Wavelet neural networks robust control of farm transmission line deicing robot manipulators

This paper shows some new results for the wavelet neural networks robust control of farm transmission line deicing robot manipulators (FTLDRM). A wavelet neural network is used to approximate the unknown model uncertainties and disturbances, and an adaptive robust compensator is given to compensate the lumped uncertainty. Based on the stability and neural network approximation theory, several sufficient conditions are provided which guarantee the convergence of the feedback error system. Both simulation and experimental results are given to show the superior performance of the proposed intelligent control method.

► Our results are based on the wavelet neural networks robust control method.
► Wavelet neural network is used to approximate the uncertainties and disturbance.
► Sufficient conditions are provided which guarantee the convergence of the system.
► Experimental results show the superior performance of the proposed method.
► The model principle and method are all based on the real FTLDRM system.