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Reconfigurable Intelligent Control Architecture of a Small-Scale Unmanned Helicopter

机译:小型无人直升机的可重构智能控制架构

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Over the past decades, substantial research has been undertaken in the design of intelligent architecture for the rotorcraft-based unmanned aerial vehicles (RUAV). Designing intelligent architecture is a challenging problem because future RUAVs are utterly autonomous and their performance is comparable with that of manned vehicles. This paper deals with the design and development of a layered architectural framework that addresses the issue arising in autonomous intelligent control systems. The architecture consists of two layers. The high-level layer is occupied by planning routines. In this level, the waypoints and mission tasks from the command center are executed. The function of the low-level layer is to stabilize the flight and follow the commanded trajectory from the upper layer. These layers integrate the following functionalities: (1) waypoint navigation and control, which includes auto-landing; (2) obstacle detection and avoidance; (3) fault detection and identification; and (4) system reconfiguration in two levels (high-level and low-level controllers). The resulting layered architecture is discussed in detail. Moreover, the novel fault detection and identification method is developed to address multiplicative and additive faults. A testing environment for RUAV is developed to validate this architecture. Complete setup is carried out using an embedded board run under a real-time operating system. The algorithms are tested and evaluated using hardware-in-the-loop simulation (HILS). The simulation result proves that the proposed architecture demonstrates the desired efficiency and reliability.
机译:在过去的几十年中,已经在基于旋翼飞机的无人机(RUAV)的智能架构设计方面进行了大量研究。设计智能体系结构是一个具有挑战性的问题,因为未来的RUAV完全是自主的,其性能可与有人驾驶车辆媲美。本文讨论了分层体系结构框架的设计和开发,该框架解决了自主智能控制系统中出现的问题。该体系结构由两层组成。计划例程占用了高层。在此级别,执行来自命令中心的航路点和任务任务。低层的功能是稳定飞行并遵循上层命令的轨迹。这些层集成了以下功能:(1)航点导航和控制,包括自动着陆; (2)障碍物的发现与规避; (3)故障检测与识别; (4)分两个级别(高级和低级控制器)进行系统重新配置。将详细讨论最终的分层体系结构。此外,开发了新颖的故障检测和识别方法来解决乘法和附加故障。开发了用于RUAV的测试环境以验证该体系结构。完整的设置使用在实时操作系统下运行的嵌入式板进行。使用硬件在环仿真(HILS)对算法进行测试和评估。仿真结果表明,所提出的架构具有预期的效率和可靠性。

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