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This paper presents an implementation of automatic flight control system (AFCS); analyzes and assures its performance during model in loop (MIL), software in loop (SIL), and processor in loop (PIL) stages. Based on both linear and analytic linear models with trimmed values of straight and leveling scenario, the proposed autopilot is applied to an Ultrastick-25e fixed wing unmanned aerial vehicle (UAV). The implementation of Ultrastick-25e AFCS is accomplished according to the resulted design parameters, and performing various flight scenarios. The choice of avionics and sensors of small UAV (SUAV) required for stability based on commercial off the Shelf (COTS) components. The proposed design uses low cost and light weight micro electro mechanical systems (MEMS) as new sensor technology. Since MEMS suffers from various types of noise, state estimation technique is introduced using both Kalman filter (KF) and complementary filter. Moreover, both results of KF and complementary filter are compared. Finally, PIL simulation is implemented to evaluate the autopilot as hardware components and software algorithms for management and PID control structure with its parameters proposed for implementing AFCS. The results show a good performance in disturbance rejection and robustness against sensors noise.

The objective of this work is to introduce the design, simulation and control of a quadcopter, as an example of unmanned aerial vehicle (UAV).To fulfill this objective, a mathematical model of the quadcopter has been developed. The simulation of the model and controller design is developed in MATLAB/Simulink environment. Although it remains a complete nonlinear system, this paper operates with mathematical representation of the quadcopter and modeling of the intended system. A linearization of the obtained mathematical model has been achieved. In order to design the attitude controller, the transfer function of the brushless DC motors (BLDCM) which are responsible of the quadcopter motion is obtained using system identification techniques. A complete test experiment is described here to achieve this goal. The designed controller is assessed and simulation results are discussed.

This paper introduces the design and the implementation of a heading angle tracking controller using fuzzy logic for a scaled Autonomous Multi-Wheeled Combat Vehicle (AMWCV) to navigate in outdoor environments. The challenge of designing this control system is to control the steering of the front four wheels individually to obtain the correct heading angle of the vehicle. The main contribution of the paper can be summarized in the fact that it is designing four fuzzy controllers for navigation and tracking the desired heading angle while at the same time while controlling the steering of the front four wheels individually. The AMWCV is capable of forwarding and backward movement where all eight wheels are powered individually. The different heading angles are used and simulated using MATLAB software to evaluate the performances of the developed algorithms. In addition, the performance of the developed controllers is validated in the presence of noise and disturbance in order to evaluate the robustness of the controller's Simulation results show the performances and demonstrate that the developed controllers are effective in predicting the desired heading angle changes.