In this paper, an improved extended state observer (ESO) based on sigmoid function and a finite-time convergence attitude controller are designed for reusable launch vehicle (RLV) in the re-entry phase. First, a control-oriented model (COM) of the RLV is established. According to the singular perturbation theory, the RLV control system is divided into an outer-loop and inner-loop subsystems. Second, a sigmoid function ESO (SESO) is proposed to estimate the model uncertainties and external disturbance caused by the large attitude maneuver and complicated external environment during the RLV re-entry phase. The continuous differentiable sigmoid function has the significant ability in noise suppression. By selecting the proper Lyapunov function, the stability of the SESO is proved. Then, based on the sliding mode control (SMC) theory, an improved multivariable super-twisting high-order sliding mode controller is designed. The finite-time convergence for the whole system is proven by the Lyapunov function technology. Finally, a 6-degree-of-freedom (6-DOF) RLV model is utilized to simulate to verify the effectiveness and robustness of the proposed control scheme. INDEX TERMSReusable launch vehicle, extended state observer, sliding mode control, super-twisting, re-entry phase.
For future lunar exploration and planetary missions, the digital elevation model (DEM) of the target object may not be well prepared before the mission, so developing a new robust crater detection algorithm (CDA) without prepared high-precision DEM is needed to meet the requirements of a high-reliability and high-precision detection and navigation system. In this paper, we presented a new robust lunar CDA method based on maximum entropy threshold segmentation. By calculating the entropy distribution of the ternary image, the threshold for retaining the maximum amount of image information is selected adaptively, a variety of evaluation indicators are proposed, and a multiple-indicator constraint matrix is constructed to realize the extraction and fitting of the craters. The proposed method has the following advantages: (1) it has strong robustness and is capable of extracting complete craters under multiple illumination conditions, which makes it suitable for the extraction of large-scale planetary and lunar images; (2) the extracted crater edges are clear and complete and do not merge with the surrounding environment edge; and (3) it avoids the problem of parameter sensitivity that is present in a traditional CDA algorithm. The proposed method was verified using an image taken by the Chang’e-2 lunar probe, and a comparison with the traditional method based on morphology and adaptive Canny edge detection shows that the number of craters detected increases by more than 35%, while the computational efficiency is improved by more than 40%.
In this paper, a novel guidance algorithm based on adaptive convex optimization is proposed to ensure robustness in the uncertainty of a lunar lander’s parameters and satisfy the constraints of terminal position, velocity, attitude, and thrust. To address the problem of parameter uncertainty in the landing process, the parameter-adaptive method is used to achieve online real-time optimal estimations of specific impulse and mass by the optimal observer, and the estimated parameters are used to realize optimal trajectory programming. To overcome the difficulty in constraining the attitude and the thrust level at the final stage in the convex optimization process, a rapid adjustment phase is added to meet the final attitude and thrust constraints; the target-adaptive method is used to adjust the target adaptively at the same time. Therefore, the position and velocity deviations caused by the rapid adjustment phase can be eliminated by the target offset. Finally, the results of numerical experiments demonstrate the effectiveness of the proposed algorithm.
To solve the problem of high-precision optical navigation for the descent landing of lunar and planetary probes, an optical navigation method based on the spatial position distribution model is proposed. The method is based on crater detection, and an imaging cosine equivalent mathematical model based on the correspondence of crater objects is constructed, The geometric distribution of the probe spatial position is described to form an Abelian Lie group spatial torus to achieve absolute positioning for parametric optical navigation, Finally, the effect of the measurement error of crater detection on the positioning and attitude of the optical navigation system is discussed, with a fitted ellipse used as a typical analysis object. The effects of different crater distribution configurations and different detection errors on the performance of the proposed optical navigation algorithm are analyzed. The results of Monte Carlo simulation experiments showed that the algorithm proposed in this paper had the advantages of high stability, high accuracy, and good real-time performance, compared with existing methods.
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