Fixed-time control of multi-motor nonlinear systems via adaptive neural network dual sliding mode

Abstract

This paper proposes a fixed-time control method integrating backlash, friction, and unknown time-varying delay compensation to achieve precise load position tracking and speed synchronization in multi-motor systems. First, the novel tracking and synchronization control strategies are developed based on adaptive neural network (NN) dual sliding modes. The sliding mode surfaces are designed based on tracking and synchronization errors, respectively, and adaptive neural networks are employed to approximate unknown nonlinear functions. This approach ensures fixed-time convergence independent of the initial states of the system, with convergence time determined a priori and capable of ensuring satisfactory dynamic performance. Secondly, a new exponential Lyapunov-Krasovskii functional is constructed to compensate for the uncertainties of time-varying delays without requiring prior knowledge of the upper bound of delay nonlinearities. Finally, the effectiveness of the proposed approach is validated through simulation results.