最佳非线性PID TSK3DCMAC控制器基于平衡复合运动优化为ballbot与外部力量
Van-Truong Nguyen1, Dai-Nhan Duong1, Duc-Hung Pham2
1Faculty of Mechatronics, SMAE, Hanoi University of Industry, Hanoi, Viet Nam.
ISA transactions
|January 24, 2025
概括
这项研究介绍了一种基于非线性PID控制器的新型Takagi-Sugeno-Kang 3D大脑模型关节控制器 (NPID-TSK3DCMAC),以提高球机稳定性. 新的控制器显著减少了错误,并提高了对外部干扰的稳定性.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 控制系统工程 控制系统工程
- 人工智能的人工智能
背景情况:
- 传统的比例积分导数 (PID) 控制器在与球机系统固有的非线性动力学和外部力量作斗争.
- 现有的控制方法在动态和变化的操作条件下经常表现出性能下降.
研究的目的:
- 开发一种创新的控制策略,以改善球机器人系统中的动态平衡和干扰排斥.
- 为了克服传统PID控制器在处理复杂的实时动态系统方面的局限性.
主要方法:
- 设计了一个基于非线性 PID 控制器的 Takagi-Sugeno-Kang 3D 大脑模型关节控制器 (NPID-TSK3DCMAC).
- 该控制器集成非线性PID控制,TSK3DCMAC和平衡复合运动优化 (BCMO) 算法.
- TSK3DCMAC被代训练,BCMO算法优化了控制器的收益,通过利亚普诺夫技术分析稳定性.
主要成果:
- 与PID (没有外力) 相比,NPID-TSK3DCMAC控制器显示出显著的错误减少:45.84%的MSE和25.68%的MAE减少.
- 与NPID相比,它实现了99.87%的MSE和63.91%的MAE减少 (没有外力).
- 在外部力量下,它在MSE中超过了NPID的64.94%和MAE的17.67%,证明了它的稳定性.
结论:
- 拟议的NPID-TSK3DCMAC控制器有效调节球机运动,并在外部干扰中保持稳定性.
- 该方法为要求在具有挑战性的环境中敏捷运动控制的应用提供了强大而精确的解决方案.
- 模拟和实验结果验证了控制器的卓越性能和稳定性.
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