With the continuous development of flapping-wing flying robot (FWFR) technology, its applications in military reconnaissance and civil monitoring are becoming increasingly widespread. However, FWFRs experience severe image jitters in aerial videos due to their unique movement patterns. These jitters are caused by periodic wing motions that include unstable rotation along the roll axis, periodic oscillations related to wing flapping, and high-frequency mechanical vibrations. These effects significantly degrade video quality and impact subsequent visual perception tasks. To address these challenges, this paper proposes a digital video stabilization method customized for FWFRs. First, an image preprocessing module is employed to deal with the roll-axis jitters, which are caused by the factors such as robot turning and crosswind disturbance during FWFR flight. Second, in order to remove periodic and high-frequency jitters and improve the computational performance of the digital video stabilization method, we design a lightweight motion smoothing network (one learns to refine noisy motion trajectories into smooth ones) primarily comprised of stacked one-dimensional convolutional layers. Leveraging this motion smoothing network, we smooth the original motion trajectories of the video and use image warping to obtain the stabilized video. Finally, extensive video stabilization experiments under various scenarios are conducted by using our self-developed FWFR named USTB-Hawk, and results demonstrate that the proposed method achieves a PSNR of 25.15 and an SSIM of 0.761, outperforming currently employed digital video stabilization methods.

This article proposes adaptive internal model controls for the collocated output regulation of a flexible wing, where distributed disturbances, boundary disturbances, and references are from an exactly unknown exosystem. Observer-based tracking error feedback controls are first designed to address the robust output regulation in case of a known exosystem matrix. If the exosystem has an unknown matrix, an adaptive observer is further proposed with the observer error system converging to zero exponentially. Then, we can obtain adaptive observer-based controls by combining adaptive observers and observer-based controls, which are able to regulate the tracking errors toward zero in case of the exactly unknown disturbances and references. The corresponding closed-loop system is proved to be internally asymptotically stable. A simulation example is further provided for adaptive internal model control of the wing system.

This article proposes an adaptive observer-based control to address the PDE–ODE coupled system of a flexible wing, where external disturbances and references have unknown frequencies, amplitudes, and phases. An exosystem is defined for the above signals, however with an unknown matrix and initial values. By finding its detectable form, an adaptive state-feedback control is designed based on an adaption law whose uncertainties are merely from the unknown exosystem matrix. In this case, filter systems are defined based on the tracking error and the observer of the PDE–ODE system, which further gives the equivalent state of the exosystem. By updating the adaption law based on the filter systems, an observer-based adaptive control is designed to guarantee the convergence of the tracking error of the closed-loop system. Two simulation results are provided and compared to demonstrate the robust output regulation of the closed-loop system.

In this article, we investigate the exponential stabilization issue of a wave equation with the external input disturbance, which is described by a nonlinear exogenous system. A novel disturbance observer is constructed to estimate the unknown input disturbance. Then, based on the proposed disturbance observer, a boundary control strategy is developed to cancel the effect of disturbance and stabilize the system. The exponential stability is proven by employing the Lyapunov’s direct method. This method can be extended to a class of flexible systems described by the hyperbolic partial differential equation met in the practical engineer area. The example of a nonuniform flexible string system is given, where the effectiveness of the proposed strategy is evaluated based on simulations.

As a kind of large flexible structure, high-rise buildings need to consider wind-resistant and anti-seismic problems for the safety of occupants and properties, especially in coastal areas. This article proposes an infinite dimensional model and an adaptive boundary control law for an active mass damper (AMD) on this question. The dynamic model of the high-rise building is a combination of some storeys which have flexible walls and rigid floors under a series of physical conditions. Then the adaptive boundary controller is acted on an AMD which is equipped on the top floor, in order to suppress the vibration of every floor and guarantee the comfort of residents. Moreover, simulations and experiments are carried out on a two-floor flexible building to illustrate the effectiveness of the proposed control strategy.

This article develops a robust fault tolerant (FT) control scheme for an n-link uncertain robotic system with actuator failures. In order to eliminate the influence of both the uncertainties and actuator failures on the system performance, the Gaussian radial basis function neural networks are used to compensate for the actuator failures and uncertain dynamics. An adaptive observer is designed to compensate for external disturbance. In addition, in order to accelerate the recovery of system stability after failure, a nonsingular fast terminal sliding mode is given. Finally, the simulation results on a two-link manipulator confirms the superior performance of the proposed neural networks-based FT controller, and the experiment results on the Baxter robot further verify the effectiveness of the control method.

Fish‐eye cameras are becoming increasingly popular in computer vision, but their use for three‐dimensional measurement is limited partly because of the lack of an accurate, efficient and user‐friendly calibration procedure. For such a purpose, the authors propose a method to calibrate the intrinsic and extrinsic parameters (including radial distortion parameters) of two/multiple fish‐eye cameras simultaneously by using a wand under general motions. Thanks to the generic camera model used, the proposed calibration method is also suitable for two/multiple conventional cameras and mixed cameras (e.g. two conventional cameras and a fish‐eye camera). Simulation and real experiments demonstrate the effectiveness of the proposed method. Moreover, the authors develop the camera calibration toolbox, which is available online.