Observational analysis with a sliding mode controller improves VTOL angle control, suggesting enhanced stability in simulations.
In this paper, a predefined-time emotion controller (PTEC) is proposed for the control of vertical takeoff and landing system (VTOL). Firstly, the double closed-loop mathematical model of VTOL is introduced. Sliding mode controller (SMC) with a dynamic boundary layer and predefined-time sliding mode controller (PTSMC) are designed for the voltage-current inner-loop (VCIL) and the current-angle outer-loop (CAOL) of the VTOL, respectively. It is proved that the VTOL with the proposed method can converge within predefined-time. Secondly, a continuous radial basis function emotional neural network (CRBENN) with better accuracy than radial basis function neural network (RBFNN) is adopted to approximate the equivalent control term of PTSMC to ensure the control of VTOL with partial unknown dynamics in the model. The update rate of CRBENN is designed by the Lyapunov method, and the whole system stability is ensured. Finally, both of the simulations and the physical experiments show that the VTOL can achieve the desired angle within a predefined-time and has good performance.
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Jia et al. (2025) studied this question.
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