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In this work, the Pachycondyla Apicalis metaheuristic algorithm (API) is used to identify and optimize control parameters for piezoelectric oscillator that exhibits frequency hysteresis behavior under strong excitation when asymmetric period which the bifurcation and chaotic behavior of higher harmonics appear by minimizing errors between actual and evaluated states of the model. In order to investigate the efficiency of the API algorithm, numerical experiments are carried out on the piezoelectric chaotic resonator. The simulation results indicate that the API algorithm can be effective in identifying the unknown parameters for given chaotic systems with high accuracy and low deviations. [ABSTRACT FROM AUTHOR]

We introduce the artificial fish swarm algorithm for heading motion model identification and control parameter optimization problems for the “Ocean Rambler” unmanned wave glider (UWG). First, under certain assumptions, the rigid-flexible multi-body system of the UWG was simplified as a rigid system composed of “thruster + float body”, based on which a planar motion model of the UWG was established. Second, we obtained the model parameters using an empirical method combined with parameter identification, which means that some parameters were estimated by the empirical method. In view of the specificity and importance of the heading control, heading model parameters were identified through the artificial fish swarm algorithm based on tank test data, so that we could take full advantage of the limited trial data to factually describe the dynamic characteristics of the system. Based on the established heading motion model, parameters of the heading S-surface controller were optimized using the artificial fish swarm algorithm. Heading motion comparison and maritime control experiments of the “Ocean Rambler” UWG were completed. Tank test results show high precision of heading motion prediction including heading angle and yawing angular velocity. The UWG shows good control performance in tank tests and sea trials. The efficiency of the proposed method is verified. [ABSTRACT FROM AUTHOR]

Soft tissues are characterized by a nonlinear mechanical response, highly affected by the multiscale structure of collagen fibers. The effectiveness and the calibration of constitutive models play a major role on the reliability and the applicability of computational models in biomechanics. This paper presents a procedure for the identification of the relationship between collagen-related structural features in soft tissues with model parameters of classical polynomial- and exponential-based constitutive models. Histological features at microscale, as well as biochemical and biophysical properties at nanoscale, are addressed by employing a multiscale structural description of soft tissue mechanics as benchmark data set. Both the direct (from structure to parameters) and the inverse (from parameters to structure) problem are addressed. Suitable optimization problems are introduced for accurate numerical and approximated analytical direct relationships. The inverse identification has been addressed by providing also a measure of the reliability of the computed estimates. Results show the effectiveness of the proposed strategies and allow to discuss the fitting capabilities of classical constitutive approaches in terms of parameters identification. [ABSTRACT FROM AUTHOR]

To accurately describe the operating mechanism of supercapacitor (SC), a precise model should be established for the SC. In this paper, an equivalent-circuit model with a controlled current source is proposed, which can simulate the dynamic behavior of the SC. The recursive least square algorithm with forgetting factor is introduced to identify model parameters. Experimental and simulation results are presented to verify the proposed equivalent-circuit model. Results show a very good performance since the maximum relative modeling error do not exceed 1%. Therefore, the proposed model with its parameter identification method can effectively reveal the operating mechanism of the SC. [ABSTRACT FROM AUTHOR]

Water-rich soft rock roadway with fast deformation speed, large deformation and support difficulty, the key for this issue is to establish a rheological model describing the characteristics. Through shear creep test of soft rock with different moisture content, the experimental results show that under the same shear stress level the instantaneous elastic modulus, the ultimate deformation modulus and the coefficient of viscosity of soft rock decreases, the creep rate increases first and then decreases, the destruction time of accelerated creep is shortened with the increase of moisture content；With the increase of shear stress, the instantaneous shear displacement, creep deformation and the radius of curvature of the attenuation creep stage increase gradually under the same moisture content. According to the nonlinear characteristics of water-rich soft rock creep, a nonlinear shear rheological model is established to describe the creep characteristics of water-rich soft rock, and model parameters are identificated based on the BFGS algorithm and universal global optimization method, the identification results agree well with the experimental curves, which show that the model is correct and reasonable. It is very important significance for rich-water soft rock roadway stability research in the deep and complex geological mechanics environment. [ABSTRACT FROM AUTHOR]

