Human resources allocation for aircraft maintenance with predefined sequence

There are always large-scale items in the maintenances schedule of aircraft system, many of which have been fixed to be done in predefined sequences, which leads the workflow to be sys-tematically complex and makes this kind of problem quite different from all sorts of existing job-selection modes. On the other hand, the human resources are always limited and men have different working capabilities on different items, which make the allocation operation of human resources be much roomy. However, the final total time span of maintenance is often required to be as short as possible in many practices, in order to suffer only the lowest cost of loss while the system is stopping. A new model for op-timizing the allocation if aircraft maintenance human resources with the constraint of predefined sequence is presented. The ge-netic algorithm is employed to find the optimal solution that holds the shortest total time span of maintenance. To generate the ul-timate maintenance work items and the human resource array, the sequences among all maintenance work items are considered firstly, the work item array is then generated through traversal with the constraint of maintenance sequence matrix, and the human resources are finally allocated according to the work item array with the constraint of the maintenance capability. An example is demonstrated to show that the model and algorithm behave a satisfying performance on finding the optimal solution as expected.

Predefined Exponential Basis Set for Half-Bounded Multi Domain Spectral Method

A non-orthogonal predefined exponential basis set is used to handle half-bounded domains in multi domain spectral method (MDSM). This approach works extremely well for real-valued semi-infinite differential problems. It spans simultaneously wide range of exponential decay rates with multi scaling and does not suffer from zero crossing. These two conditions are necessary for many physical problems. For comparison, the method is used to solve different problems and compared with analytical and published results. The comparison exhibits the strengths and accuracy of the presented basis set.

Exponential Continuous Non-Parametric Neural Identifier With Predefined Convergence Velocity

This paper addresses the design of an exponential function-based learning law for artificial neural networks(ANNs)with continuous dynamics.The ANN structure is used to obtain a non-parametric model of systems with uncertainties,which are described by a set of nonlinear ordinary differential equations.Two novel adaptive algorithms with predefined exponential convergence rate adjust the weights of the ANN.The first algorithm includes an adaptive gain depending on the identification error which accelerated the convergence of the weights and promotes a faster convergence between the states of the uncertain system and the trajectories of the neural identifier.The second approach uses a time-dependent sigmoidal gain that forces the convergence of the identification error to an invariant set characterized by an ellipsoid.The generalized volume of this ellipsoid depends on the upper bounds of uncertainties,perturbations and modeling errors.The application of the invariant ellipsoid method yields to obtain an algorithm to reduce the volume of the convergence region for the identification error.Both adaptive algorithms are derived from the application of a non-standard exponential dependent function and an associated controlled Lyapunov function.Numerical examples demonstrate the improvements enforced by the algorithms introduced in this study by comparing the convergence settings concerning classical schemes with non-exponential continuous learning methods.The proposed identifiers overcome the results of the classical identifier achieving a faster convergence to an invariant set of smaller dimensions.

Event-triggered neuroadaptive predefined practical finite-time control for dynamic positioning vessels:A time-based generator approach

This paper discusses the predefined practical finite-time(PPFT)dynamic positioning(DP)control problem for DP vessels subject to internal/external uncertainties.Those heterogeneity uncertainties are handled by a separate-type treatment approach.The finite-time(FT)DP control is fulfilled by a predefined FT function on the basis of a time-based generator(TBG).Under the dynamic surface control together with the TBG design framework,the convergence time and control accuracy of the DP system can be determined by the designer offline.Meanwhile,the virtual derivation and computational burden problems are dissolved by using a first-order filter and virtual parameter learning technique.To reduce mechanical wear,an event-triggering protocol between the control law and the actuator is built to reduce the operating frequency of the actuator.An event-triggered neuroadaptive PPFT control scheme is presented for DP vessels.The stability of the closed-loop DP control systems is validated via the Lyapunov theorem.Approach efficiency is confirmed by numerical examples.

Connectivity-preserving consensus of nonlinear switched multi-agent systems with predefined accuracy

This paper focuses on the connectivity-preserving consensus of nonlinear switched multi-agent systems with predefined accuracy.Accordingly,a unified error transformation is adopted to preserve the initial interaction pattern determined by agents’limited communication ranges and initial states.Meanwhile,the so-called congelation of variables method is used to handle the unknown aperiodically time-varying parameters,which are fast-varying in an unknown compact set with only their radii known a priori.In addition,a series of continuously differentiable functions are incorporated into the Lyapunov function to design the controller.Based on Lyapunov stability theory,the proposed control algorithm guarantees that the consensus errors converge with a predefined accuracy,whereas most existing connectivity-preserving results can only ensure uniform ultimate boundedness.Simultaneously,all closed-loop signals remain bounded.Finally,two simulations are provided to validate the effectiveness of the proposed control protocol.

