Unified numerical predictor-corrector guidance based on characteristic model

Aerocapture is one of the key technologies for low-cost transportation,with high demands of autonomy,accuracy,and robustness of guidance and control,due to its high reliability requirements for only one chance of trying.A unified numerical predictor-corrector guidance method based on characteristic models for aerocapture is proposed.The numerical predictor-corrector guidance method is used to achieve autonomy and high accuracy,and the characteristic model control method is introduced to achieve robustness.At the same time,by transforming path constraints,characteristic model equations including apogee deviation and altitude differentiation are established.Based on the characteristic model equations,a unified guidance law which can satisfy path constraints and guidance objectives simultaneously is designed.In guidance problems,guidance deviation is not directly obtained from the output of the dynamics at present,but is calculated through integral and algebraic equations.Therefore,the method of directly discretizing differential equations cannot be used to establish characteristic models,which brings great difficulty to characteristic modeling.A method for characteristic modeling of guidance problems is proposed,and convergence analysis of the proposed guidance law is also provided.Finally,a joint numerical simulation of guidance and control considering navigation deviation and various uncertainties is conducted to verify the effectiveness of the proposed method.The proposed unified method can be extended to general aerodynamic entry guidance designs,providing theoretical and methodological support for them.

Modeling and identification for soft sensor systems based on the separation of multi-dynamic and static characteristics

Data-driven soft sensor is an effective solution to provide rapid and reliable estimations for key quality variables online. The secondary variables affect the primary variable in considerably different speed, and soft sensor systems exhibit multi-dynamic characteristics. Thus, the first contribution is improving the model in the previous study with multi-time-constant. The characteristics-separation-based model will be identified in substep way,and the stochastic Newton recursive(SNR) algorithm is adopted. Considering the dual-rate characteristics of soft sensor systems, the proposed model cannot be identified directly. Thus, two auxiliary models are first proposed to offer the intersample estimations at each update period, based on which the improved algorithm(DAM-SNR) is derived. These two auxiliary models function in switching mechanism which has been illustrated in detail. This algorithm serves for the identification of the proposed model together with the SNR algorithm, and the identification procedure is then presented. Finally, the laboratorial case confirms the effectiveness of the proposed soft sensor model and the algorithms.

Analysis of Frequency Characteristics and Sensitivity of Compliant Mechanisms

Based on a modified pseudo-rigid-body model,the frequency characteristics and sensitivity of the large-deformation compliant mechanism are studied.Firstly,the pseudo-rigid-body model under the static and kinetic conditions is modified to enable the modified pseudo-rigid-body model to be more suitable for the dynamic analysis of the compliant mechanism.Subsequently,based on the modified pseudo-rigid-body model,the dynamic equations of the ordinary compliant four-bar mechanism are established using the analytical mechanics.Finally,in combination with the finite element analysis software ANSYS,the frequency characteristics and sensitivity of the compliant mechanism are analyzed by taking the compliant parallel-guiding mechanism and the compliant bistable mechanism as examples.From the simulation results,the dynamic characteristics of compliant mechanism are relatively sensitive to the structure size,section parameter,and characteristic parameter of material on mechanisms.The results could provide great theoretical significance and application values for the structural optimization of compliant mechanisms,the improvement of their dynamic properties and the expansion of their application range.

Uniformity evaluation and optimization of fluid flow characteristics in a seven-strand tundish

The effect of flow control devices（FCDs） on the uniformity of flow characteristics in a seven-strand symmetrical trapezoidal tundish was studied using both an experimental 1：2.5 hydraulic model and a numerical simulation of a 1：1 geometric model.The variation coefficient（CV） was defined to evaluate the flow uniformity of the seven-strand tundish.An optimized FCD configuration was proposed on the basis of the evaluation of experimental results.It is concluded that a turbulence inhibitor（TI） and U-type dam are essential to improve the uniformity of fluid flow in the seven-strand tundish.In addition,the configuration of inclination T-type dams with a height of 200 mm between the second and third strands and with a height of 300 mm between the third and fourth strands can minimize the proportion of dead zone.After optimizing the configuration of FCDs,the variation coefficient reduces below 20%of the mean value,and the average proportion of dead zone is just 14.6%;in addition,the temperature fluctuation between the strands could be controlled within 0.6 K.In summary,the uniformity of flow and temperature in the seven-strand tundish is greatly improved.

