Motion synchronization in a dual redundant HA/EHA system by using a hybrid integrated intelligent control design

This paper presents an integrated fuzzy controller design approach to synchronize a dis-similar redundant actuation system of a hydraulic actuator (HA) and an electro-hydrostatic actu-ator (EHA) with system uncertainties and disturbances. The motion synchronous control system consists of a trajectory generator, an individual position controller for each actuator, and a fuzzy force tracking controller (FFTC) for both actuators. The trajectory generator provides the desired motion dynamics and designing parameters of the trajectory which are taken according to the dynamic characteristics of the EHA. The position controller consists of a feed-forward controller and a fuzzy position tracking controller (FPTC) and acts as a decoupled controller, improving posi-tion tracking performance with the help of the feed-forward controller and the FPTC. The FFTC acts as a coupled controller and takes into account the inherent coupling effect. The simulation results show that the proposed controller not only eliminates initial force fighting by synchronizing the two actuators, but also improves disturbance rejection performance.     

Checking the permanent joint quality using the hologram interferometry method

The possibilities of applying holography for checking defects of soldering and welding in composite structural parts are considered.     

Tracking an incoming ballistic missile using an extended interval Kalman filter

The important tracking problem by radar of an incoming ballistic missile system, which contains uncertainty in modeling and noise in both dynamics and measurements, is studied. The classical extended Kalman filter (EKF) is no longer applicable to such an uncertain system, and so a new extended interval Kalman filter (EIKF) is developed for tracking the missile system. Computer simulation is presented to show the effectiveness of the EIKF algorithm for this uncertain and nonlinear ballistic missile tracking problem.     

State estimation using an approximate reduced statistics algorithm

The problem of state estimation using nonlinear additive Gaussian noise measurements is addressed. A geometric model for the posterior state density is assumed based on a multidimensional Haar basis representation. An approximate reduced statistics (ARS) algorithm, suggested by the parameter estimator of Kulhavy is then developed, using successive minimization of relative entropy between model densities and an approximate posterior density. The state estimator thus derived is applied to a bearings-only target tracking problem in a multiple sensor scenario     

Mini-UAV altitude estimation using an inertially stabilized payload

A novel method is introduced for autonomous attitude estimation of a mini unmanned aerial vehicle (UAV) carrying an inertially stabilized payload. The method is based on utilizing the outputs of rate gyros normally used to inertially stabilize the payload, and other data that is normally available from conventional aircraft-mounted sensors. A decentralized estimation algorithm is developed, which uses the aircraft/payload mathematical models to bound the estimation errors. Exploiting modern multiprocessor computer technology, the new estimation algorithm comprises two parallel extended Kalman filters (EKFs) and a data fusion algorithm. Real-time experimental tests, incorporating a payload model with real rate gyros mounted on a three-axis flight table, have validated the feasibility of the concept. The theoretical and experimental investigation demonstrates that the estimation algorithm is capable of estimating the attitude angles with an estimation error not exceeding 1 deg, at output rates of 13 Hz, thus constituting a viable substitute for the conventional vertical gyroscope     

Two-phase forward converter using an integrated magnetic component

An interleaved two-phase forward converter using an integrated magnetic component is proposed for telecommunication and computer applications. The integrated magnetic component consists of two step-down transformers and two output-filtering inductors on a single magnetic core. The z-parameter (gyrator) model and the equivalent-circuit model of the integrated magnetic component are presented. The circuit operation and design criteria of the proposed converter are described. All theoretical analyses are verified by simulated and experimental results.     

ISAR imaging using an emulated multistatic radar system

The use of a monostatic radar configuration limits the ability of an inverse synthetic aperture radar (ISAR) system to image targets in certain geometries. By employing multistatic geometries this limitation may be overcome. This paper discusses the emulation of multistatic geometries, via sea surface multipath reflections, using a monostatic system. This application capitalises on the advantages provided by both monostatic and bistatic systems. The possibility of obtaining ISAR images using these emulated multistatic radar configurations is first theoretically discussed and then verified using experimental results.     

