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Robust Adaptive Self-Organizing Wavelet Fuzzy CMAC Tracking Control for Deicing Robot Manipulator

机译:除冰机器人的鲁棒自适应自组织小波模糊CMAC跟踪控制

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摘要

In this paper, a robust adaptive self-organizing control system based on a novel wavelet fuzzy cerebellar model articulation controller (WFCMAC) is developed for an n-link robot manipulator to achieve the high-precision position tracking. This proposed controller consists of two parts: one is the WFCMAC approach which is implemented to cope with nonlinearities, due to the novel WFCMAC not only incorporates the wavelet decomposition property with fuzzy CMAC fast learning ability but also it will be self-organized; that is, the layers of WFCMAC will grow or prune systematically. Therefore, dimension of WFCMAC can be simplified. The second is the order which is the adaptive robust controller which is designed to achieve robust tracking performance of the system. The adaptive tuning laws of WFCMAC parameters and error estimation of adaptive robust controller are derived through the Lyapunov function so that the stability of the system can be guaranteed. Finally, the simulation and experimental results of novel three-link deicing robot manipulator are applied to verify the effectiveness of the proposed control methodology.
机译:本文为n链接机器人操纵器开发了一种基于新型小波模糊小脑模型关节控制器(WFCMAC)的鲁棒自适应自组织控制系统,以实现高精度的位置跟踪。该控制器由两部分组成:一是为解决非线性问题而设计的WFCMAC方法,由于新颖的WFCMAC不仅融合了具有模糊CMAC快速学习能力的小波分解特性,而且具有自组织性。也就是说,WFCMAC的层将系统地增长或修剪。因此,可以简化WFCMAC的尺寸。第二个是阶,它是自适应鲁棒控制器,旨在实现系统的鲁棒跟踪性能。通过Lyapunov函数推导了WFCMAC参数的自适应调整规律和自适应鲁棒控制器的误差估计,从而可以保证系统的稳定性。最后,利用新型三连杆除冰机器人机械手的仿真和实验结果,验证了所提控制方法的有效性。

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