Aircraft Attitude Estimation Using Panoramic Images

This thesis investigates the problem of reliably estimating attitude from panoramic imagery in cluttered environments. Accurate attitude is an essential input to the stabilisation systems of autonomous aerial vehicles. A new camera system which combines a CCD camera, UltraViolet (UV) filters and a panoramic mirror-lens is designed. Drawing on biological inspiration from the Ocelli organ possessed by certain insects, UV filtered images are used to enhance the contrast between the sky and ground and mitigate the effect of the sun. A novel method for real–time horizon-based attitude estimation using panoramic image that is capable of estimating an aircraft pitch and roll at a low altitude in the presence of sun, clouds and occluding features such as tree, building, is developed. Also, a new method for panoramic sky/ground thresholding, consisting of a horizon– and a sun–tracking system which works effectively even when the horizon line is difficult to detect by normal thresholding methods due to flares and other effects from the presence of the sun in the image, is proposed. An algorithm for estimating the attitude from three–dimensional mapping of the horizon projected onto a 3D plane is developed. The use of optic flow to determine pitch and roll rates is investigated using the panoramic image and image interpolation algorithm (I2A). Two methods which employ sensor fusion techniques, Extended Kalman Filter (EKF) and Artificial Neural Networks (ANNs), are used to fuse unfiltered measurements from inertial sensors and the vision system. The EKF estimates gyroscope biases and also the attitude. The ANN fuses the optic flow and horizon–based attitude to provide smooth attitude estimations. The results obtained from different parts of the research are tested and validated through simulations and real flight tests

Robust PID tuning rule using grey prediction algorithm with optimization method

This paper discusses an approach to tune the PID controller parameters using the optimization method and grey prediction algorithm. The method involves calculating the average of the estimated error using grey prediction algorithm. A mat lab program is developed using simulink tofind the average of the estimated errorfor the system whose process is modeled infirst order lag plus dead time (FOLPD) form. the Optimization method with mat lab software program was used to find the optimum value for the controller gain (K, (opD which minimizes spectfic performance criteria (ITAE performance criteria) to achieve most of the systems requirements such as reducing the overshoot, maintain a high system response, achieve a good load disturbances rejection and maintain robustness. The cwerage of the estimated error had been calculated using grey prediction algorithm. Those two parameters were used to calculate the gain of the controller (K"), integral time g) and the derivative time Qa) for PID controller. Simulations for the proposed algorithm had been done for dffirent process models. A comparison between the proposed tuning rules and the traditional tuning rules is done through the Matlab software to show the efficiency of the new tuning rule

Micro controller-based fuzzy logic controller for a small autonomous underwater robot

Mobile systems traveling through a complex environment, lil@ underwater environments, present major dfficulties in determining accurate dynamic models. Autonomous underwater vehicle motion in these conditions requires investigation of competent control solutions that guarantee robustness against external parameter uncertainty. In this paper, a microcontroller-basedfuzzy logic controller is introduced to stabilize balancing the robot while it is movingforward. This approach is applied to one onboard microcontroller which is inside small AUV and the control system is able to meet the required robustness. The significance of this work is because of using a microcontroller with its limited amount of on-chip MM rather than using commercial computer. It is implemented along with a fuzzy PI controller as the supemisor, and evaluated through experiments. It is shown that the characteristics of the fuzzy logic, such as flexibility of the I/O selection and saturation of the outputs, provide favorable performance to the control systemfor AUVs