This paper proposes a composite non-singular fast terminal sliding mode attitude control scheme based on a reduced-order extended state observer for the stratospheric airship’s attitude system affected by multiple disturbances. First, the feedback linearisation method is applied to address the nonlinearity of the attitude motion model and achieve decoupling of the model in three channels. Second, the overall disturbances, encompassing airship parameter perturbations and external disturbances, are treated as an aggregate. A reduced-order extended state observer is designed for each channel to formulate a composite non-singular fast terminal sliding mode surface. In the control design phase, the hyperbolic sine function is adopted as replacement for the sign function to ensure the continuity of the control signal. The estimated disturbances are incorporated in the control law design to directly offset the effects of multiple disturbances on the attitude motion of the airship. Third, based on Lyapunov theory, it has been proven that the control law can drive the attitude tracking error to converge to zero within a finite time. Simulation results demonstrate that the proposed control scheme exhibits favorable disturbance rejection capability, as well as higher tracking accuracy and faster response speed.

This paper concentrates on the trajectory tracking problem for a stratospheric airship subject to underactuated dynamics, unmeasured velocities, modeling inaccuracies and environmental disturbances. First, a coordinate transformation is performed to solve the underactuated issue, which simultaneously permits a priori assignment of the tracking accuracy. Second, a finite-time observer is integrated into the control structure to offer the exact information of unmeasured velocities and uncertainties in an integral manner. Then, by combining the backstepping technique with the method of adding a power integrator, a new output-feedback control strategy is derived with several salient contributions: (1) the airship’s position errors fall into a predetermined residual region near zero within a finite settling time and stay there, while all the closed-loop signals maintain bounded during operation; and (2) no artificial neural networks and filters are adopted, resulting in a low-complexity control property. Furthermore, the presented method can be extended readily to a broad range of second-order mechanical systems as its design builds upon a transformed system model. Rigorous mathematical analysis and simulations demonstrate the above theoretical findings.

Stratospheric airships are promising aircraft, usually designed as a non-rigid airship. As an essential part of the non-rigid airship, the envelope plays a significant role in maintaining its shape and bearing the external force load. Generally, the envelope material of a flexible airship consists of plain-weave fabric, composed of warp and weft fibre yarn. At present, biaxial tensile experiments are the primary method used to study the stress–strain characteristics of such flexible airship materials. In this work, biaxial tensile testing of UN-5100 material was carried out. The strain on the material under unusual stress and the stress ratio were obtained using Digital Image Correlation (DIC) technology. Also, the stress–strain curve was corrected by polynomial fitting. The slope of the stress–strain curve at different points, the Membrane Structures Association of Japan (MSAJ) standard and the Radial Basis Function (RBF) model were compared to identify the stress–strain characteristics of the materials. Some conclusions on the mechanical properties of the flexible airship material can be drawn and will play a significant role in the design of such envelopes.

In this article, we investigate the horizontal trajectory tracking problem for an underactuated stratospheric airship subject to nonvanishing external disturbances and model uncertainties. By transforming the tracking errors into new virtual error variables, we can specify the transient and steady-state tracking performance of the resulting nonlinear system quantitatively, which means that under the proposed control scheme, the tracking errors will converge to prescribed residual sets around the origin before a preselected finite time with decay rates no less than a preassignable value. To address unknown items, minimal learning parameter (MLP) techniques for neural networks (NNs) approximation are employed, which efficaciously relax the computational burden, enhance the robustness against dynamics uncertainties and provide an improved property for disturbances rejection. A finite-time convergent observer (FTCO) is incorporated into the control framework to realise output-feedback control, ensuring that estimation errors are bounded during operation and approach zero within a finite time. Stability analysis proves that all the closed-loop signals are uniformly bounded. The effectiveness and advantages of the proposed control strategy are verified by simulation results.