Integral Event-Triggered Attack-Resilient Control of Aircraft-on-Ground Synergistic Turning System With Uncertain Tire Cornering Stiffness

This article proposes an integral-based event-triggered attack-resilient control method for the aircraft-on-ground(AoG) synergistic turning system with uncertain tire cornering stiffness under stochastic deception attacks. First, a novel AoG synergistic turning model is established with synergistic reverse steering of the front and main wheels to decrease the steering angle of the AoG fuselage, thus reducing the steady-state error when it follows a path with some large curvature. Considering that the tire cornering stiffness of the front and main wheels vary during steering, a dynamical observer is designed to adaptively identify them and estimate the system state at the same time.Then, an integral-based event-triggered mechanism(I-ETM) is synthesized to reduce the transmission frequency at the observerto-controller end, where stochastic deception attacks may occur at any time with a stochastic probability. Moreover, an attackresilient controller is designed to guarantee that the closed-loop system is robust L2-stable under stochastic attacks and external disturbances. A co-design method is provided to get feasible solutions for the observer, controller, and I-ETM simultaneously. An optimization program is further presented to make a tradeoff between the robustness of the control scheme and the saving of communication resources. Finally, the low-and high-probability stochastic deception attacks are considered in the simulations. The results have illustrated that the AoG synergistic turning system with the proposed control method follows a path with some large curvature well under stochastic deception attacks. Furthermore,compared with the static event-triggered mechanisms, the proposed I-ETM has demonstrated its superiority in saving communication resources.

Case Retrieval Strategy of Turning Process Based on Grey Relational Analysis

To solve the problem of long response time when users obtain suitable cutting parameters through the Internet based platform,a case-based reasoning framework is proposed.Specifically,a Hamming distance and Euclidean distance combined method is designed to measure the similarity of case features which have both numeric and category properties.In addition,AHP(Analytic Hierarchy Process)and entropy weight method are integrated to provide features weight,where both user preferences and comprehensive impact of the index have been concerned.Grey relation analysis is used to obtain the similarity of a new problem and alternative cases.Finally,a platform is also developed on Visual Studio 2015,and a case study is demonstrated to verify the practicality and efficiency of the proposed method.This method can obtain cutting parameters which is suitable without iterative calculation.Compared with the traditional PSO(Particle swarm optimization algorithm)and GA(Genetic algorithm),it can obtain faster response speed.This method can provide ideas for selecting processing parameters in industrial production.While guaranteeing the characteristic information is similar,this approach can select processing parameters which is the most appropriate for the production process and a lot of time can be saved.

Analysis on the turning point of dynamic in-plane compressive strength for a plain weave composite

Experimental investigations on dynamic in-plane compressive behavior of a plain weave composite were performed using the split Hopkinson pressure bar. A quantitative criterion for calculating the constant strain rate of composites was established. Then the upper limit of strain rate, restricted by stress equilibrium and constant loading rate, was rationally estimated and confirmed by tests. Within the achievable range of 0.001/s-895/s, it was found that the strength increased first and subsequently decreased as the strain rate increased. This feature was also reflected by the turning point(579/s) of the bilinear model for strength prediction. The transition in failure mechanism, from local opening damage to completely splitting destruction, was mainly responsible for such strain rate effects. And three major failure modes were summarized under microscopic observations: fiber fracture, inter-fiber fracture, and interface delamination. Finally, by introducing a nonlinear damage variable, a simplified ZWT model was developed to characterize the dynamic mechanical response. Excellent agreement was shown between the experimental and simulated results.

High-sensitive state perception method for inverter-fed machine turn insulation based on FrFT-Mel

Amidst the swift advancement of new power systems and electric vehicles,inverter-fed machines have progressively materialized as a pivotal apparatus for efficient energy conversion.Stator winding turn insulation failure is the root cause of inverter-fed machine breakdown.The online monitoring of turn insulation health can detect potential safety risks promptly,but faces the challenge of weak characteristics of turn insulation degradation.This study proposes an innovative method to evaluate the turn insulation state of inverter-fed machines by utilizing the fractional Fourier transform with a Mel filter(FrFT-Mel).First,the sensitivity of the high-frequency(HF)switching oscillation current to variations in turn insulation was analyzed within the fractional domain.Subsequently,an improved Mel filter is introduced,and its structure and parameters are specifically designed based on the features intrinsic to the common-mode impedance resonance point of the electrical machine.Finally,an evaluation index was proposed for the turn insulation state of inverter-fed machines.Experimental results on a 3kW permanent magnet synchronous machine(PMSM)demonstrate that the proposed FrFT-Mel method significantly enhances the sensitivity of turn insulation state perception by approximately five times,compared to the traditional Fourier transform method.