Trajectory tracking control of characteristic model for nonplanar hex-rotor UAV

The nonplanar hex-rotor unmanned aerial vehicle(UAV)has much higher driving property,greater payload capacity and damage tolerance than quad-rotor UAV.It is difficult to design a highperformance controller of easy engineering implementation for strongly coupled nonlinear hex-rotorUAV system.In response to this practical problem,an adaptive trajectory tracking control based oncharacteristic model for nonplanar hex-rotor is studied.Firstly,the dynamic model for the hex-rotorUAV is devised.Secondly,according to dynamic characteristics,environmental characteristics andcontrol performance requirements,the characteristic model of the hex-rotor UAV is constructed.Then,based on the characteristic model,a golden section adaptive controller is designed to realizetrajectory tracking.Furthermore,the stability analysis of the closed loop hex-rotor system is given.Finally,the validity of the proposed trajectory tracking control method adopted in the nonplanar hex-rotor UAV is demonstrated via numerical simulations and hex-rotor prototype experiments.

Sedimentary Characteristics and Models of Paleo-salt Lake During Paleocene and Eocene in the Jiangling Depression of Central China

1 Sedimentary Characteristics of Paleo-salt Lake In early sedimentary stages of Shashi formation,because of drought climate and the concentration of lake,a set of salt strata of hundreds of meters is developed in the tension

The Geochemical Characteristics and Minerogenic Model for the Amo Hypothermal Tin Deposit in Ximeng County, Yunnan Province

Through studies on the element geochemistry, alteration of country rocks, ore-forming fluids and isotopegeochemistry of the Arno tin deposit in the metamorphic rocks of the Upper Proterozoic Ximeng Group, theauthors consider that the concentration of the B-F-Li-Rb-Cs-Sn association is related to acidic magmatism inthe study area. The Fe-Mg-Li tourmaline in the ore is the replaced product of the country rocks byhypothermal fluid. The δ^(18)O values of mineral separates are +2.01- +13.16‰ and their δ^(34)S values, +2.6-+7.2‰. The ore-forming materials were derived from hydrothermal fluid of granitic magma. For themineralization, the temperature is 450°-350℃, the pressure, 450-1000×10~5 Pa, and the age, Himalayan(21.5 Ma). According to the geochemical characteristics, a minerogenic model is established: the deposit is ahypothermal cassiterite-quartz vein type tin deposit controlled by the hidden Himalayan granites.

Effect of Characteristic Spectral Lines on Rock Identification of LIBS

The LIBS （Laser induced-breakdown spectroscopy） combined with BPNN （Back propagation neural network） was applied in rock sorting and distinguishing for 26 rock samples of 6 types. According to contents of major elements in samples, we selected lines of Si, Al, Fe, K, Ca, Mg, Na, Ti and Mn. These lines of 9 elements composed three characteristic spectral models which were the WSLM （Wide spectral line model）, the PM （Peak model） and the PRM （Peak ratio model）. The first and the second characteristic spectral model were divided into 9 kinds, as follows： the characteristic spectrum with 1 element, the characteristic spectrum with 2 elements, we can deduce the rest from this and the last one has 9 elements. The third model was divided into 8 kinds which were using AI as reference element. We analysed spectrums of the three models by BPNN. Experimental results shown that whether sorting or distinguishing these samples, identification accuracies of the PM were more than that of the PRM overall, the same as the WSLM did to the PM. While the selected number of elements was 5, 6 or 7, the identification accuracy of the WSLM could reach more than 90%. Continuing to add the number of elements to improve identification accuracy was not very obvious.

Analysis of the Characteristics and Model of Online Social Network Information Dissemination

Online social network is increasingly showing a significant impact and role in many areas of social life. In the study of online social network related issues have become the consensus of the academic and industrial communities and the urgent need for. This paper mainly studies the problem of information dissemination in social network, the mode of communication, behavior, propagation paths and propagation characteristics are studied, and take the Tencent micro-blog as an example, based on the analysis of many examples, several main models and characteristics of information dissemination in social network platform.