Adaptive field-oriented control of an IM using predictive control

A novel adaptive control algorithm for the field-oriented control of a CSI-fed induction machine is presented. It includes an adaptive flux model for determining the position and magnitude of the rotor field vector, which avoids the need to obtain the orientation and magnitude of the flux for purposes of feedback. This online estimation of field vector requires the measurements of stator voltage and rotor speed. The algorithm has been tested by simulating the machine using a digital computer. The controller perform well, and the machine parameters are estimated with reasonable accuracy. The controller has a self-adjusting mechanism and adjusts itself to any variation of machine parameters during operation. It can be applied to any machine and requires no tuning. The scheme is being tested on a machine inverter setup controlled by a microcomputer     

Pursuer identification and time-to-go estimation using passive measurements from an evader

We present an algorithm for identifying the parameters of a proportional navigation guidance missile (pursuer) pursuing an airborne target (evader) using angle-only measurements from the latter. This is done for the purpose of classifying the missile so that appropriate counter-measures can be taken. Mathematical models are constructed for a pursuer with a changing velocity, i.e., a direction change and a speed change. Assuming the pursuer is launched from the ground with fixed thrust, its motion can be described by a four-dimensional parameter vector consisting of its proportional navigation constant and three parameters related to thrusting. Consequently, the problem can be solved as a parameter estimation problem, rather than state estimation and we provide an estimator based on maximum likelihood (ML) to solve it. The parameter estimates obtained can be mapped into the time-to-go until intercept estimation results are presented for different scenarios together with the Cramer-Rao lower bound (CRLB), which quantifies the best achievable estimation accuracy. The accuracy of the time-to-go estimate is also obtained. Simulation results demonstrate that the proposed estimator is efficient by meeting the CRLB.     

Angle of arrival estimation of coherent signals using an arraydoublet in motion

Shown here is how the estimation of signal parameters via relational invariance techniques (ESPRIT) algorithm may be used with a single pair of antennas in motion to estimate angles of arrival (AOA) for coherent signals. The approach exploits the Doppler frequency shifts caused by the doubler in motion. With this estimator, the number of signals that can be handled is not limited by the size of the array, as in the usual ESPRIT application, but by an adjustable parameter. A theoretical performance analysis of the estimator and typical examples showing the use of this estimator are given     

Flow visualization study of an airship model using a water towing tank

The work presented investigates the aerodynamic drag and flow physics of an airship configuration. The investigation is carried out experimentally in a water towing tank. The purpose of this project is to improve the understanding of the aerodynamic characteristics of an airship through quantitative and qualitative approaches. Qualitative measurements of integral drag force and moment are measured in the presence of a crosswind. Flow visualization using colored and fluorescent dyes has been applied to improve knowledge of the aerodynamics of airship configurations with an emphasis on the boundary layer separation, transition and hull–appendage interference effects.     

孔壁通透率对平面附壁射流的影响

本文研究了不同壁面通透率对平面附壁射流动态特性的影响。实验结果表明孔壁减弱、甚至消除了流场中的低频摆动现象。随着孔壁通透率的增加,射流时均附壁点向下游逐渐移动,射流和壁面之间的回流区长度逐渐增大,而射流内侧剪切层内的涡旋与壁面之间的相互作用减小,壁面压强脉动强度变小,附壁射流的动态特性逐渐向自由射流转化。当孔壁通透率为40％左右时,射流与二维平面自由射流类似。距离射流出口不同位置上的壁面脉动压强之间的互谱表明,当孔壁通透率增大以后,射流内侧剪切层中的旋涡向下游传播距离变得更长,传播速度加快,这说明低孔壁通透率情况下的附壁射流中存在的低频摆动现象阻碍了剪切层高频旋涡向下游的发展。     

Improving GPS-Based Landing System Performance using an Empirical Barometric Altimeter Confidence Bound

This paper develops an empirical confidence bound for barometric altimeter altitude errors and shows how this bound may improve the performance of GPS-based approach and landing systems. This empirical bound is developed using historical meteorological data collected at a set of geographically diverse locations over a thirty year period. The confidence bound developed is shown to provide a Gaussian overbound on altimeter altitude errors in standard atmospheric conditions between a 10-5 and 10-6 confidence level. This confidence bound is integrated into the standard methodology for analyzing the performance of GPS-based landing systems and the results of a performance trade study using the confidence bound are presented. The results show that incorporating the empirical barometric altimeter confidence bound provides an increase in the coterminous United States (CONUS) service volume for lateral precision with vertical guidance (LPV) type approaches. While this increase is approximately 2% for an L1 single-frequency GPS user, it jumps to roughly 40% for an L5 single-frequency user.     