One of the major issues in simulation and control of power system dynamics is load modelling. More accurate load models in power system stability analysis increases the accuracy of simulation results. If inappropriate model is used for the load, the obtained results may contain a high degree of error. In majority of analysis, the loads are usually considered as a constant impedance element. Whereas, such a model is not only accountable for the stability analysis of power system but also may sometimes lead to opposite results. Due to the variation of the load and also the variation of the composition of the load components, it would be difficult to provide a fixed model for electrical loads similar to those of other elements of the power system. A method for modelling the power system loads via genetic algorithm is presented in this paper. This methodology is performed based on the composite load model. In order to get an accurate load model, several scenarios are considered. The particular method of this paper is that after obtaining the load model parameters corresponding to each of the scenarios, various values obtained for the parameters are averaged. Finally, the validity of the obtained parameters is testified with some other scenarios. The results reported in this paper indicate that the existing load models satisfactorily describe the actual behaviour of the physical load and can be reliably estimated using the identification techniques presented herein. [ABSTRACT FROM AUTHOR]

In this paper, a new inverse method is proposed to identify the anisotropic plasticity properties of materials using solely the residual imprint mapping in spherical indentation. This method does not need the entire load-displacement (P-h) curve in spherical indentation experiment. The stress strain curves along transverse and longitudinal directions of the indented specimens can be simultaneously identified using single spherical indentation test. The new method is based on weighting the average and difference amounts, S ̅ and ∆ S of the residual imprint snapshots along transverse and longitudinal directions. The proper orthogonal decomposition is used to correlate the effective imprint snapshots with material constitutive parameters, and the inverse problem is solved by the “Interior-point” optimization algorithm. We finally applied the new method on the SiCw/A6061. The well-posed solution of material properties is achieved, and the anisotropic plasticity parameters obtained from indentation and uniaxial tests show good agreement. Besides, the influence of weighting factor and experiment error on the numerical results are also investigated. Results indicate the proposed inverse method is very effective and reliable. [ABSTRACT FROM AUTHOR]

The positioning accuracy of the empirical robot manipulators is determined by various factors, such as kinematic accuracy, structure rigidity, and controller performance. Here, we report on the development of a new and straightforward technique to calibrate the kinematic parameters of a dual-arm robot under uncertainty. In comparison with other techniques, which generally rely on using other instruments to calibrate the manipulators, the proposed method utilizes the intrinsic characteristics of the dual-arm robot for calibration. In particular, when the two arms grasp each other, a formed closed chain can be operated as the constraint equation for the kinematic parameter optimization of the two arms. In the optimization process, the dual-arm robot has to pose in various configurations to yield better performance, and thus a motion generation strategy of the dual-arm robot is proposed, where one arm serves as the master to track the designated trajectory and the other arm serves as the slave to track the motion of the master arm by using a compliance control strategy. The proposed calibration method was experimentally validated, and the results confirm that the positioning accuracy of both arms can be improved. [ABSTRACT FROM AUTHOR]

This paper presents an improved method for the reconstruction of busbar voltage waveforms from signals acquired by a system of electric field (EF) sensors located in an indoor medium voltage substation. In the previous work [8], the authors proposed the use of black-box models in the form of artificial neural networks (ANNs) for this task. In this paper it is shown that a parametric model of the system of EF sensors can reconstruct voltages with much lower errors, provided that it is accurately identified. The model identification is done by minimization of a nonlinear goal function, i.e. mean squared error (MSE) of voltage reconstruction. As a result of examining several optimization techniques, the method based on simulated annealing extended with a simplex search, is proposed. The performance of the model identified with this method is at least 8 times better in terms of MSE and at least 12 times better in terms of frequency domain errors than the best one of concurrent ANNs. [ABSTRACT FROM AUTHOR]

Copyright of Engineering Mechanics / Gongcheng Lixue is the property of Engineering Mechanics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A novel parameters identification method is proposed in this paper, which adopts the rectangular strain rosette structure with three FBGs, BFM (Body Force Method, BFM) theory and improved PSO (Particle Swarm Optimization, PSO) algorithm to identify the parameters for crack. To detect the strains, a rectangular strain rosette structure with three FBGs is adopted, and the transverse effect correction factor is established to improve the accuracy. The position of crack can be determined by improved PSO algorithm. By utilizing the principal strain direction angle to coarsely get the center coordinates of the crack which can initialize the particle, the local optimum problem of PSO can be solved. To improve the performance of PSO, the weight and termination condition are modified, and the selection of learning factors is discussed. To test performance of improved PSO algorithm, a well-known benchmark problem of the mathematical test function is first solved, and the numerical experiments have shown that the proposed PSO obtains better results among the compared algorithms. [ABSTRACT FROM AUTHOR]

