Adversarial Ground Target Tracking Using UAVs with Input Constraints.
ABSTRACT This paper deals with the problem of adversarial ground target tracking using Unmanned Aerial Vehicles (UAVs) subject to input
constraints. For adversarial ground target tracking, tracking performance and UAV safety are two important considerations
during tracking controller design. In this paper, a bang-bang heading rate controller is proposed to achieve circular tracking
around the target. Exposure avoidance of the UAV to the target and minimizing the exposure time are studied respectively in
terms of the initial state of the UAV. The performance of the proposed controller in both cases is also analyzed. Simulation
results demonstrate the effectiveness of the proposed approach.
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ABSTRACT: The article investigates the discrete-time controller for the longitudinal dynamics of the hypersonic flight vehicle with throttle setting constraint. Based on functional decomposition, the dynamics can be decomposed into the altitude subsystem and the velocity subsystem. Furthermore, the discrete model could be derived using the Euler expansion. For the velocity subsystem, the controller is proposed by estimating the system uncertainty and unknown control gain separately with neural networks. The auxiliary error signal is designed to compensate the effect of throttle setting constraint. For the altitude subsystem, the desired control input is approximated by neural network while the error feedback is synthesized for the design. The singularity problem is avoided. Stability analysis proves that the errors of all the signals in the system are uniformly ultimately bounded. Simulation results show the effectiveness of the proposed controller.Journal of Intelligent and Robotic Systems 01/2014; 73(1-4):219-231. · 0.83 Impact Factor
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ABSTRACT: This paper presents a 3D path planning algorithm for an unmanned aerial vehicle (UAV) in complex environments. In this algorithm, the environments are divided into voxels by octree algorithm. In order to satisfy the safety requirement of the UAV, free space is represented by free voxels, which have enough space margin for the UAV to pass through. A bounding box array is created in the whole 3D space to evaluate the free voxel connectivity. The probabilistic roadmap method (PRM) is improved by random sampling in the bounding box array to ensure a more efficient distribution of roadmap nodes in 3D space. According to the connectivity evaluation, the roadmap is used to plan a feasible path by using A* algorithm. Experimental results indicate that the proposed algorithm is valid in complex 3D environments.International Journal of Automation and Computing 12/2013; 10(6):525-533.
Conference Paper: Vector field guidance for path following and arrival angle control[Show abstract] [Hide abstract]
ABSTRACT: This paper focuses on unmanned aircraft guidance laws for a straight path and a circular orbit following using the vector field approach. The vector fields introduced in this paper can be applied to not only path following, but also other purposes such as arrival position, angle, and time control. Therefore, they could be applied to various missions providing advantages over other previous vector fields. Stability and performance of the path following has been proved and analyzed using the classical control theory. And simulation using a six degrees-of-freedom aircraft model shows that these guidance laws are effective for the missions even under the existence of wind disturbance.Unmanned Aircraft Systems (ICUAS), 2014 International Conference on; 05/2014