A method for constructing an airfoil using a specified chord velocity diagram

A problem of determining a shape of the airfoil being streamlined by a potential incompressible inviscid flow is solved by the successive approximation method using a specified chord velocity diagram. It is shown that a closed airfoil that possesses a specified chord velocity diagram can be constructed with a sufficient accuracy; if the chord diagram is unsuccessfully specified, the closed airfoil may prove to be not univalent, that is, physically unrealizable.     

Multi-mode diagnosis of a gas turbine engine using an adaptive neuro-fuzzy system

Gas Turbine Engines (GTEs) are vastly used for generation of mechanical power in a wide range of applications from airplane propulsion systems to stationary power plants. The gas-path components of a GTE are exposed to harsh operating and ambient conditions, leading to several degradation mechanisms. Because GTE components are mostly inaccessible for direct measurements and their degradation levels must be inferred from the measurements of accessible parameters, it is a challenge to acquire reliable information on the degradation conditions of the parts in different fault modes. In this work, a data-driven fault detection and degradation estimation scheme is developed for GTE diagnostics based on an Adaptive Neuro-Fuzzy Inference System (ANFIS). To verify the performance and accuracy of the developed diagnostic framework on GTE data, an ensemble of measurable gas path parameters has been generated by a high-fidelity GTE model under (a) diverse ambient conditions and control settings, (b) every possible combination of degradation symptoms, and (c) a broad range of signal to noise ratios. The results prove the competency of the developed framework in fault diagnostics and reveal the sensitivity of diagnostic results to measurement noise for different degradation symptoms.     

Smuggling interdiction using an adaptation of the AN/APG-76multimode radar

The AN/APG-76 multimode radar was designed and developed for a multimode attack fighter application requiring rapid search, detection, identification, and precision location of both airborne and surface targets from long standoff ranges under adverse weather conditions. Unique is the radar's ability to generate SAR images of a selected area while simultaneously detecting and tracking all-speed moving objects located within that imaged region. Northrop Grumman Norden Systems has recently upgraded and adapted this radar to smuggling interdiction and related law enforcement missions. These adaptations have added an integrated GPS/INS subsystem for enhanced self-navigation and target location accuracy, a long range wide-band digital data link and ground station for mission control and data dissemination, a 3-D interferometric SAR imaging capability for detailed high resolution topographic mapping, and 1 meter and 0.3 meter resolution SAR modes for positive target identification. Additionally, the radar has been installed into wing-mounted pods and adapted for side-looking and 360 degree coverage applications. Automatic target detection and enhanced-range sea-surveillance and air-targeting modes are also now available through the use of open architecture commercial processors and non-proprietary transportable programming languages     

Online condition diagnosis for a two-stage gearbox machinery of an aerospace utilization system using an ensemble multi-fault features indexing approach

China manned space station is designed to operate for over ten years. Long-term and sustainable research on space science and technology will be conducted during its operation. The application payloads must meet the ‘‘long life and high reliability" mission requirement. Gearbox machinery is one of the essential devices in an aerospace utilization system, failure of which may lead to downtime loss even during some disastrous catastrophes. A fault diagnosis of gearbox has attracted attentions for its significance in preventing catastrophic accidents and guaranteeing sufficient maintenance. A novel fault diagnosis method based on the Ensemble Multi-Fault Features Indexing(EMFFI) approach is proposed for the condition monitoring of gearboxes. Different from traditional methods of signal analysis in the one-dimensional space, this study employs a supervised learning method to determine the faults of a gearbox in a two-dimensional space using the classification model established by training the features extracted automatically from diagnostic vibration signals captured. The proposed method mainly includes the following steps. First, the vibration signals are transformed into a bi-spectrum contour map utilizing bi-spectrum technology,which provides a basis for the following image-based feature extraction. Then, Speeded-Up Robustness Feature(SURF) is applied to automatically extract the image feature points of the bi-spectrum contour map using a multi-fault features indexing theory, and the feature dimension is reduced by Linear Discriminant Analysis(LDA). Finally, Random Forest(RF) is introduced to identify the fault types of the gearbox. The test results verify that the proposed method based on the multi-fault features indexing approach achieves the target of high diagnostic accuracy and can serve as a highly effective technique to discover faults in a gearbox machinery such as a two-stage one.     

