Adaptive backstepping trajectory tracking controller for a miniature helicopter

Abstract

An adaptive backstepping controller is proposed to achieve the asymptotically stable trajectory tracking for a miniature helicopter. The helicopter model is firstly decomposed into a cascaded structure between the position and attitude loops with unmodeled dynamics. The backstepping technique is applied to exploit this cascaded structure and to streamline the controller design procedure. Hyperbolic tangent functions, instead of traditional sign functions, are adopted to complete adaptive algorithms for adjusting the upper bounds of the unmodeled dynamics. Further, the controller introduces an auxiliary dynamic system to ensure the thrust constraint and to obviate singularity during the command attitude extraction. The stability analysis demonstrates that, the asymptotical stability of the auxiliary dynamic system warrants the asymptotically stable tracking of the miniature helicopter system. Simulations verify the theoretical results and analyze the tracking performance.

Two time‐scale assignment with state extension for an autonomous helicopter

“…They demonstrate that the phenomenon results from the non-minimum phase behavior, and illustrate that the flapping angle, which produces the pitching moment and induces a horizontal component of force, can not be neglected. Thus the methods based on the approximation of non-minimum phase character in [3,4,[6][7][8] can only guarantee local bounded tracking.…”

“…Tracking control design of the autonomous unmanned helicopter (AUH) has gained considerable attention from a large number of researchers [1][2][3][4]. The forces of an AUH are generated by cyclic pitch, which couples with the moments produced by the flapping angle.…”

“…During the past decades, many approaches to the negligence of the aforementioned coupling have been proposed [3,4,[6][7][8][9]. Control methods such as feedback lineariza-tion [3,10], backstepping strategy [4,11,12], dynamic inversion [6,9], and neural-network based methods [8,13] were implemented on a simplified model. However, it has been demonstrated that such a simplification may cause the aforementioned techniques to result in limitations in the operating regimes, and inaccurately followed reference commands [5,14,15].…”

“…During the past decades, many approaches to the negligence of the aforementioned coupling have been proposed [3,4,6–9]. Control methods such as feedback linearization [3,10], backstepping strategy [4,11,12], dynamic inversion [6,9], and neural‐network based methods [8,13] were implemented on a simplified model.…”

High‐order mismatched disturbance rejection control for small‐scale unmanned helicopter via continuous nonsingular terminal sliding‐mode approach

“…Therefore, it is imperative to investigate finite-time robust flight controllers for unmanned helicopters in the presence of disturbances. [3][4][5][6] In the past decades, many elegant control methods have been employed for the unmanned helicopters, such as linear quadratic gaussian, 7 H ∞ , 8 feedback-linearization control, 9 backstepping, 10 sliding-mode control (SMC). 11 Above all, the SMC method has drawn much attention for its superior disturbance rejection ability.…”