Collision avoidance strategies for multiple unmanned aerial vehicles (UAVs) based on geometry are investigated in this study. The proposed strategies allow a group of UAVs to avoid obstacles and separate if necessary through a simple algorithm with low computation by expanding the collision-cone approach to formation of UAVs. The geometric approach uses line-of-sight vectors and relative velocity vectors where dynamic constraints are included in the formation. Each UAV can determine which plane and direction are available for collision avoidance. An analysis is performed to define an envelope for collision avoidance, where angular rate limits and obstacle detection range limits are considered. Based on the collision avoidance envelope, each UAV in a formation determines whether the formation can be maintained or not while avoiding obstacles. Numerical simulations are performed to demonstrate the performance of the proposed strategies.

This paper presents a methodology for coordinated standoff tracking of moving target groups using multiple unmanned aerial vehicles (UAVs). The vector field guidance approach for a single UAV is first applied to track a group of targets by defining a variable standoff orbit to be followed, which can keep all targets within the field-of-view of the UAV. A new feedforward term is included in the guidance command considering variable standoff distance, and the convergence of the vector field to the standoff orbit is analyzed and enhanced by adjusting radial velocity using two active measures associated with vector field generation. Moreover, for multiple group tracking by multiple UAVs, a two-phase approach is proposed as a suboptimal solution for a Non-deterministic Polynomial-time hard (NP-hard) problem, consisting of target clustering/assignment and cooperative standoff group tracking with online local replanning. Lastly, localization sensitivity to the group of targets is investigated for different angular separations between UAVs and sensing configurations. Numerical simulations are performed using randomly moving ground vehicles with multiple UAVs to verify the feasibility and benefit of the proposed approach.

This article was published in the Journal of Guidance, Control, and Dynamics [© American Institute of Aeronautics and Astronautics] and it was presented at the AIAA Guidance, Navigation, and Control Conference, Portland, Oregon, US, 8-11 Aug 2011. The definitive version is available at: http://dx.doi.org/10.2514/1.56254This paper proposes a nonlinear model-predictive control framework for coordinated standoff tracking by a pair of unmanned aerial vehicles. The benefit of this approach is to get optimal performance compared with using a decoupled controller structure: heading control for standoff-distance keeping and speed control for phase keeping. The overall controller structure is fully decentralized as each unmanned aerial vehicle optimizes its controller based solely on the future propagation of the pair vehicle states and the target estimates received via communication. This paper uses an acceleration model for sophisticated and realistic target dynamics, which can consider a more reasonable system noise covariance matrix reflecting the target’s motion characteristics. To simplify optimization formulation and decrease computation burden, a new manipulation using the inner product of position vectors of the unmanned aerial vehicles with respect to the target position is proposed for antipodal tracking instead of using the relative phase-angle difference. To consider a more realistic situation, inequality constraints are considered for collision avoidance between unmanned aerial vehicles and control input saturations using penalty functions in the model-predictive control scheme. Simulations with a pair of unmanned aerial vehicles are done using realistic car trajectory data in an urban environment in the United Kingdom to verify the feasibility and benefit of the proposed approach with comparing to a Lyapunov vector field guidance

This paper was published in the journal Control Engineering Practice [© Elsevier Ltd]. The definitive version is available at: http://dx.doi.org/10.1016/j.conengprac.2014.04.003.This paper investigates the use of small UAVs as communication relay nodes for expanding communication links and improving communication quality for a fleet of naval vessels. This paper firstly deals with the UAV deployment for stationary communication nodes, and then, proposes a decentralised nonlinear model predictive trajectory planning strategy for a dynamic environment. By exploiting motion estimates of vessels and states of UAVs, the trajectory planning algorithm finds a control input sequence optimising network connectivity over a certain time horizon. Numerical simulations are performed for both stationary and manoeuvring vessels to verify the feasibility and benefit of the proposed approach

A guidance and control system is proposed for automatic carrier landing of an unmanned aerial vehicle. To this end, the position and attitude of the carrier is predicted by considering the sea state so that the UAV guidance loop can be compensated during the final approach phase. The landing kinematics and reference trajectory are determined using the predicted touchdown position. Nonlinear guidance and control laws are designed based on a sliding-mode control scheme to make the UAV robustly follow the reference trajectory

This paper proposes a new interacting multiple model (IMM) filter for actuator fault detection. Since each individual filter of the IMM filter uses the combined information of the estimation values from all the operating filters, it can effectively estimate system parameter variations, thereby it can diagnose the actuator damage with an unknown magnitude. In this study, to diagnose the actuator failure fast and accurately, fuzzy logic is used to tune a transition probability among multiple models. This makes the fault detection process smooth and reduces the possibility of false fault detection. Also, a discrete fault tolerant command tracker is derived to cope with actuator damages. To validate the performance of the proposed fault detection and diagnosis (FDD) algorithm, numerical simulations are performed for a high performance aircraft system.