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The application of deep learning technology to ionospheric prediction has become a new research hotspot. However, there are still some gaps, such as the prediction effect with different input solar and geomagnetic activity parameters, and the forecast accuracy with different prediction methods as well as the validation of long period data results, to be filled. We developed an ionospheric long short‐term memory network (Ion‐LSTM) with multiple input parameters to predict the global ionospheric total electron content (TEC). Two solutions with different ionospheric data based on Ion‐LSTM were assessed, namely spherical harmonic coefficients (SHC) and vertical TEC (VTEC) prediction solution. The results show two solutions, both perform well in accuracy and stability. The input of the geomagnetic activity index improves the prediction effect of the model in the storm period. For the 1‐ and 2‐day‐predicted global ionospheric maps (GIMs) from 2015 to 2020, the root mean square error (RMSE) of SHC prediction solution is 1.69 TECU and 1.84 TECU while that of the VTEC prediction solution is 1.70 TECU and 1.84 TECU, respectively. Over 70% of the absolute residuals are within 3 TECU in high solar activity and over 96% in low solar activity. Further, by comparing the predicted results between Ion‐LSTM and conventional methods (e.g., Center for Orbit Determination in Europe (CODE) predicted GIMs), the evaluation results show that the RMSE of Ion‐LSTM is 0.7 TECU lower than that of CODE predicted GIMs under different solar and geomagnetic activities. Additionally, the accuracy of the Ion‐LSTM prediction results decreases slightly as the input time span increases.

In this paper, a novel single-parameter adaptive finite time fault tolerant control (FTC) scheme is developed for an n-link robotic system with actuator fault, disturbances, system parameter uncertainties and saturation constraints. First, a finite time passive FTC (PFTC) is designed. Then, an improved control strategy called active FTC (AFTC) based on single-parameter adaptive method is studied. In this control scheme, a nonsingular fast terminal sliding mode (NFTSM) control is employed for the purpose of enhancing the robustness of the robotic system. The single-parameter adaptive method is employed to avoid obtaining the values of actuator fault, disturbances and system parameter uncertainties which reduces the complexity of the control design and the time required for online calculations. Finally, the effectiveness of the proposed single-parameter adaptive finite time AFTC scheme is verified by the simulation results.

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An accurate description of the topside ionosphere is of great importance for space weather applications. Currently, there are two commonly used empirical ionosphere models, that is, NeQuick2 and IRI-2016, that can be used to describe the topside ionosphere. In this study, topside total electron content (TEC) values derived from low Earth orbit (LEO) satellites are selected to validate the topside ionosphere predictions of the NeQuick2 and IRI-2016 models from 2008 to 2018. The results show that these two models both underestimate the topside ionosphere. Compared with the global topside ionosphere model estimated by LEO-based global positioning system (GPS) observations with orbital altitudes of 500 and 800 km, NeQuick2 and IRI-2016 have similar performances over different latitudes and longitudes. The daily mean root mean square (RMS) values are approximately 4.10 and 2.10 TEC units (TECU) for the region above 500 and 800 km, respectively. The results assessed by the GPS-TEC technique indicate that the performance of the NeQuick2 model is slightly better than that of the IRI-2016 model. The daily mean bias mainly ranges from −1.5 to 1.5 and −3.0 to −1.0 TECU for the regions above 500 and 800 km, respectively. The RMS values for the corresponding parts are 3.50 and 2.74 TECU. Finally, the validation results of the dSTEC method show that the mean bias is −0.43 and −0.20 TECU above 500 and 800 km, respectively. The mean RMS values are 2.04 and 0.72 TECU for the corresponding regions. Recently, low Earth orbit (LEO) satellites equipped with dual-frequency global positioning system (GPS) receivers for precise orbit determination purposes have grown in use. The topside total electron content ©2020. American Geophysical Union. All Rights Reserved.