Identification Modeling Based on RBFNN for an Aerial Inertially Stabilized Platform*

Xiangyang Zhou, Weiqian Wang, Yanjun Shi
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Abstract

Aiming at the serious influence of multi-source disturbances on the control precision of inertially stabilized platform (ISP), an accurate identification modeling method based on RBFNN for the ISP system is proposed. Since the ISP control system under the multi-source disturbances is a nonlinear, parameters uncertain, and time-varying system, the conventional modeling method cannot accurately describe the system characteristics. Therefore, more accurate modeling should be conducted. In the proposed modeling method, an off-line/on-line composite identification method is proposed to ensure the real-time performance in the dynamic adjustment process of the model, and the basis for the design of adaptive controller is designed. Besides, the simulation analysis and the experimental validation are performed and consistent conclusions are gotten.
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基于RBFNN的航空惯性稳定平台识别建模*
针对多源干扰对惯性稳定平台(ISP)控制精度的严重影响,提出了一种基于RBFNN的惯性稳定平台系统精确辨识建模方法。由于多源干扰下的ISP控制系统是一个非线性、参数不确定、时变的系统,传统的建模方法无法准确描述系统的特性。因此,需要进行更精确的建模。在该建模方法中,为了保证模型动态调整过程的实时性,提出了离线/在线复合辨识方法,并为自适应控制器的设计奠定了基础。并进行了仿真分析和实验验证,得到了一致的结论。
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