In this paper, a novel inverse computation approach is proposed to extract the anisotropic plasticity parameters of metal materials by using inverse analysis and dual indentation tests. Based on dimensional analysis and extensive finite element (FE) simulations, four independent dimensionless functions are derived to correlate the anisotropic plasticity parameters with material responses in dual indentation tests. Besides, an inverse calculation algorithm is suggested, to estimate the unknown anisotropic parameters of the indented specimens using the information collected from indentation. The proposed numerical approach is applied on a series of engineering materials. Results show that the inverse analysis is ill-posed when only the load-displacement (P-h) curves in dual indentation tests were used. This problem can be effectively alleviated by introducing the pile-up effect as the additional information. The new method is proved to be very effective and reliable. [ABSTRACT FROM AUTHOR]

The establishment of the Aircraft Dynamic Model (ADM) constitutes the prerequisite for the design of the navigation and control system, but the aerodynamic parameters in the model could not be readily obtained especially for small-scaled fixed-wing UAVs. In this paper, the procedure of computing the aerodynamic parameters is developed. All the longitudinal and lateral aerodynamic derivatives are firstly calculated through semi-empirical method based on the aerodynamics, rather than the wind tunnel tests or fluid dynamics software analysis. Secondly, the residuals of each derivative are proposed to be identified or estimated further via Extended Kalman Filter (EKF), with the observations of the attitude and velocity from the airborne integrated navigation system. Meanwhile, the observability of the targeted parameters is analyzed and strengthened through multiple maneuvers. Based on a small-scaled fixed-wing aircraft driven by propeller, the airborne sensors are chosen and the model of the actuators are constructed. Then, real flight tests are implemented to verify the calculation and identification process. Test results tell the rationality of the semi-empirical method and show the improvement of accuracy of ADM after the compensation of the parameters. [ABSTRACT FROM AUTHOR]

Based on the relationship between finite element (FE) solution and mesh size, a new approach based on mesh depending on the material properties is proposed to make the finite element analysis results more efficient and more close to the optimal solution. This optimal solution is often evaluated either by experiment or by finite element method (FEM). At the opposite of the accuracy obtained by sensitivities analysis of the FEM which requires time-consuming, our approach allows getting the optimal meshing based on the material properties. [ABSTRACT FROM AUTHOR]

A comparative study of optimization techniques for identifying soil parameters in geotechnical engineering was first presented. The identification methodology with its 3 main parts, error function, search strategy, and identification procedure, was introduced and summarized. Then, current optimization methods were reviewed and classified into 3 categories with an introduction to their basic principles and applications in geotechnical engineering. A comparative study on the identification of model parameters from a synthetic pressuremeter and an excavation tests was then performed by using 5 among the mostly common optimization methods, including genetic algorithms, particle swarm optimization, simulated annealing, the differential evolution algorithm and the artificial bee colony algorithm. The results demonstrated that the differential evolution had the strongest search ability but the slowest convergence speed. All the selected methods could reach approximate solutions with very small objective errors, but these solutions were different from the preset parameters. To improve the identification performance, an enhanced algorithm was developed by implementing the Nelder-Mead simplex method in a differential algorithm to accelerate the convergence speed with strong reliable search ability. The performance of the enhanced optimization algorithm was finally highlighted by identifying the Mohr-Coulomb parameters from the 2 same synthetic cases and from 2 real pressuremeter tests in sand, and ANICREEP parameters from 2 real pressuremeter tests in soft clay. [ABSTRACT FROM AUTHOR]

Experimental modal analysis, dynamic modeling and parameter identification is employed to investigate the in-plane vibration modal characteristic of a heavy-loaded radial tire with a larger flat ratio. In-plane vibration characteristic of heavy-loaded radial tire is modeled as flexible beam on modified elastic foundation model and flexible tread and distributed sidewall are respectively modeled as the Euler beam and distributed mass element with sectional stiffness. Analytic relationship between the modal resonant frequency and the structural parameters is solved and derived with modal expansion method. The in-plane coupling modal between the flexible tread and sidewall is investigated experimentally. The unknown structural parameters are identified by the genetic algorithm based on the experimental and analytical modal parameter. The higher order modal frequency is predicted with the identified structural parameters and the influence of structural parameters on the modal parameters is compared. Experimental and theoretical result shows that: the experimental modal analysis and theoretical modeling method with the coupling feature of flexible tread, distributed sidewall and rim can accurately characterize the in-plane vibration feature of heavy-loaded radial tire within the frequency band of 300 Hz, compared with the method which only considers the flexible feature of tread and is limited to 180 Hz. [ABSTRACT FROM AUTHOR]

