented and analysed. In some instances available literature was reworked and re-derived to produce a genericmodel-controller package that can easily be adapted for helicopters of any make, model and size.

This thesis presents how unmanned aerial vehicles (UAVs) can successfully assist in search and rescue (SAR) operations using wireless localization. The zone-grid to partition to capture/detect WiFi probe requests follows the concepts found in Search Theory Method. The UAV has attached a sensor, e.g., WiFi sniffer, to capture/detect the WiFi probes from victims or lost people’s smartphones. Applying the Random-Forest based machine learning algorithm, an estimation of the user's location is determined with a 81.8% accuracy. UAV technology has shown limitations in the navigational performance and limited flight time. Procedures to optimize these limitations are presented. Additionally, how the UAV is maneuvered during flight is analyzed, considering different SAR flight patterns and Li-Po battery consumption rates of the UAV. Results show that controlling the UAV by remote-controll detected the most probes, but it is less power efficient compared to control it autonomously.

Marine search and rescue activities have been plagued with the problem of risking the lives of rescuers in rescue operations. With increasing developments in sensor technologies, it became a necessity in the marine search and rescue community to develop an autonomous marine craft to assist in rescue operations. Autonomy of marine craft requires a robust localization technique and process. To apply robust localization to marine craft, GPS technology was used to determine the position of the marine craft at any given point in time. Given that the operational environment of the marine was at open air, river, sea etc. GPS signal was always available to the marine craft as there are no obstructions to GPS signal. Adequate cognizance of the current position and states of an unmanned marine craft was a critical requirement for navigation of an unmanned surface vehicle (USV). The unmanned surface vehicle uses GPS in conjunction with state estimated solution provided by inertial sensors. In the absence of the GPS signal, navigation is resumed with a digital compass and inertial sensors to such a time when the GPS signal becomes accessible. GPS based navigation can be used for an unmanned marine craft with the mathematical modelling of the craft meeting the functional requirements of an unmanned marine craft. A low cost GPS unit was used in conjunction with a low cost inertial measurement unit (IMU) with sonar for obstacle detection. The use of sonar in navigation algorithm of marine craft was aimed at surveillance of the operational environment of the marine craft to detect obstacles on its path of motion. Inertial sensors were used to determine the attitude of the marine craft in motion. / Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2011.

The construction of fish passes has been a longstanding measure to improve river ecosystem status by ensuring the passability of weirs, dams and other in- channel structures for migratory fish. Many fish passes have a low biological effectiveness because of unsuitable hydrodynamic conditions hindering fish to rapidly detect the pass entrance. There has been a need for techniques to quantify the hydrodynamics surrounding fish pass entrances in order to identify those passes that require enhancement and to improve the design of new passes. This PhD thesis presents the development of a methodology for the rapid, spatially continuous quantification of near-pass hydrodynamics in the field. The methodology involves moving-vessel Acoustic Doppler Current Profiler (ADCP) measurements in order to quantify the 3-dimensional water velocity distribution around fish pass entrances. The approach presented in this thesis is novel because it integrates a set of techniques to make ADCP data robust against errors associated with the environmental conditions near engineered in-channel structures. These techniques provide solutions to (i) ADCP compass errors from magnetic interference, (ii) bias in water velocity data caused by spatial flow heterogeneity, (iii) the accurate ADCP positioning in locales with constrained line of sight to navigation satellites, and (iv) the accurate and cost-effective sensor deployment following pre-defined sampling strategies. The effectiveness and transferability of the methodology were evaluated at three fish pass sites covering conditions of low, medium and high discharge. The methodology outputs enabled a detailed quantitative characterisation of the fish pass attraction flow and its interaction with other hydrodynamic features. The outputs are suitable to formulate novel indicators of hydrodynamic fish pass attractiveness and they revealed the need to refine traditional fish pass design guidelines.