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This paper is focused on dynamic modeling and control system design as well as vision based collision avoidance for multi-rotor unmanned aerial vehicles (UAVs). Multi-rotor UAVs are defined as rotary-winged UAVs with multiple rotors. These multi-rotor UAVs can be utilized in various military situations such as surveillance and reconnaissance. They can also be used for obtaining visual information from steep terrains or disaster sites. In this paper, a quad-rotor model is introduced as well as its control system, which is designed based on a proportional-integral-derivative controller and vision-based collision avoidance control system. Additionally, in order for a UAV to navigate safely in areas such as buildings and offices with a number of obstacles, there must be a collision avoidance algorithm installed in the UAV's hardware, which should include the detection of obstacles, avoidance maneuvering, etc. In this paper, the optical flow method, one of the vision-based collision avoidance techniques, is introduced, and multi-rotor UAV's collision avoidance simulations are described in various virtual environments in order to demonstrate its avoidance performance.

The increased demand for high maneuverability of modern missiles requires excellent autopilot performance over a large flight envelope. The main difficulty in missile autopilot design is the influence of high angle-of-attack aerodynamic phenomena on stability characteristics (Hemsch, 1992). As a missile executes a high angle-of-attack maneuver, the forebody vortices can become asymmetric and give rise to significant lateral-forces and yawing moments. Classically, missile autopilots are designed using gain scheduling approaches in roll, pitch, and yaw channels (Blakelock, 1991;Shamma and Athans, 1992;Shamma and Cloutier, 1993;White et al., 2007). However, the performance of singleaxis autopilot design approaches are limited within some flight boundaries because aerodynamic coupling effects and their parameter dependencies in large angle-of-attack aerodynamics could not be considered. In this context, the design of a three-axis missile autopilot has been studied using linear and nonlinear control approaches (Choi et al., 2008;Devaud et al., 2001;Kim et al., 2008). These methods are based on gain scheduling techniques by local linearization, and demonstrate some improvements from a practical point of view.In this paper, a three-axis missile autopilot design with a multi-objective output-feedback control theory is presented. Because high angle-of-attack aerodynamics is highly nonlinear and estimates of the aerodynamic coefficients are very imprecise, a mix of H∞ and H2 criteria is employed to guarantee the performance of the three-axis missile autopilot. This control methodology, which uses linear matrix inequality (LMI) techniques, was motivated by the work in (Schere et al., 1997). This paper is organized as follows. In Section 2, we give an overview of multi-objective output-feedback control theory. Section 3 describes our formulation of the missile control problem. Section 4 describes strategies and numerical simulation results for the designed autopilot. Our conclusions are provided in Section 5. AbstractWe report on the design of a three-axis missile autopilot using multi-objective control synthesis via linear matrix inequality techniques. This autopilot design guarantees H 2 /H ∞ performance criteria for a set of finite linear models. These models are linearized at different aerodynamic roll angle conditions over the flight envelope to capture uncertainties that occur in the high-angle-of-attack regime. Simulation results are presented for different aerodynamic roll angle variations and show that the performance of the controller is very satisfactory.