Neural Adaptive Funnel Synchronization Control of Multi-motor Driving Systems

A funnel synchronization control strategy for a multi-motor driving system is developed to guarantee that the synchronization error can converge to a given funnel boundary. First, the tracking and synchronization problem is transformed into a stability problem by introducing a coupling synchronization error. This error is based on the tracking errors and synchronization errors between multiple motors. Second, a funnel function is constructed to actualize the state constraints, and a radial basis function (RBF) neural network is employed to estimate the uncertainty nonlinearities. Third, a funnel synchronization control protocol based on the backstepping strategy is proposed to ensure that each motor follows the reference signal and achieves speed synchronization. Finally, an example is given to demonstrate the viability of the proposed controller design strategies.