为了提高内部凸近似的性能,用于次优非线性MPC
IEEE transactions on cybernetics
|July 17, 2025
概括
这项研究通过加速内近似来改进非线性模型预测控制 (MPC). 新方法提高了更快,更高效的实时控制应用程序的收率.
科学领域:
- 控制工程 控制工程 控制工程
- 应用数学 应用数学 应用数学
背景情况:
- 内近似使得实时的非线性模型预测控制 (MPC) 成为可能.
- 传统方法的趋同缓慢,在采样时间内性能受到限制.
研究的目的:
- 为了加速内圆近似的收率,以获得低于最佳的MPC.
- 提高实时MPC系统的整体性能.
主要方法:
- 作为一个非线性根查找问题,重构了内凸近似.
- 对非线性方程 (连续性,可微分性,雅可比式可逆性) 进行功能分析.
- 应用了布罗伊登的方法来加快根的寻找程序.
主要成果:
- 为改进的算法实现了局部超线性收率.
- 在没有显著的额外计算成本的情况下,证明了增强的融合.
- 通过避障模拟验证了有效性.
结论:
- 提出的布罗伊登方法加速算法显著提高了MPC内近似的收速度.
- 这种进步可以实现更好的实时低于最佳的MPC性能和效率.
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