Modern Control System Learning

Brendon Smeresky, A. Rizzo
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Abstract

This manuscript will explore and analyze the effects of different controllers in an overall spacecraft’s attitude determination and control system (ADCS). The experimental setup will include comparing an ideal nonlinear feedforward controller, a feedback controller, and a combined ideal nonlinear feedforward + feedback controller within a Simulink simulation. A custom proportional, derivative, integral controller was implemented in the feedback control, adding an additional term to account for the nonlinear coupled motion. Consistent proportional, derivative, and integral gains were used throughout the duration of the experiment. The simulated results will show that the ideal nonlinear feedforward controller lacked an error correction mechanism and took extra time to execute, the feedback controller faired only slightly better, but the combined ideal nonlinear feedforward controller with feedback correction yielded the highest accuracy with the lowest execution time. This highlights the potential effectiveness for a learning control system.
现代控制系统学习
本文将探讨和分析不同控制器对航天器姿态确定和控制系统(ADCS)的影响。实验设置将包括在Simulink仿真中比较理想的非线性前馈控制器,反馈控制器和组合的理想非线性前馈+反馈控制器。在反馈控制中实现了自定义的比例、导数、积分控制器,增加了一个额外的项来考虑非线性耦合运动。在整个实验过程中,使用了一致的比例、导数和积分增益。仿真结果表明,理想的非线性前馈控制器缺乏误差校正机制,执行时间较长,反馈控制器的性能仅略好,而结合反馈校正的理想非线性前馈控制器以最少的执行时间获得了最高的精度。这突出了学习控制系统的潜在有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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