Observer-Based Disturbance Estimation and Optimal Allocation for the Roll Control of an Unmanned Motorcycle with Control Moment Gyros

For the roll control of an unmanned motorcycle equipped with twin control moment gyros (CMGs), the optimal allocation between the steering motor and CMGs when encountering strong disturbance is rarely investigated in existing studies. In this paper, based on an extended state observer (ESO) and a novel control allocator (CA), a robust control scheme ESO-CA is proposed for the unmanned motorcycle to resist disturbances. The ESO enables the estimation and compensation of the lumped disturbance, which incorporates unmodeled dynamics, parameter perturbations and external disturbances. Based on a novel optimization formulation that considers the integral saturations of actuators, the control allocation method is developed to minimize total energy consumption and reduce steering chattering. Two comparative numerical simulations and one physical experiment are provided to demonstrate the effectiveness of the proposed control scheme.