An adaptive guidance law of a Vision Based Target Tracking (VBTT) system was previously developed and implemented onboard a Small Unmanned Aerial Vehicle (SUAV) in order to track a ground target moving with a constant velocity. This work extends previous results by considering scenarios where the variation of target velocity, in both magnitude and direction, is used to excite the feedback control law for further robustness analysis. This provides essential insight on the sensitivity of the performance criteria indicated by the range holding capability, navigation error and the convergence speed of the guidance law. In addition, this thesis addresses the robustness of the SUAV guidance law to the generalized time delay in feedback due to, for example, data processing or communications lag. This thesis also extends the previously obtained results by introducing a multi-criteria optimization technique. The results obtained are first based on the numerical simulations implemented in SIMULINK and then in high fidelity HIL simulation environment with Piccolo Plus AP in the control loop. Initial steps in developing Vision Based HIL environment incorporating TASE gimbal, Piccolo Plus AP, Pan-Tilt unit and image processing software are presented. The work also includes motivation for the development, an overview of the existing technologies, and initial implementation of low-level driving mechanism (drivers) for the realistic representation of the real-world environment.
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机译:先前已经开发并在小型无人机(SUAV)上实施了基于视觉的目标跟踪(VBTT)系统的自适应制导律,以便跟踪以恒定速度运动的地面目标。这项工作通过考虑使用目标速度在幅度和方向上的变化来激发反馈控制律以进行进一步鲁棒性分析的方案来扩展先前的结果。这对范围保持能力,导航误差和制导律的收敛速度所指示的性能标准的敏感性提供了重要的见识。另外,本文针对由于例如数据处理或通信滞后而导致的反馈中的一般时间延迟,提出了SUAV制导律的鲁棒性。本文还通过引入多准则优化技术扩展了先前获得的结果。所获得的结果首先基于在SIMULINK中实现的数值仿真,然后基于在Piccolo Plus AP控制环的高保真HIL仿真环境中进行。介绍了开发基于视觉的HIL环境的初始步骤,该环境结合了TASE云台,Piccolo Plus AP,Pan-Tilt单元和图像处理软件。该工作还包括开发的动机,对现有技术的概述以及对现实环境的真实表示的低级驱动机制(驱动程序)的初始实现。
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