Fast terminal synergetic control for morphing quadcopter with time-varying parameters

To enhance flexibility and improve versatility, recent research has focused on the development of variable structure vehicles. In line with this, this paper introduces a morphing quadcopter with time-varying parameters that enables independent rotation of its arms around the main body. This study highlights the influence of these parameters on the geometric properties, dynamics, flight stability, and control of this aerial robot, while considering nonlinear functions, unknown parameters, and external disturbances. The system dynamics are derived using Newton-Euler formalism, and a robust control approach based on synergetic theory is proposed. The distinctive features of this strategy are demonstrated through finite-time convergence, enhanced control accuracy, and effective chattering suppression. In the control aspect, a Synergetic Controller (SC) is initially developed and further improved by incorporating fast finite-time convergence of the state variables. A comparative study is conducted, quantitatively and qualitatively, among four controllers: BackStepping (BS) controller, Sliding Mode Controller (SMC), SC, and Fast Terminal Synergetic Controller (FTSC). The FTSC exhibits numerous advantages, including rapid tracking towards desired states, adaptability to varying system parameters and uncertain external disturbances, as well as suitability for digital implementation. To conduct a significant comparative study, a Genetic Algorithm is employed to select the optimal gains for each control technique. Additionally, to imitate the real situation as much as possible, external disturbances are considered in the performed numerical simulation. Overall, the results demonstrate that the proposed control technique outperforms in terms of accuracy and robustness. It offers superior control performance and effective handling of system variations and external disturbances, making it a promising approach for the morphing quadcopter system.& COPY; 2023 Elsevier Masson SAS. All rights reserved.