SNCDM: Spinal Tumor Detection from MRI Images Using Optimized Super-Pixel Segmentation

Conferring to the American Association of Neurological Surgeons(AANS)survey,85%to 99%of people are affected by spinal cord tumors.The symptoms are varied depending on the tumor’s location and size.Up-to-the-min-ute,back pain is one of the essential symptoms,but it does not have a specific symptom to recognize at the earlier stage.Numerous significant research studies have been conducted to improve spine tumor recognition accuracy.Nevertheless,the traditional systems are consuming high time to extract the specific region and features.Improper identification of the tumor region affects the predictive tumor rate and causes the maximum error-classification problem.Consequently,in this work,Super-pixel analytics Numerical Characteristics Disintegration Model(SNCDM)is used to segment the tumor affected region.Estimating the super-pix-els of the affected region by this method reduces the variance between the iden-tified pixels.Further,the super-pixels are selected according to the optimized convolution network that effectively extracts the vertebral super-pixels features.Derived super-pixels improve the network learning and training process,which minimizes the maximum error classification problem also the efficiency of the system was evaluated using experimental results and analysis.

Characteristic modeling and the control of flexible structure

Appropriate modeling for a controlled plant has been a remarkable problem in the control field. A new modeling theory, i.e. characteristic modeling, is roundly demonstrated. It is deduced in detail that a general linear constant high-order system can be equivalently described with a two-order time-varying difference equation. The application of the characteristic modeling method to the control of flexible structure is also introduced. Especially, as an example, the Hubble Space Telescope is used to illustrate the application of the characteristic modeling and adaptive control method proposed in this paper.

Gray correction method of X-ray fusion image

The conventional X-ray gray weighted image fusion method based on variable energy cannot characterize the phys- ical properties of complicated objects correctly, therefore, the gray correction method of X-ray fusion image based on neural network is proposed. The conventional method acquires 12 bit images on variable energy, and then fuses the images in a tra- ditional way. While the new method takes the fusion image as the input of neural network simulation system and takes the acquired 16 bit image as the output of neural network. The X-ray image physical characteristic model based on neural net- work is obtained through training. And then it takes steel ladder block as the test object to verify the feasibility of the mod- el. In the end, the gray curve of output image is compared with the gray curve of 16 bit real image. The experiment results show that this method can fit the nonlinear relationship between the fusion image and the real image, and also can expand the scope of application of low dynamic image acquisition equipment.

A characteristic modeling method of error-free compression for nonlinear systems

The existence of error when compressing nonlinear functions into the coefficients of the characteristic model is known to be a key issue in existing characteristic modeling approaches,which is solved in this work by an error-free compression method.We first define a key concept of relevant states with corresponding compressing methods into their coefficients,where the coefficients are continuous and bounded and the compression is error-free.Then,we give the conditions for decoupling characteristic modeling for MIMO systems,and sequentially,we establish characteristic models for nonlinear systems with minimum phase and relative order two as well as the flexible spacecrafts,realizing the equivalence in the characteristic model theory.Finally,we explicitly explain the reasons for normalization in the characteristic model theory.

Computational fluid dynamic modeling of gas flow characteristics of the high-power CW CO_2 laser

To increase the photoelectronic conversion efficiency of the single discharge tube and to meet the requirements of the laser cutting system, optimization of the discharge tube structure and gas flow field is necessary. We present a computational fluid dynamic model to predict the gas flow characteristics of high-power fast-axial flow CO2 laser. A set of differential equations is used to describe the operation of the laser. Gas flow characteristics, are calculated. The effects of gas velocity and turbulence intensity on discharge stability are studied. Computational results are compared with experimental values, and a good agreement is observed. The method presented and the results obtained can make the design process more efficient.

Controller design based on viscoelasticity dynamics model and experiment for flexible drive unit

In order to ensure that the system has the advantage of light weight and vibration absorption, the steel rope is used as a flexible transmission part. A flexible drive unit(FDU) is developed, whose features are guided by steel rope, increasing force by the movable pulley group, modular, convenient and flexible. Dynamics model for controller is deduced based on the constitutive equation of viscoelasticity. Controller is designed for position control and is based on the viscoelasticity dynamics model compensation control strategy proposed. The control system is based on the TURBO PMAC multi-axis motion control card.Prototype loading experiments and velocity experiments results show that the FDU can reach 2 Hz with no load and the max speed of 30(°)/s. The FDU has the capability of the load torque 11.2 N·m and the speed of 24(°)/s simultaneously, and the frequency response is 1.3 Hz. The FDU can be used to be the pitch joint of hip for biped robot whose walking speed is 0.144 km/h theoretically.

