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A new control scheme for flexible air-breathing hypersonic vehicle is designed in this paper based on non-singular fast terminal sliding mode control and nonlinear disturbance observer. The proposed control scheme is derived from basic back-stepping method, which is capable of handling the higher-order nonlinear system, and a novel terminal sliding mode control method is designed for the last step to promise the finite time convergence and improve the steady-state precision. Meanwhile, a command filter is used to avoid the “explosion of complexity” in traditional back-stepping method. To overcome inevitable uncertainties as well as cross couplings between flexible and rigid modes, NDO is introduced to estimate diverse uncertainties. Thus flexible modes and uncertainties can be suppressed simultaneously. The convergence of overall closed-loop system states is proved via Lyapunov analysis. Numerical simulations show the effectiveness and advantages of the proposed control strategy.

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High-resolution and accurate Digita (DEM) generation from satellite image problem. In this work, a stereo 3 framework is outlined that is nonstereoscopic satellite image pa captured by different satellites. The o maps given by stereo reconstruction height maps given by a multiview a Probabilistic Volumetric Representat map qualities are measured in compa prepared ground-truth height maps i different parts of the world with urba rural features. The results along w weaknesses of the two techniques are su

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This paper presents a multi‐time hierarchical stochastic predictive control (MHSPC) scheme for an island microgrid, in which electric vehicles (EVs) can be used as mobile energy storages to improve power balance and realise load‐frequency control (LFC) with micro‐turbines (MTs). At the upper layer, a stochastic model predictive control is proposed to handle the EVs uncertainties on a long time scale, while optimising controllable power adjustment of MTs, the charge/discharge energy of the battery electric storage (BES) unit and guaranteeing EVs to be fully charged at the expected plug‐out time. At the lower layer, the coordination between EVs and MTs for LFC is achieved by a standard MPC framework on a short time scale. In this way, the power balance is met, and the frequency fluctuation is inhibited. Finally, simulation results are presented to illustrate the satisfactory operation of the island microgrid.

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With the development of multi-constellation multi-frequency Global Navigation Satellite Systems (GNSS), more and more observations are available for tightly coupled GNSS/Inertial Navigation System (INS) integration. Concerning the accuracy, robustness, and computational burden issues in the integration, we proposed a robust and computationally efficient implementation. The new tight integration model uses pseudorange, Doppler and carrier phase simultaneously, to achieve the maximum possible navigation accuracy for a single receiver. The resultant high-dimensional observation vector is then processed by a sequential Kalman Filter (KF) to improve the computational efficiency in the measurement update step. Based on the innovation of the sequential KF, a robust estimation method with Gaussian test is further devised to detect and adapt the faults in individual GNSS channels. Two field vehicular tests are conducted to evaluate the performance improvements of the proposed method, compared with loose coupling and conventional tight coupling. Test results in favorable environments indicate that the proposed method can significantly improve the velocity and attitude accuracy by 69.42% and 47.16% over loose coupling and by 64.75% and 30.88% over conventional tight coupling, respectively. Moreover, the computational efficiency is also improved by about 53.09% for the proposed method, compared with batch KF processing. In GNSS challenging environments, the proposed method also shows superiority in terms of velocity and attitude accuracy, and better bridging capability during the GNSS partial or complete outages. These results demonstrate that the proposed method is able to provide a more robust and accurate solution in real-time vehicular navigation.