Analysis and Prediction of Effect of Turning Marks Diffraction on Image Quality of Optical System

Single-point diamond turning (SPDT) is widely used in the machining of infrared materials and metal-based mirrors. Diamond tips can scratch material, replicate the shape of the tip, and create annular turning marks on optical surfaces, which can have unpredictable adverse effects on imaging. In order to predict the effect of turning marks diffraction on the degradation of imaging quality, a model of the influence of SPDT processing parameters on the reduction of system imaging MTF under the influence of ideal grating turning marks diffraction was established. The results show that the depth of the turning mark will lead to the decline of MTF, especially the low frequency information. Finally, a method is proposed to reduce the effect of turning marks diffraction through changing the processing parameters. .

DER SPATIAL TURN IN DEN KLASSISCHEN ALTERTUMSWISSENSCHAFTEN(UND SPEZIELL IN DER EPIGRAPHIK)

Since the 1990s the so-called spatial turn has brought back space and topography into the discussion within historical studies,particular ancient studies.This survey reviews current trends and developments within the field and offers some perspectives on possible future developments related to space,material,objects,their agency,and frames.

Algorithm Research and Realization of the Turning Control System for Heavy Transportation Vehicle

The dynamics of turning system which is a nonlinear system normally has great impact on the transportation speed of the vehicle having heavy load and large size.The dynamics of turning system depends on control algorithm and its implementation,but the existing control algorithms which having high dynamics in the application of heavy transportation vehicle are complex for realization and high hardware requirement.So,the nonlinear turning system is analyzed for improving its dynamics by researching new efficient control algorithm.The models of electromagnetic valve,hydraulic cylinder and turning mechanical part are built individually to get the open-loop model of the turning system following characteristics analyzed.According to the model,a new control algorithm for heavy transportation vehicle which combined PID with Bang-Bang control is presented.Then the close-loop model of turning system is obtained under Matlab/Simulink environment.By comparing the step response of different control algorithms in the same conditions,the new algorithm＇s validity is verified.On the basis of the analysis results,the algorithm is adopted to implement the turning control system by using CAN field bus and PLC controllers.Furthermore,the turning control system has been applied in one type of heavy transportation vehicle.It reduces the response time of turning system from seconds level to 250 ms,and the speed of heavy transportation vehicle increases from 5 km/h to 30 km/h.The application result shows that the algorithm and turning control system have met all the turning requirements.This new type of turning control algorithm proposed is simple in implementation for fast response of nonlinear and large-scale turning system of heavy transportation vehicle.

Active Vibration Isolation System for Sub microultra precision Turning Machine

Now vibration isolation of ultra precision machine tool is usually achieved through air springs systems. As far as HCM I sub micro turning machine developed by HIT, an active vibration isolation system that consists of air springs and electro magnetic actuators was presented. The primary function of air springs is to support the turning machine and to isolate the high frequency vibration. The electro magnetic actuators controlled by fuzzy neural networks isolate the low frequency vibration. The experiment indicates that active vibration isolation system isolates base vibration effectively in all the frequency range. So the vibration of the machine bed is controlled under 10 -6 g and the surface roughness is improved.

Development and Testing of an Automatic Turning Movement Identification System at Signalized Intersections

Vehicle turning movement data from signalized intersections is utilized for numerous applications in the field of transportation. Such applications include real-time adaptive signal control, dynamic traffic assignment, and traffic demand estimation. However, it is very time consuming and costly to obtain vehicle turning movement information manually. Previous efforts to simplify this process were focused on solving the problem using an O-D matrix, but this method proved to be inaccurate and unreliable with the existing data acquisition system. Another study involved the identification of vehicle turning movements from the detector information, but the presence of shared lanes led to uncertainties in vehicle matching, thus limiting application of the method only to intersections without shared lanes. In light of those unsuccessful attempts, this paper develops and tests a system called the Automatic Turning Movement Identification System (ATMIS), which estimates vehicle turning movements at a signalized intersection in real time, regardless of its geometry. The results from lab experiments as well as a field test show that the algorithm is very promising and may potentially be expanded for field applications.

