Predefined-time sliding mode control for position and attitude of quadrotor with variable exponent coefficients

This paper presents a comprehensive study on predefined-time sliding mode control applied to quadrotor systems with variable exponent coefficients. The main goal is to achieve efficient control with predefined-time convergence to the desired target. Novel predefined-time sliding mode control and predefined-time neural networks sliding model control algorithms are developed to adapt to the dynamics of variable coefficients and ensure system stability. The stability analysis confirms their capability to achieve predefined-time convergence. Extensive numerical simulations on diverse nonlinear systems validate the superiority of the proposed approach over conventional sliding mode control and neural networks control.