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

机译: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

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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.
机译:为了从系统中获得良好的性能,性能指标在目标功能中起着至关重要的作用。在本文中,各种性能指标被用作目标函数。目标函数的选择是将任何优化算法应用于自适应控制系统的最关键和最复杂的步骤。它们用于评估项目的适用性以进行迭代。各种目标函数,例如均方误差(MSE),时间积分乘以绝对误差(ITAE),误差绝对幅度的积分(IAE),平方误差积分(ISE)和时间积分乘以已对平方误差(ITSE)进行了分析和比较,以找到最合适的误差。应用蚁群优化算法对PID控制器进行优化,以找出最佳解决方案,并研究不同性能指标的行为。

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