EXTENDED SYSTEMS FOR MULTIPLE S-BREAKING TURNING POINTS IN Z_2×Z_2-SYMMETRIC NONLINEAR PROBLEMS

Making use of the Z2×Z2 symmetry,we could study the structure near multiple S-treaking turning points.In particular,we show that there exist two kinds of singular point path through double S breaking turning points and triple S bieaking turning points,one ts quadratic turning pornt path and one is quadratic pitch fork bifurcation point path.Some simple regular extended systems to corn pute double and triple S-breaking turning points are proposed.Numerical examples are also

Program Design of Graphic Realism Displaying System Based on DXF Lathe Turning Rotational Parts

For virtually realizing the graphic realism display of DXF machine parts, in AutoCAD2007 graphic drawing environment, an interactive experimental method was taken to realize the display of graphic in DXF, which was taken as the data-exchanged interface and source. Based on depth analysis of DXF data structure, take one drawing of DXF lathe turning rotational part asthe test piece. By VC＋＋6.0 programming, part＇s geometry information could be obtained. Through data processing, 3D data of the test piece could be generated, which is based on 2D data of DXF test piece. Then, OpenGL graphic processing technologies （light, material, texture, map, et al.） were applied on the 3D display of test piece from DXF files or program modules. Finally based on the test report, results of the system functions were shared to prove the realization of system design, and the feasibility of algorithms used. In the developed software, Machine Designers could get a full view of machine parts, and do some proper modifications. The study content and results of our work have some theory and practical significance on the application of program design in the practical projects.

An Expert System for the Prediction of Surface Finish in Turning Process

Prediction of surface finish in turning process is a difficult but important task. Artificial Neural Networks (ANN) can reliably pred ict the surface finish but require a lot of training data. To overcome this prob lem, an expert system approach is proposed, wherein it will be possible to predi ct the surface finish from limited experiments. The expert system contains a kno wledge base prepared from machining data handbooks and number of experiments con ducted by turning steel rods, over a wide range of cutting parameters. With this knowledge base, the expert system predicts surface finish for different tool-w ork-piece combinations, by carrying out few experiments for each case. The prop osed expert system model is validated by carrying out a number of experiments.

A Fast Tool Servo System for Fabrication of Micro-structured Surfaces on A Diamond Turning Machine

A fast tool servo (FTS) system is developed for the fabrication of non-rotationally symmetric micro-structured surfaces using single-point diamond turning machines.The constructed FTS employs a piezoelectric tube actuator (PZT) to actuate the diamond tool and a capacitive probe as the feedback sensor.To compensate the inherent nonlinear hysteresis behavior of the piezoelectric actuator,Proportional Integral (PI) feedback control is implemented.Besides,a feed-forward control based on a simple feed-forward predictor has been added to achieve better tracking performance.Experimental results indicate that error motions in the performance of the system caused by hysteresis can be reduced greatly and the micro-structured surface is successfully fabricated by implementing the FTS.

On the Singular Perturbation of Nonlinear Systems with Turning Points

In this paper we consider the asymptotic behavior of boundary value problems of nonliner systems εy″= F(t,y,y′,ε) , -1<t<1, y(-1,ε)=A, y(1,ε)=B when F possesses a generalized turning point at t=0. The interior layer phenomenon of the problem is discussed.

Regular-Singular Crossings on Nonlinear Systems with Turning Point

We consider in this paper the boundary value problems of nonlinear systems the form εY″=F(t,Y,Y′,ε), -1<t<1, Y(-1,ε)=A(ε), Y(1,ε)=B(ε). Supoosing some or all of the components of F , that is, f i satisfy 2 f y′ 2 i t =0 =0, we say that F possesses a generalized turning point at t =0. Our goal is to give sufficient conditions for the existence of solution of the problems and to study the asymptotic behavior of the solution when F possesses a generalized turning point at t =0. We mainly discuss regular singular crossings.

The summer solstice is the turning point when light and temperature affect the growth of trees

The interaction between light and temperature is known to influence the seasonal growth of trees.Traditional studies on"light"primarily focus on day length,specifically short day(SD)or long day(LD)conditions.However,little research has been conducted on the process of transitioning between SD and LD conditions.

Technique for Multi-Pass Turning Optimization Based on Gaussian Quantum-Behaved Bat Algorithm

The multi-pass turning operation is one of the most commonly used machining methods in manufacturing field.The main objective of this operation is to minimize the unit production cost.This paper proposes a Gaussian quantum-behaved bat algorithm(GQBA)to solve the problem of multi-pass turning operation.The proposed algorithm mainly includes the following two improvements.The first improvement is to incorporate the current optimal positions of quantum bats and the global best position into the stochastic attractor to facilitate population diversification.The second improvement is to use a Gaussian distribution instead of the uniform distribution to update the positions of the quantum-behaved bats,thus performing a more accurate search and avoiding premature convergence.The performance of the presented GQBA is demonstrated through numerical benchmark functions and amulti-pass turning operation problem.Thirteen classical benchmark functions are utilized in the comparison experiments,and the experimental results for accuracy and convergence speed demonstrate that,in most cases,the GQBA can provide a better search capability than other algorithms.Furthermore,GQBA is applied to an optimization problem formulti-pass turning,which is designed tominimize the production cost while considering many practical machining constraints in the machining process.The experimental results indicate that the GQBA outperforms other comparison algorithms in terms of cost reduction,which proves the effectiveness of the GQBA.

