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首页> 外文会议>Biennial Conference on Engineering Systems Design and Analysis >A NOVEL OPTIMIZATION ALGORITHM FOR THE ESTIMATION OF ARMAX MODELS
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A NOVEL OPTIMIZATION ALGORITHM FOR THE ESTIMATION OF ARMAX MODELS

机译：一种新颖优化算法估计ARMAX模型

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摘要

This paper introduces a hybrid optimization algorithm, followed by a corresponding estimation technique, for the estimation of ARMAX. models. The hybrid algorithm consists of a stochastic component and a deterministic counterpart and aims at combining high convergence rate together with reliability in the search for global optimum. The estimation procedure is slit in two phases, due to the mixed linear-nonlinear relationship between the residuals and the parameter vector, and results in stable and invertible models. The proposed methodology is implemented in the estimation of a half-car suspension model of a road vehicle, using noise-corrupted observations, and the results yield very stable performance of the hybrid algorithm, reduced computational cost, in comparison to conventional stochastic optimization algorithms, and ability to describe satisfactory system's dynamics.
机译：本文介绍了一种混合优化算法，其次是相应的估计技术，用于估计ARMAX。楷模。混合算法包括随机分量和确定性对应物，并旨在将高收敛速率与寻求全局最佳的可靠性相结合。由于残留物和参数向量之间的混合线性非线性关系，估计过程是两个相的狭缝，导致稳定和可逆的模型。所提出的方法在估计道路车辆的半汽车悬架模型中，使用噪声损坏的观察结果，结果产生了混合算法的非常稳定的性能，与传统的随机优化算法相比，计算成本降低，能够描述令人满意的系统动态。

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