The wheeled inverted pendulum (WIP) models have been widely applied in the transportation vehicles formed by a mobile wheeled inverted pendulum system with an operator (demonstrated in  Fig. 1  ). In this paper, we focus on the study of nonlinear control design for the WIP model-based vehicles, for which accurate dynamics could not be obtained beforehand due to the presence of uncertainties caused by the human operator as well as the vehicle. We develop an output feedback adaptive neural network (NN) control incorporating a linear dynamic compensator to achieve stable dynamic balance and tracking of the desired given trajectories. Comparison simulation studies demonstrate guaranteed tracking performance and stable dynamics balance in the presence of uncertainties and thus verify the efficiency of the developed nonlinear controller.
['Zhijun Li', 'Chenguang Yang']
Neural-Adaptive Output Feedback Control of a Class of Transportation Vehicles Based on Wheeled Inverted Pendulum Models