A theoretical and deep learning hybrid model for predicting surface roughness of diamond-turned polycrystalline materials

Polycrystalline materials are extensively employed in industry.Its surface roughness significantly affects the working performance.Material defects,particularly grain boundaries,have a great impact on the achieved surface roughness of polycrystalline materials.However,it is difficult to establish a purely theoretical model for surface roughness with consideration of the grain boundary effect using conventional analytical methods.In this work,a theoretical and deep learning hybrid model for predicting the surface roughness of diamond-turned polycrystalline materials is proposed.The kinematic–dynamic roughness component in relation to the tool profile duplication effect,work material plastic side flow,relative vibration between the diamond tool and workpiece,etc,is theoretically calculated.The material-defect roughness component is modeled with a cascade forward neural network.In the neural network,the ratio of maximum undeformed chip thickness to cutting edge radius RT S,work material properties(misorientation angle θ_(g) and grain size d_(g)),and spindle rotation speed n s are configured as input variables.The material-defect roughness component is set as the output variable.To validate the developed model,polycrystalline copper with a gradient distribution of grains prepared by friction stir processing is machined with various processing parameters and different diamond tools.Compared with the previously developed model,obvious improvement in the prediction accuracy is observed with this hybrid prediction model.Based on this model,the influences of different factors on the surface roughness of polycrystalline materials are discussed.The influencing mechanism of the misorientation angle and grain size is quantitatively analyzed.Two fracture modes,including transcrystalline and intercrystalline fractures at different RTS values,are observed.Meanwhile,optimal processing parameters are obtained with a simulated annealing algorithm.Cutting experiments are performed with the optimal parameters,and a flat surface finish with Sa 1.314 nm is finally achieved.The developed model and corresponding new findings in this work are beneficial for accurately predicting the surface roughness of polycrystalline materials and understanding the impacting mechanism of material defects in diamond turning.

Status of research on non-conventional technology assisted single-point diamond turning

With the increasing use of difficult-to-machine materials in aerospace applications,machining requirements are becoming ever more rigorous.However,traditional single-point diamond turning(SPDT)can cause surface damage and tool wear.Thus,it is difficult for SPDT to meet the processing requirements,and it has significant limitations.Research indicates that supplementing SPDT with unconventional techniques can,importantly,solve problems due to the high cutting forces and poor surface quality for difficult-to-machine materials.This paper first introduces SPDT and reviews research into unconventional techniques for use with SPDT.The machining mechanism is discussed,and the main advantages and disadvantages of various methods are investigated.Second,hybrid SPDT is briefly described,which encompasses ultrasonic-vibration magnetic-field SPDT,ultrasonic-vibration laser SPDT,and ultrasonic-vibration cold-plasma SPDT.Compared with the traditional SPDT method,hybrid SPDT produces a better optical surface quality.The current status of research into unconventional techniques to supplement SPDT is then summarized.Finally,future development trends and the application prospects of unconventional assisted SPDT are discussed.

Design of a coated thinly clad chalcogenide long-period fiber grating refractive index sensor based on dual-peak resonance near the phase matching turning point

A novel method for designing chalcogenide long-period fiber grating(LPFG) sensors based on the dual-peak resonance effect of the LPFG near the phase matching turning point(PMTP) is presented. Refractive index sensing in a high-refractive-index chalcogenide fiber is achieved with a coated thinly clad film. The dual-peak resonant characteristics near the PMTP and the refractive index sensing properties of the LPFG are analyzed first by the phase-matching condition of the LPFG. The effects of film parameters and cladding radius on the sensitivity of refractive index sensing are further discussed. The sensor is optimized by selecting the appropriate film parameters and cladding radius. Simulation results show that the ambient refractive index sensitivity of a dual-peak coated thinly clad chalcogenide LPFG at the PMTP can be 2400 nm/RIU, which is significantly higher than that of non-optimized gratings. It has great application potential in the field of chemical sensing and biosensors.