Generally, the relative parameters of continuous multi-impacts are ambiguous in the practical engineering. In this paper, continuous twice-impacts of Ultra-High Molecule Weight Polyethylene (UHMWPE) laminate which is fixed by four bolted joints are designed and conducted by experiment and simulation. The experimental results of first impact are used to verify the numerical model, in which a solid blunt projectile penetrates the laminate with the velocity of 216 m/s. The obtained results of experiment and simulation indicate that strong lateral effects can be observed for the twice-impacts of UHMWPE target fixed with bolted joints, then the deformation responses of bolt holes are studied to discuss parameters identification of secondary non-penetration impact, i.e., the velocity and impact position of secondary penetrator are identified based on inverse problem model. Finally, the numerical results calculated with the identification parameters are in good agreement with the twice-impacts test. The research scheme of this paper is significant to recognize the process of multi-impacts. [ABSTRACT FROM AUTHOR]

To improve the accuracy of extreme short-term prediction of ship motion under environmental disturbances, a method to identify the motion model of ship turning maneuver and predict the ship extreme short-term trajectory with the influence of ocean currents is studied. Under the influence of ocean currents, a ship motion response model is identified based on the least squares method, and a ship extreme short-term trajectory prediction model is established. The velocity distribution extraction algorithm, center point restoration algorithm, and weighted derivation algorithm are proposed to extract the current direction and the velocity of the turning test. By integrating the current information and ship response characteristics in the extreme short-term ship prediction model, the extreme short-term segmented prediction of the ship trajectory is realized, and the current information is corrected online according to the prediction errors. The real test results show that, compared with the prediction method based on the ship dynamic model, inertia derivation and current compensation, the proposed extreme short-term trajectory prediction method has higher accuracy. Specifically, the prediction error of the proposed method is reduced by 80.6%, 89.3%, and 54.7% than abovementioned methods, respectively. • Ship extreme short-term trajectory prediction is modelled under sea current influence. • VDE, CPR, and WD are to extract the sea current information. • Online corrected extreme short-term trajectory prediction is verified in actual sea area. [ABSTRACT FROM AUTHOR]

• A numerical model able to VIV on a circular cylinder is presented. • The model parameters are defined by using a genetic algorithm-based approach • Results of the model are discussed and compared to experimental data • The idea is to define a model for VIV usable for civil applications. The paper presents a numerical model, based on the equivalent oscillator approach, able to simulate vortex induced vibrations on a circular cylinder. This model consists of a single degree of freedom mechanical system characterized by non-linear parameters that reproduce the fluid-structure interaction in time domain. A genetic algorithm approach was used in order to identify the characteristic parameters of the equivalent oscillator: obtained results are discussed and compared with wind tunnel experimental data and with a previous version of the numerical model. Comparison is performed both in terms of aerodynamic forces and oscillation amplitudes and both in steady and transient conditions. [ABSTRACT FROM AUTHOR]

• A new methodology for multi-parameter identification of concrete dams is proposed. • For the first time, polynomial chaos expansion and slime mould algorithm are integrated. • A very high computational efficiency is achieved using the proposed methodology. This paper presents a novel methodology that combines polynomial chaos expansion and slime mould algorithm for multi-parameter identification of concrete dams. This methodology not only incorporates the merits of low computational cost in the polynomial chaos expansion and fast convergence of slime mould algorithm, but also considers the priori uncertainty in the input parameters by introducing statistical probability theory. By considering two examples with different complexity, this paper verifies the effectiveness of the proposed method with a univariate simply supported beam model, followed by a complex multivariate dam model to demonstrate its practicability in real engineering problems. In addition, parameter sensitivity analysis of the dam model is conducted at an extremely low cost by polynomial chaos expansion based on Sobol' indices. Furthermore, the conventional parameter identification methods based on optimization methods directly combined with the finite element model are employed for comparison, highlighting two distinct advantages of the proposed method: (i) the proposed method improves the computational efficiency by nearly 52 times while ensuring a high accuracy, and (ii) the classical non-population optimization algorithm, Bayesian optimization, is used for comparison, revealing the outstanding performance of slime mould algorithm in terms of convergence speed and robustness. The application of the proposed algorithm is not only limited to dams, but also it can be extended to any structure. [ABSTRACT FROM AUTHOR]

This brief paper describes a new approach to identification of unknown constant parameters for a linear regression model. The main idea of the method lies in transformation of initial model into a new kind one. The new model regressor possesses identification properties or meets persistency of excitation conditions. An example of two unknown parameters identification for the linear regression model shows efficiency of the proposed approach. Simulation was carried out for a regressor with no persistency of excitation conditions, hence, parameter identification is not guaranteed.