Polarization Projection for 3D Geometry-Based Stochastic Channel Model

Comprehensive radiation characteristics of polarized antenna are crucial in creating practical channel coefficients for next generation wireless communication system designs.Being currently supported within3 D geometry-based stochastic channel models(GSCM),field patterns are technically obtained by chamber measurement(or by its best fitting).However,in some channel related performance analysis scenarios,design insight can be crystallized better by starting the derivations with theoretical co-polarization and cross-polarization components.Specifically,these two components are mathematically linked with field patterns through the proposed polarization projection algorithm.In this manuscript,we focus on revealing the transformation criterion of polarization states between the antenna plane and the propagation plane.In practice,it makes retrieving the field patterns by electromagnetic computation possible.Meanwhile,the impact imposed by distinct antenna orientations is geometrically illustrated and consequently incorporated into the proposed algorithm.This will further facilitate flexible performance evaluation of related radio transmission technologies.Our conclusions are verified by the closed-form expression of the dipole field pattern(via an analytical approach) and by chamber measurement results.Moreover,we find that its 2D degenerative case is aligned with the definitions in 3^(rd) generation partnership project(3GPP)technical report 25.996.The most obvious benefit of the proposed algorithm is to significantly reduce the cost on generating channel coefficients in GSCM simulation.

Trajectory-tracking control of an unmanned surface vehicle based on characteristic modelling approach:Implementation and field testing

In this study,a practical adaptive control scheme is proposed for the trajectory tracking of an unmanned surface vehicle via the characteristic modelling approach.Therefore,accurate tracking control can be achieved in the presence of unknown time‐varying model parameters and environmental disturbances.The control scheme comprises a trajectory guidance module based on the virtual target approach and a tracking control module designed by characteristic modelling theory.Firstly,the ideal control commands of the yaw speed and surge speed are generated using the position errors between the vehicle and the virtual target.Then,a second‐order characteristic model for the heading and surge speed channel is developed.The parameters of the model are updated by a real‐time parameter identification algorithm.Based on this model,an integrated adaptive control law is designed which consists of golden‐section control,feed‐forward control and integral control.Finally,the development processes of the vehicle platform and the control algorithms are described,and the results of simulation and field experiments are presented and discussed.

DBN-GABP model for estimation of aircraft wake vortex parameters using Lidar data

Aircraft wake turbulence is an inherent outcome of aircraft flight,presenting a substan-tial challenge to air traffic control,aviation safety and operational efficiency.Building upon data obtained from coherent Doppler Lidar detection,and combining Dynamic Bayesian Networks(DBN)with Genetic Algorithm-optimized Backpropagation Neural Networks(GA-BPNN),this paper proposes a model for the inversion of wake vortex parameters.During the wake vortex flow field simulation analysis,the wind and turbulent environment were initially superimposed onto the simulated wake velocity field.Subsequently,Lidar-detected echoes of the velocity field are simulated to obtain a data set similar to the actual situation for model training.In the case study validation,real measured data underwent preprocessing and were then input into the established model.This allowed us to construct the wake vortex characteristic parameter inversion model.The final results demonstrated that our model achieved parameter inversion with only minor errors.In a practical example,our model in this paper significantly reduced the mean square error of the inverted velocity field when compared to the traditional algorithm.This study holds significant promise for real-time monitoring of wake vortices at airports,and is proved a crucial step in developing wake vortex interval standards.

Control of a flexible rotor active magnetic bearing test rig: a characteristic model based all-coefficient adaptive control approach

Active magnetic bearings （AMBs） have found a wide range of applications in high-speed rotating machinery industry. The instability and nonlinearity of AMBs make controller designs difficult, and when AMBs are coupled with a flexible rotor, the resulting complex dynamics make the problems of stabilization and disturbance rejection, which are critical for a stable and smooth operation of the rotor AMB system, even more difficult. Proportional-integral-derivative （PID） control dominates the current AMB applications in the field. Even though PID controllers are easy to implement, there are critical performance limitations associated with them that prevent the more advanced applications of AMBs, which usually require stronger robustness and performance offered by modern control methods such as H-infinity control and if-synthesis. However, these advanced control designs rely heavily on the relatively accurate plant models and uncertainty characterizations, which are sometimes difficult to obtain. In this paper, we explore and report on the use of the characteristic model based all-coefficient adaptive control method to stabilize a flexible rotor AMB test rig. In spite of the simple structure of such a characteristic model based all-coefficient adaptive controller, both simulation and experimental results show its strong performance.