This paper presents an optimal algorithm for finding collision-free path and trajectory for microair vehicles (MAVs) in urban terrain where multiple ground obstacles are distributed. Regarding vertices of polygonal obstacles as input points of the Delaunay triangulations, a Delaunay-based path planning is proposed to determine an optimal waypoint path while considering criterions of minimum fuel expenditure and collision risk. A trajectory generation method with corresponding optimal constraints is further developed to yield feasible fly trajectory along the planned path. The off-line pre-planning and on-line updated planning are integrated to enhance autonomy of vehicles flying in dangerous situations, with tight maneuvering and operational capability. Simulation results of a mission scenario are finally presented to demonstrate effectiveness of the proposed approach

This paper aims to investigate theoretically and experimentally the dynamic behaviors of the pitch and roll motions of a small-scale unmanned air vehicle in loitering flight. Two fourth-order ARX (AutoRegressive with eXogenous input) models are successfully identified, and the performance analysis is carried out based on the flight test data. The validity of the identified model is verified by both time domain model prediction and frequency domain spectral analysis. With the proposed ARX models, two compensators are further designed using a frequency technique to improve the transient performance of the pitch and roll control channels. Simulations and experiments demonstrate that the proposed ARX model-based compensation control design strategy can improve the flight performance.

This paper presents a model identification of a micro air vehicle in loitering flight, based on the input-output data collected from flight experiments on a homemade 1-m-sized aircraft. A miniature flight-control system, which consists of the onboard and the ground sections, is equipped with a multichannel data logger associated with the data acquisition software. Modeling and performance analysis are carried out, based on the flight-test data using a system identification technique. Two fourth-order autoregressive with exogenous input (ARX) models are identified to present the attitude characteristics of the longitudinal (pitch) and the lateral (roll) control channels, respectively. The validity of the identified model is verified by both time-domain model prediction and frequency-domain spectral analysis. Based on the proposed ARX models, two compensators are further designed using a frequency-domain method, and then added to the closed-loop control systems to improve the transient performance of the pitch- and roll-control channels. Simulations and experiments demonstrate that the flight performance obtained by the proposed ARX model-based compensation control can be improved.

This paper presents the development of an electrically powered micro air vehicle (MAV) with a wingspan of 360 mm. A miniature flight control system including a self-made micro video image system especially suitable for MAV is developed. The aerodynamic performance of several airfoil sections at low chords Reynolds number is analyzed in order to find an optimum airfoil section for the MAV prototype. A small-sized propulsion testing setup is built to measure the performance of the motor-gear-propeller-battery combination so that an efficient propulsion system can be obtained. The TH360 MAV with a payload of a self-made micro color video image system has been successfully tested in the real-time flight, where the real-time images of the ground target can be transmitted from the onboard video camera to the ground.

This paper presents an investigation of autonomous hovering flight control of micro air vehicles (MAVs). The control system consists of an onboard section with a self-made micro azimuth gradienter sensor and a ground station. An open-loop control strategy named teaching-by showing based control is proposed by stimulating a skilled human operator's manipulation of the aircraft, with the objective of learning operator's manipulation and then generating a set of command data to control MAV's hovering. A feedforward plus a PD feedback control is further employed to control the aircraft using the command data generated in the open-loop control. The PD control gains are tuned automatically according to the attitude of the vehicle by fuzzy logic theory. The effectiveness of the proposed approach is validated in autonomous hovering flight experiments conducted on a one-meter sized aircraft.