CAJ | 학술논문

随着控制技术的发展，控制对象的规模越来越大，使得辨识算法的计算量也越来越大。对于结构复杂的非线性系统，特别是包含未知参数乘积的非线性系统，使得过参数化辨识方法的参数数目大幅度增加，辨识算法的计算量也急剧增加，因此探索计算量小的参数估计方法势在必行。针对输出非线性方程误差类系统，讨论了基于过参数化模型的递推最小二乘类辨识方法；为减小过参数化辨识算法的计算量和提高辨识精度，分别利用分解技术和数据滤波技术，研究和提出了基于模型分解的递推最小二乘辨识方法和基于数据滤波的递推最小二乘辨识方法。最后给出了几个典型辨识算法的计算量、计算步骤、流程图。
수착공제기술적발전，공제대상적규모월래월대，사득변식산법적계산량야월래월대。대우결구복잡적비선성계통，특별시포함미지삼수승적적비선성계통，사득과삼수화변식방법적삼수수목대폭도증가，변식산법적계산량야급극증가，인차탐색계산량소적삼수고계방법세재필행。침대수출비선성방정오차류계통，토론료기우과삼수화모형적체추최소이승류변식방법；위감소과삼수화변식산법적계산량화제고변식정도，분별이용분해기술화수거려파기술，연구화제출료기우모형분해적체추최소이승변식방법화기우수거려파적체추최소이승변식방법。최후급출료궤개전형변식산법적계산량、계산보취、류정도。
With the development of control technology,the scales of the control systems become larger and larger, so does the computational load of the identification algorithms.For nonlinear systems with complex structures,espe?cially for the nonlinear systems that contain the products of the unknown parameters of the nonlinear part and linear part,the sizes of the involved matrices in the over?parameterization model based least squares methods greatly in?crease,this makes the computational amount of the identification algorithms increase dramatically. Therefore, it is necessary to explore new parameter estimation methods with less computation. For output nonlinear equation?error type systems,this paper discusses the over?parameterization model based recursive least squares type identification algorithms;in order to reduce computational loads and improve the identification accuracy,this paper uses the de?composition technique and the filtering technique and presents the model decomposition based recursive least squares identification methods and the filtering based recursive least squares identification methods.Finally,the com?putational efficiency,the computational steps and the flowcharts of several typical identification algorithms are dis?cussed.