蚁群算法在自适应控制系统性能指标计算与分析中的应用

2014 Innovative Applications of Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH) Pub Date : 2014-11-01 DOI:10.1109/CIPECH.2014.7019078

A. Q. Ansari, Ibraheem, Sapna Katiyar

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引用次数: 11

摘要

为了使系统获得良好的性能，性能指标在目标函数中起着至关重要的作用。本文采用各种性能指标作为目标函数。目标函数的选择是应用自适应控制系统优化算法中最关键和最复杂的步骤。它们用于评估迭代项目的适应度。分析和比较了各种目标函数，如均方根误差(MSE)，时间乘以绝对误差的积分(ITAE)，误差绝对值的积分(IAE)，平方误差的积分(ISE)和时间乘以平方误差的积分(ITSE)，以找到最合适的一个。采用蚁群优化算法对PID控制器进行调整，找出最优解，并研究不同性能指标的行为。

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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Application of ant colony algorithm for calculation and analysis of performance indices for adaptive control system

To achieve good performance from the system, performance index plays vital role in the objective function. In this paper various performance indices are used as the objective functions. The choice of the objective function is the most crucial and complicated step in applying any optimizing algorithm for an adaptive control system. They are used to evaluate fitness of items for iterations. The various objective functions like Mean of the Squared Error (MSE), Integral of Time multiplied by Absolute Error (ITAE), Integral of Absolute Magnitude of the Error (IAE), Integral of the Squared Error (ISE) and Integral of Time multiplied by the Squared Error (ITSE) have been analyzed and compared to find the most suitable one. Ant Colony Optimization algorithm is applied to tune a PID controller to find out best solution and to study the behavior of different performance indices.

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2014 Innovative Applications of Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH)

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