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在量子连贯反中基于LQG控制器的进化优化设计
IEEE transactions on cybernetics
|January 19, 2026
概括
一个新的微分进化 (DE) 算法优化了量子系统的线性-二次-高斯 (LQG) 控制器. 这种方法提高了性能,并确保了量子应用的物理可实现性.
科学领域:
- 量子控制工程 量子控制工程
- 量子系统优化 量子系统优化
- 先进的算法设计设计先进的算法设计
背景情况:
- 设计用于量子系统的控制器,由于物理可实现性约束,提出了独特的挑战.
- 现有的控制设计方法可能无法充分满足量子系统的特定要求,影响性能和实用性.
- 线性-二次-高斯 (LQG) 控制是一个强大的框架,但其在量子领域的应用需要专门的适应.
研究的目的:
- 开发一种新的差异演化 (DE) 算法,专门用于设计量子系统中的LQG控制器.
- 提高DE的勘探和开发能力,同时确保量子应用的物理可实现性.
- 证明拟议的算法在优化量子光学系统控制器方面的有效性.
主要方法:
- 一个修改的微分演化 (DE) 算法,包含了宽松的可行性规则,预定惩罚函数,自适应性搜索范围调整和"投注和运行"初始化策略.
- 应用DE算法来设计三个不同的LQG控制器,用于具有不同配置的量子光学系统.
- 基于LQG性能指数的性能评估和物理可实现性约束的验证.
主要成果:
- 拟议的DE算法成功为量子光学系统设计了LQG控制器.
- 设计的控制器实现了卓越的性能,与现有方法相比,LQG性能指数较低.
- 所有设计的控制器都满足了物理可实现性约束,确保与实际量子平台的兼容性.
结论:
- 专门的DE算法对于设计量子系统的高性能,物理可实现的LQG控制器是有效的.
- 增强的DE框架为具有可行性约束的线性量子系统的性能优化提供了一个有前途的方法.
- 这种方法在各种量子控制和优化任务中具有广泛的应用潜力.
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