Guidance and control of standoff air-to-surface carrier vehicle

Abstract

This paper presents an open framework, through which, conventional general purpose aerial munitions can be converted into smart munitions. The retrofit consists of a smart adaptation kit (SAK) having a dedicated Guidance and Control Module (GCM). The adaptation kit along with the GCM ensures that the SAK glide optimally towards the designated target. To reduce cost, the number of control surfaces of the SAK has been kept to a bare minimum, which resulted in an under actuated system. The methodology proposed utilises the theory of gain-scheduled control and leads to an efficient procedure for the design of the controllers, which accurately track reference trajectories defined in an inertial reference frame. The paper illustrates the application of this procedure to the design of stabilisation and tracking controller for the SAK. The design phase is summarised, and the performance of the resulting controllers is assessed in simulation using dynamic model of the vehicle. Simulation results show that apart from improved circular error probable (CEP) of hitting the target, munition ballistic range has also significantly increased with the proposed modification.

Deep Reinforcement Learning for Integrated Non-Linear Control of Autonomous UAVs

“…The UAV configuration consisting of 'V' tail with inverted fin have been adopted to meet the challenging performance requirements and aerodynamic characteristics. In this paper, the flight dynamics are modelled using the 6-DOF model, which is often used to represent vehicle motion in 3D space [36][37][38][39][40][41][42].…”

A Consolidated Review of Path Planning and Optimization Techniques: Technical Perspectives and Future Directions

“…The performance analysis shows that both the configurations include minimum aerodynamic efficiency and wind shear. Imran Mir et al [7] researched aerial munitions that can be modeled into smart munitions. The model has a smart adaptation kit (SAK) with a Guidance and Control Module (GCM).…”

“…Advancement in research and commercial technology made it conceivable for UAVs, robots, and their related application to appear in our daily life activities at an unprecedented rate [2,3]. For UAVs, Dull Dirty and Dangerous (DDD) missions [4][5][6][7][8][9][10][11] are the most prominent applications, whereas for robotics, iRobot applications [12] and Self-Driven cars [13] have gained much importance in research area as well as in commercial technology. Such vehicles require autonomous path planning algorithms to be energy/time efficient for their implementation.…”

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