New nonlinear stiffness actuator with predefined torque‒deflection profile

A nonlinear stiffness actuator(NSA)could achieve high torque/force resolution in low stiffness range and high bandwidth in high stiffness range,both of which are beneficial for physical interaction between a robot and the environment.Currently,most of NSAs are complex and hardly used for engineering.In this paper,oriented to engineering applications,a new simple NSA was proposed,mainly including leaf springs and especially designed cams,which could perform a predefined relationship between torque and deflection.The new NSA has a compact structure,and it is lightweight,both of which are also beneficial for its practical application.An analytical methodology that maps the predefined relationship between torque and deflection to the profile of the cam was developed.The optimal parameters of the structure were given by analyzing the weight of the NSA and the mechanic characteristic of the leaf spring.Though sliding friction force is inevitable because no rollers were used in the cam-based mechanism,the sliding displacement between the cam and the leaf spring is very small,and consumption of sliding friction force is very low.Simulations of different torque‒deflection profiles were carried out to verify the accuracy and applicability of performing predefined torque‒deflection profiles.Three kinds of prototype experiments,including verification experiment of the predefined torque‒deflection profile,torque tracking experiment,and position tracking experiment under different loads,were conducted.The results prove the accuracy of performing the predefined torque‒deflection profile,the tracking performance,and the interactive performance of the new NSA.

High-resolution photogrammetry to measure physical aperture of two separated rock fracture surfaces

Photogrammetry,reconstructing three-dimensional(3D)models from overlapping two-dimensional(2D)photos,finds application in rock mechanics and rock engineering to extract geometrical details of reconstructed objects,for example rock fractures.Fracture properties are important for determining the mechanical stability,permeability,strength,and shear behavior of the rock mass.Photogrammetry can be used to reconstruct detailed 3D models of two separated rock fracture surfaces to characterize fracture roughness and physical aperture,which controls the fluid flow,hydromechanical and shear behavior of the rock mass.This research aimed to determine the optimal number of scale bars required to produce high-precision 3D models of a fracture surface.A workflow has been developed to define the physical aperture of a fracture using photogrammetry.Three blocks of Kuru granite(25 cm×25 cm×10 cm)with an artificially induced fracture,were investigated.For scaling 3D models,321 markers were used as ground control points(GCPs)with predefined distances on each block.When the samples were wellmatched in their original positions,the entire block was photographed.Coordinate data of the GCPs were extracted from the 3D model of the blocks.Each half was surveyed separately and georeferenced by GCPs and merged into the same coordinate system.Two fracture surfaces were extracted from the 3D models and the vertical distance between the two surfaces was digitally calculated as physical aperture.Accuracy assessment of the photogrammetric reconstruction showed a 20-30 mm digital control distance accuracy when compared to known distances defined between markers.To attain this accuracy,the study found that at least 200 scale bars were required.Furthermore,photogrammetry was employed to measure changes in aperture under normal stresses.The results obtained from this approach were found to be in good agreement with those obtained using linear variable displacement transducers(LVDTs),with differences ranging from 1 mm to 8μm.

Thermodynamic analysis on synthesis of fibrous Ni-Co alloys precursor and Ni/Co ratio control

According to the principles of simultaneous equilibrium and mass equilibrium, a series of thermodynamic equilibrium equations in Ni（II）-Co（II）-C2O4^2--NH3-NH4^＋-H2O system at ambient temperature were deduced. The diagrams of logarithm ion concentrations versus pH values at different solution compositions were drawn. The results show that Ni^2＋ and Co^2＋ can completely precipitate at pH less than 5.0 and the predefined Ni/Co ratios can be well kept in the precursor. The precursor morphology is granular aggregation. However, rod aggregation precursor is obtained in the pH range of 5.0-8.0, and fibre-shape precursor is got at pH value higher than 8.0. The Ni/Co ratios in the above two precursors are not reproduced as that in the feed due to the formhtion of multi-coordinated Ni（NH3）n^2＋ and Co（NH3）n^2＋ （n=1-6）. Modification of precipitation medium is favorable for the precursors to keep the predefined Ni/Co ratios of the feed in the pH range of 2.0-8.6. Meanwhile, the precursors with fibrous morphology can be obtained.

Prescribed Performance Control of One-DOF Link Manipulator With Uncertainties and Input Saturation Constraint

In this paper, we mainly address the position control problem for one-degree of freedom(DOF) link manipulator despite uncertainties and the input saturation via the backstepping technique, active disturbance rejection control(ADRC) as well as predefined tracking performance functions. The extended state observer(ESO) is employed to compensate uncertain dynamics and disturbances, and it does not rely on the accurate model of systems. The tracking differentiator(TD) is utilized to substitute the derivative of the virtual control signals, and the explosion of complexity caused by repeated differentiations of nonlinear functions is removed. The auxiliary system is used to deal with the control input limitation, and the tracking accuracy and speed are improved by predefined tracking performance functions.With the help of the input-to-state stability(ISS) and Lyapunov stability theories, it is proven that the tracking error can be gradually converged into arbitrarily small neighborhood of the origin, and the tracking error is adjusted by suitable choice of control parameters. The simulation results are presented for the verification of the theoretical claims.