A continuous simulated annealing algorithm with global convergence ability is applied to solve this controller parameters optimization design problem.
采用一类全局收敛的连续模拟退火算法完成了控制器参数的优化设计。
In this paper, we study a new kind of evolutionary algorithm for global optimization over continuous Spaces, a revision of Differential evolution based on piecewise two-dimensional search.
本文研究了一种求解连续变量空间全局优化的进化算法，基于分片二维搜索的修正微分进化算法。
The algorithm is a random searching algorithm in nature. It can converge to the global minima more probability and be adept in continuous functions optimization.
该算法本质上是一种随机搜索算法，并能以较大概率收敛到全局最优，特别适用于连续函数的优化。
The algorithm is a random searching algorithm in nature. It can converge to the global minima more probability and be adept in continuous functions optimization.
该算法本质上是一种随机搜索算法，并能以较大概率收敛到全局最优，特别适用于连续函数的优化。
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