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Parameter Estimation of Damped Compound Pendulum Using Bat Algorithm

机译:基于Bat算法的阻尼复合摆参数估计。

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In this study, the parameter identification of the damped compound pendulum system is proposed using one of the most promising nature inspired algorithms which is Bat Algorithm (BA). The procedure used to achieve the parameter identification of the experimental system consists of input-output data collection, ARX model order selection and parameter estimation using bat algorithm (BA) method. PRBS signal is used as an input signal to regulate the motor speed. Whereas, the output signal is taken from position sensor. Both, input and output data is used to estimate the parameter of the autoregressive with exogenous input (ARX) model. The performance of the model is validated using mean squares error (MSE) between the actual and predicted output responses of the models. Finally, comparative study is conducted between BA and the conventional estimation method (i.e. Least Square). Based on the results obtained, MSE produce from Bat Algorithm (BA) is outperformed the Least Square (LS) method.
机译:在这项研究中,使用最有前途的自然启发算法之一蝙蝠算法(BA)提出了阻尼复合摆系统的参数识别。用于实现实验系统参数识别的过程包括输入-输出数据收集,ARX模型顺序选择和使用蝙蝠算法(BA)方法的参数估计。 PRBS信号用作调节电机速度的输入信号。而输出信号是从位置传感器获取的。输入和输出数据均用于估计具有外源输入的自回归(ARX)模型的参数。使用模型的实际和预测输出响应之间的均方误差(MSE)验证模型的性能。最后,在BA和常规估计方法(即最小二乘)之间进行了比较研究。根据获得的结果,蝙蝠算法(BA)产生的MSE优于最小二乘(LS)方法。

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