A Gaussian wavelet network-based robust adaptive tracking controller for a wheeled mobile robot with unknown wheel slips

AbstractIn this paper, a robust adaptive tracking controller based on a Gaussian wavelet network is proposed for a nonholonomic wheeled mobile robot (WMR) in the presence of unknown wheel slips, model uncertainties, and unknown bounded disturbances. The role of the Gaussian wavelet network in this proposed controller is to approximate unknown smooth nonlinear dynamic functions due to no prior knowledge of the dynamic parameters of the WMR by using an online adaptive update law by which the gains of the dilations and translations of Gaussian wavelet functions are trained online. In addition, two robust control laws are utilized in this proposed control method, where one is employed at the kinematic level so as to compensate the harmful effects of the unknown wheel slips, and the other is used at the dynamic level in order to overcome total uncertainties caused by dynamic parameter variations, external disturbances, and/or the inevitable approximation errors resulting from the finite number of wavelet basis...