Multi-UAV reconnaissance task allocation for heterogeneous targets using an opposition-based genetic algorithm with double-chromosome encoding

This paper presents a novel multiple Unmanned Aerial Vehicles (UAVs) reconnaissance task allocation model for heterogeneous targets and an effective genetic algorithm to optimize UAVs’ task sequence. Heterogeneous targets are classified into point targets, line targets and area targets according to features of target geometry and sensor’s field of view. Each UAV is regarded as a Dubins vehicle to consider the kinematic constraints. And the objective of task allocation is to minimize the task execution time and UAVs’ total consumptions. Then, multi-UAV reconnaissance task allocation is formulated as an extended Multiple Dubins Travelling Salesmen Problem (MDTSP), where visit paths to the heterogeneous targets must meet specific constraints due to the targets’ feature. As a complex combinatorial optimization problem, the dimensions of MDTSP are further increased due to the heterogeneity of targets. To efficiently solve this computationally expensive problem, the Opposition-based Genetic Algorithm using Double-chromosomes Encoding and Multiple Mutation Operators (OGA-DEMMO) is developed to improve the population variety for enhancing the global exploration capability. The simulation results demonstrate that OGA-DEMMO outperforms the ordinary genetic algorithm, ant colony optimization and random search in terms of optimality of the allocation results, especially for large scale reconnaissance task allocation problems.     

Quantile-based optimization under uncertainties for complex engineering structures using an active learning basis-adaptive PC-Kriging model

The Reliability-Based Design Optimization(RBDO) of complex engineering structures considering uncertainties has problems of being high-dimensional, highly nonlinear, and timeconsuming, which requires a significant amount of sampling simulation computation. In this paper,a basis-adaptive Polynomial Chaos(PC)-Kriging surrogate model is proposed, in order to relieve the computational burden and enhance the predictive accuracy of a metamodel. The active learning basis-adaptive PC-Kriging model is combined with a quantile-based RBDO framework. Finally,five engineering cases have been implemented, including a benchmark RBDO problem, three high-dimensional explicit problems, and a high-dimensional implicit problem. Compared with Support Vector Regression(SVR), Kriging, and polynomial chaos expansion models, results show that the proposed basis-adaptive PC-Kriging model is more accurate and efficient for RBDO problems of complex engineering structures.     

Wake vortex safety assessment during cruise using a regional medium-short-range turbofan aircraft as an example

Regional turbofan aircraft, which are used for medium-short distances, have a heightened risk of high-altitude Wake Vortices(VV) because of their tail-mounted engines and high horizontal tail configurations. For some regional medium-short-range turbofan aircraft, this threat is higher than that for conventionally designed aircraft. To analyze the flight safety of turbofan aircraft during cruise, this study developed a model to assess wake vortex encounters based on evolutionary high-altitude wake flow patterns. First, the high-altitude wake vortex aircraft dissipation patterns were analyzed by combining Quick Access Recorder(QAR) flight data with the wake vortex evolution model. Then, to consider the uniqueness of the medium-short-range turbofan aircraft,the severity of the wake vortex encounters was simulated using an induced roll moment coefficient.The proposed high-altitude wake vortex encounter model was able to identify and assess the highaltitude wake vortex changes, the bearing moments at different altitudes, and the atmospheric pressure conditions. Using the latest wake separation standards from the International Civil Aviation Organization(ICAO), acceptable safety wake intervals for follower aircraft in different scenarios were determined for the safety assessment. The results indicate that compared to mid and low altitudes, the high-altitude aircraft wake vortex dissipation rate is faster, the ultimate bearing moment is weaker, and the roll moment coefficient is higher, which confirm that there is elevated wake vortex encounter severity for regional turbofan aircraft. As safety is found to deteriorate when encountering wake vortices at altitudes higher than 8 km, new medium-short-range turbofan regional aircraft require higher safety margins than the latest wake separation standards.