基于高级滑模的微陀螺双回路递归模糊神经自适应控制

Manufacturing errors, parameter uncertainties and external disturbances will degrade the performance of the microgyroscope system. In this project, we will systematically study double-loop recurrent fuzzy neural adaptive control theories and methods for the microgyroscope based on advanced sliding mode algorithms, comprehensively use advanced sliding mode control and double-loop recurrent fuzzy neural network control methods to control and compensate the microgyroscope, and establish a theoretical framework for the dynamic recurrent fuzzy neural adaptive advanced sliding mode control of the microgyroscope. We will study the adaptive sliding mode control with double-loop recurrent fuzzy neural structure for the microgyroscope; fuzzy neural adaptive control based on fractional-order sliding mode; fuzzy neural adaptive control based on global terminal sliding mode; fuzzy neural adaptive control based on dynamic sliding mode and super-twisting sliding mode.We will study the advanced sliding mode control methods such as dynamic sliding mode, global terminal sliding mode and fractional-order sliding mode etc. and their applications in the microgyroscope. The objective of this research is to on-line estimate and compensate manufacturing errors, parameter uncertainties and external disturbances, improve the robustness, sensitivity and accuracy of the control system, and enhance the dynamic and robust performance of the microgyroscope. The research of this project has important academic value and application potential, it is of great significance to the theory of recurrent fuzzy neural adaptive advanced sliding mode control and the research of microgyroscope control.

制造误差、参数不确定性和外部干扰都会降低微陀螺系统的性能。本项目系统研究基于高级滑模的微陀螺双回路递归模糊神经自适应控制理论与方法,综合运用高级滑模控制、双回路递归模糊神经网络控制等方法控制和补偿微陀螺,建立微陀螺动态递归模糊神经网络自适应高级滑模控制理论框架。研究双回路递归模糊神经网络自适应滑模控制;基于分数阶滑模的微陀螺模糊神经网络自适应控制;微陀螺全局终端滑模模糊神经自适应控制;微陀螺动态滑模和超扭曲滑模模糊神经自适应控制;研究高级滑模控制方法如动态滑模控制、全局终端滑模、分数阶滑模等及其在微陀螺中的应用。研究目的是在线估计和补偿制造误差、参数不确定性和外界干扰,提高灵敏度和精度,增强系统动态和鲁棒性能。本项目研究具有重要的学术价值和应用前景,对递归模糊神经自适应高级滑模控制理论和微陀螺控制研究具有重要的意义。

微陀螺是惯性导航和制导系统的基本测量元件,采用有效的控制方法补偿微陀螺制造误差、参数的不确定性、外部干扰和非线性环节,提高输出精度和鲁棒性,具有重要的理论和现实意义。本项目研究基于高级滑模的微陀螺双回路递归模糊神经自适应控制理论与方法,综合运用高级滑模控制、双回路递归模糊神经控制等方法控制微陀螺,建立微陀螺动态递归模糊神经网络自适应高级滑模控制理论框架。研究增加输出反馈回路的双回路递归模糊神经网络控制;研究超扭曲滑模、终端滑模、分数阶滑模等高级滑模控制方法和双回路递归模糊神经网络高级滑模控制方法及其在微陀螺中的应用。研究目的是辨识系统参数,补偿制造误差、参数不确定性和外部干扰,提高灵敏度和精度,增强系统动态和鲁棒性能。本项目研究成果具有重要学术价值和应用前景,为神经网络滑模控制理论发展及其应用提供原创性方法。