Predictive fault-tolerant control of an all-thruster satellite in 6-DOF motion via neural network model updating

The problem of controlling an all-thruster spacecraft in the coupled translational-rotational motion in presence of actuators fault and/or failure is investigated in this paper. The nonlinear model predictive control approach is used because of its ability to predict the future behavior of the system. The fault/failure of the thrusters changes the mapping between the commanded forces to the thrusters and actual force/torque generated by the thruster system. Thus, the basic six degree-of-freedom kinetic equations are separated from this mapping and a set of neural networks are trained off-line to learn the kinetic equations. Then, two neural networks are attached to these trained networks in order to learn the thruster commands to force/torque mappings on-line. Different off-nominal conditions are modeled so that neural networks can detect any failure and fault, including scale factor and misalignment of thrusters. A simple model of the spacecraft relative motion is used in MPC to decrease the computational burden. However, a precise model by the means of orbit propagation including different types of perturbation is utilized to evaluate the usefulness of the proposed approach in actual conditions. The numerical simulation shows that this method can successfully control the all-thruster spacecraft with ON-OFF thrusters in different combinations of thruster fault and/or failure.     

Distributed intelligent self-organized mission planning of multi-UAV for dynamic targets cooperative search-attack

This article studies the cooperative search-attack mission problem with dynamic targets and threats, and presents a Distributed Intelligent Self-Organized Mission Planning (DISOMP) algorithm for multiple Unmanned Aerial Vehicles (multi-UAV). The DISOMP algorithm can be divided into four modules: a search module designed based on the distributed Ant Colony Optimization (ACO) algorithm, an attack module designed based on the Parallel Approach (PA) scheme, a threat avoidance module designed based on the Dubins Curve (DC) and a communication module designed for information exchange among the multi-UAV system and the dynamic environment. A series of simulations of multi-UAV searching and attacking the moving targets are carried out, in which the search-attack mission completeness, execution efficiency and system suitability of the DISOMP algorithm are analyzed. The simulation results exhibit that the DISOMP algorithm based on online distributed down-top strategy is characterized by good flexibility, scalability and adaptability, in the dynamic targets searching and attacking problem.     

Direction finding for two-dimensional incoherently distributed sources with Hadamard shift invariance in non-uniform orthogonal arrays

This paper proposes a novel algorithm for Two-Dimensional (2D) central Direction-of-Arrival (DOA) estimation of incoherently distributed sources. In particular, an orthogonal array structure consisting of two Non-uniform Linear Arrays (NLAs) is considered. Based on first-order Taylor series approximation, the Generalized Array Manifold (GAM) model can first be established to separate the central DOAs from the original array manifold. Then, the Hadamard rotational invariance relationships inside the GAMs of two NLAs are identified. With the aid of such relationships, the central elevation and azimuth DOAs can be estimated through a search-free polynomial rooting method. Additionally, a simple parameter pairing of the estimated 2D angular parameters is also accomplished via the Hadamard rotational invariance relationship inside the GAM of the whole array. A secondary but important result is a derivation of closed-form expressions of the Cramer-Rao lower bound. The simulation results show that the proposed algorithm can achieve a remarkably higher precision at less complexity increment compared with the existing low-complexity methods, which benefits from the larger array aperture of the NLAs. Moreover, it requires no priori information about the angular distributed function.     

GNSS观测数据ZTD建模的质量控制方法

针对目前基于GNSS观测数据的对流层天顶总延迟(ZTD)模型缺乏有效质量控制手段的现状,提出了一套综合考虑数据量、网格分辨率以及模型稳定性的ZTD建模质量控制方法,并采用内华达大地测量实验室(NGL)解算的高空间分辨率GNSS对流层数据,选取了近十年德国及周边区域[47°N-55°N,5°E-15°E]183个测站的实测ZTD,对该方法进行了校验。实验结果表明:在该质量控制方法下建立的新模型精度稳定,平均均方根误差(RMS)为3.4 cm,相对于UNB3m、EGNOS、GPT2w+Saas平均改善了42.4%、35.8%、33.3%。本文提出的质量控制方法有效提升了基于GNSS观测数据的ZTD模型的性能,对于ZTD建模研究具有一定的参考价值。     

L-band nighttime scintillations at the northern edge of the EIA along 95°E during the ascending half of the solar cycle 24

