Adaptive state-constrained/model-free iterative sliding mode control for aerial robot trajectory tracking

doi:10.1007/s10483-024-3103-8

摘要/Abstract

Abstract:

This paper develops a novel hierarchical control strategy for improving the trajectory tracking capability of aerial robots under parameter uncertainties. The hierarchical control strategy is composed of an adaptive sliding mode controller and a model-free iterative sliding mode controller (MFISMC). A position controller is designed based on adaptive sliding mode control (SMC) to safely drive the aerial robot and ensure fast state convergence under external disturbances. Additionally, the MFISMC acts as an attitude controller to estimate the unmodeled dynamics without detailed knowledge of aerial robots. Then, the adaption laws are derived with the Lyapunov theory to guarantee the asymptotic tracking of the system state. Finally, to demonstrate the performance and robustness of the proposed control strategy, numerical simulations are carried out, which are also compared with other conventional strategies, such as proportional-integral-derivative (PID), backstepping (BS), and SMC. The simulation results indicate that the proposed hierarchical control strategy can fulfill zero steady-state error and achieve faster convergence compared with conventional strategies.

Key words: aerial robot, hierarchical control strategy, model-free iterative sliding mode controller (MFISMC), trajectory tracking, reinforcement learning

中图分类号:

93C10
93C85

. [J]. Applied Mathematics and Mechanics (English Edition), 2024, 45(4): 603-618.

Chen AN, Jiaxi ZHOU, Kai WANG. Adaptive state-constrained/model-free iterative sliding mode control for aerial robot trajectory tracking[J]. Applied Mathematics and Mechanics (English Edition), 2024, 45(4): 603-618.

图/表 10

参考文献 34

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