This article proposes a novel adaptive disturbance observer-based fixed-time backstepping control algorithm for uncertain robotic systems. First, an adaptive sliding mode disturbance observer (ASMDO) is designed to compensate for the lumped disturbances of the robotic system, such as model uncertainty and friction. Second, considering the actuator saturation problem of the robotic system, a new adaptive fixed-time auxiliary system is developed. Then, based on the ASMDO and the adaptive auxiliary system, a novel fixed-time backstepping tracking control algorithm is proposed to achieve faster fixed-time high accuracy tracking control for uncertain robotic systems under actuator saturation. Finally, comparative experiments validate the practicality of the proposed faster fixed-time backstepping control algorithm. Both theoretical analysis and experimental results demonstrate the superiority of the proposed fixed-time backstepping control algorithm.

In fluorescence microscopy, computational algorithms have been developed to suppress noise, enhance contrast, and even enable super-resolution (SR). However, the local quality of the images may vary on multiple scales, and these differences can lead to misconceptions. Current mapping methods fail to finely estimate the local quality, challenging to associate the SR scale content. Here, we develop a rolling Fourier ring correlation (rFRC) method to evaluate the reconstruction uncertainties down to SR scale. To visually pinpoint regions with low reliability, a filtered rFRC is combined with a modified resolution-scaled error map (RSM), offering a comprehensive and concise map for further examination. We demonstrate their performances on various SR imaging modalities, and the resulting quantitative maps enable better SR images integrated from different reconstructions. Overall, we expect that our framework can become a routinely used tool for biologists in assessing their image datasets in general and inspire further advances in the rapidly developing field of computational imaging.