The characteristics of nighttime ionospheric scintillations measured at the L-band frequency of 1.575 GHz over Dibrugarh (27.5°N, 95°E, MLAT ～ 17°N, 43° dip) during the ascending half of the solar cycle 24 from 2010 to 2014 have been investigated and the results are presented in this paper. The measurement location is within or outside the zone of influence of the equatorial ionization anomaly depending on solar and geomagnetic activity. Maximum scintillation is observed in the equinoxes irrespective of solar activity with clear asymmetry between March and September. The occurrence frequency in the solstices shifts from minimum in the June solstice in low solar activity to a minimum in the December solstice in high solar activity years. A significant positive correlation of occurrence of scintillations in the June solstice with solar activity has been observed. However, earlier reports from the Indian zone (～75°E) indicate negative or no correlation of scintillation in June solstice with solar activity. Scintillations activity/occurrence in solstices indicates a clear positive correlation with Es recorded simultaneously by a collocated Ionosonde. In equinoxes, maximum scintillations occur in the pre-midnight hours while in solstices the occurrence frequency peaks just after sunset. The incidence of strong scintillations (S₄ ≥ 0.4) increases with increase in solar activity. Strong (S₄ ≥ 0.4) ionospheric scintillations accompanied by TEC depletions in the pre-midnight period is attributed to equatorial irregularities whereas the dusk period scintillations are related to the sporadic-E activity. Present results thus indicate that the current location at the northern edge of the EIA behaves as low as well as mid-latitude location.     

Analytical Calculation Model for Mach Wave Parameters

When a wave shaper is embedded in a liner,Mach wave will emerge above the liner,which affects the head shape of an explosively formed projectile.Mach wave parameters,including radius and pressure need to be determined to effectively match Mach wave with the liner,so that a good head shape can be obtained.An analytical calculation model for Mach wave parameter is presented based on three-shock theory,and the theoretical values agree well with the experimental ones.The analysis shows that when the radius of the wave shaper is constant,the radius of the Mach wave increases,whereas the pressure decreases while increasing the distance between the liner and the wave shaper.When the distance between the liner and the wave shaper is constant,the radius of the Mach wave increases,whereas the pressure decreases when decreasing the radius of the wave shaper.     

Spatial transformation of general sampling-aliasing frequency region for rotating-blade parameter identification with emphasis on single-probe blade tip-timing measurement

Blade-health monitoring is intensely required for turbomachinery because of the high failure risk of rotating blades. Blade-Tip Timing (BTT) is considered as the most promising technique for operational blade-vibration monitoring, which obtains the parameters that characterize the blade condition from recorded signals. However, its application is hindered by severe undersampling and stringent probe layouts. An inappropriate probe layout can make most of the existing methods invalid or inaccurate. Additionally, a general conflict arises between the allowed and required layouts because of arrangement restrictions. For the sake of economy and safety, parameter identification based on fewer probes has been preferred by users. In this work, a spatial-transformation-based method for parameter identification is proposed based on a single-probe BTT measurement. To present the general Sampling-Aliasing Frequency (SAFE) map definition, the traditional time–frequency analysis methods are extended to a time-sampling frequency. Then, a SAFE map is projected onto a parameter space using spatial transformation to extract the slope and intercept parameters, which can be physically interpreted as an engine order and a natural frequency using coordinate transformation. Finally, the effectiveness and robustness of the proposed method are verified by simulations and experiments under uniformly and nonuniformly variable speed conditions.     

Passive localization by a single moving observer using TOA only with unknown SRI: Observability analysis and algorithm

Passive localization by a single moving observer using Time of Arrival (TOA) only with an unknown Signal Repetition Interval (SRI) is investigated in this paper. Observability analysis is performed first. The observability condition for uniquely determining the emitter position and SRI is derived. The conditional Cramer-Rao Lower Bound (CRLB) is also analyzed. It is found that the ambiguity of the SRI integer of the first TOA does not affect the theoretical estimation precision of the emitter position and SRI. A Reference-Fixed Differential TOA (RFDTOA)-based Iterative Maximum Likelihood Estimator (IMLE) is proposed, which only needs O(M) computational operations. Theoretical analysis and simulation results show that the Mean Square Error (MSE) of the proposed algorithm could attain the CRLB with moderate Gaussian measurement noise.     

Collaborative image compression and classification with multi-task learning for visual Internet of Things

Widespread deployment of the Internet of Things(Io T) has changed the way that network services are developed, deployed, and operated. Most onboard advanced Io T devices are equipped with visual sensors that form the so-called visual Io T. Typically, the sender would compress images, and then through the communication network, the receiver would decode images, and then analyze the images for applications. However, image compression and semantic inference are generally conducted separately, and t...     

SAR performance-based fault diagnosis for electro-hydraulic control system: A novel FDI framework for closed-loop system

Model-based fault diagnosis serves as an efficient and powerful technique in addressing fault detection and isolation (FDI) issues for control systems. However, the standard methods and their modifications still encounter some difficulties in algorithm design and application for complex higher-order systems. To avoid these difficulties, a novel fault diagnosis framework based on multiple performance indicators of closed-loop control system is proposed. Under this framework, a so-called performance residual vector is constructed to measure the differences between the real system and the nominal model in terms of system stability, accuracy, and rapidity (SAR) respectively. The criteria for quantification, normalization of the SAR residuals and the explicit mappings between the thresholds and the required performance are given. FDI can be easily achieved simultaneously by monitoring the normalized residual vector length and direction in the SAR performance residual space. A case study on electro-hydraulic servo control system of turbofan engine is adopted to demonstrate the effectiveness of the proposed method.