Relevance of the research is caused by fact that 80 % of oil in the Russian Federation is extracted using electrical submersible pump units and this index is growing, but specific ratio of wells with electrical submersible pump in the general fund has not almost changed and it is about 34 %. It necessary to note that maintenance of optimal operation of the electrical drive, for example maximum volume of oil production at the lowest electrical power consumption, depends not only on the correct configuration of units and processing of external actions, but also it depends on self-tuning of adaptive control system, including the solution of the problems of identifying online the parameters of submersible induction motors. The aim of the research is to design and test the method for online identification of the parameters of submersible induction motors based on the algebraic identification methods and discrete models. Methods of research are based on using the systems of differential and difference equations, algebraic identification methods, construction of discrete mathematical models of submersible induction motors. Results. The authors have designed the software system for monitoring the parameters of the submersible induction motors and tested this system by mathematical modeling. Using the designed software system for online monitoring the parameters of submersible induction motors is expedient. The perspective of using the designed system is in improving the intelligent control system of submersible centrifugal pump, that will result in increasing the exploitation efficiency, decreasing drive power consumption, accordingly reducing oil production cost, and increasing fault tolerance of the submersible induction motors due to online monitoring for motor parameters.

The paper considers a possibility to apply a hybrid model for approximation of the currentvoltage characteristics of MOSFETs in a wide temperature range from cryogenic temperatures to regular (room) temperatures (20 … 300 K). Being analytical and compact, the hybrid model contains additional formal parameters along with the physical ones. The hybrid analytical model, presented in this paper, is intended for the MOSFETs to be used as active components in low noise amplifiers. Low noise amplifiers, in turn, are used in radio-receivers of infrared and optical bands in astronomical satellites, radio-telescopes, and space observatories.Low noise amplifiers are capable to work both at temperatures close to the room ones and at low (cryogenic) temperatures. Cooling a device allows improvement of the basic characteristics and the reliability of MOSFETs i.e. increasing a transconductance of the MOSFET and reducing self-noise. Demand to use the hybrid model is explained by the fact that modern models do not ensure a high accuracy of the current-voltage characteristics approximation for the MOSFETs which have a sufficiently large channel size and work in a wide temperature range, including cryogenic ones.The hybrid model of the MOSFET represents a compact analytical model with only physical parameters and a correction function as a two-dimensional power polynomial. The coefficients of the correction function, actually, are formal parameters of the hybrid model and are defined without using the nonlinear optimization methods.The hybrid analytical model allows approximation of MOSFET experimental currentvoltage characteristics with the relative root-mean-square error less than 0,1 % independently of a temperature at which the measurements are carried out. The accuracy of the hybrid analytical model increases with increasing correction function order. The less an accuracy of the initial model the more benefit from the hybrid model application. The greatest increase of accuracy is achieved for transistors to be used as active components in low noise amplifiers at cryogenic temperatures.

This article presents a novel methodology for the determination of synchronous machine parameters from the sudden short-circuit (SCC) test. Records of armature and field currents transient behavior are used to evaluate thed-axis equivalent circuit, including the rotor characteristic reactance, and the traditional synchronous machine parameters. The method is based on the evolutionary computer algorithm, the hybrid particle swarm optimization (HPSO). The developed program has been successfully applied into two large salient pole synchronous machines test data. [ABSTRACT FROM PUBLISHER]

Sphere-plane contact is ubiquitous in the fields of equipment manufacturing and intelligent machine design. Research on sphere-plane contact processes not only helps to reveal the causes of instability in terms of contact object motions, functional failures, and vibration noises, but also allows for an accurate prediction of dynamic behavior for the precise control of real-time intelligent machinery. The contact part of the process parameters related to impact are difficult to measure, and current sphere-plane contact impact theory models do not accurately reflect them. Contact process calculations are generally inaccurate, and finite element simulation analysis for the sphere-plane contact impact process is computationally burdensome. In this study, the finite element simulation method was used to obtain contact force, relative penetration, and velocity as input parameter estimations. Contact stiffness, hysteresis damping factors, and elastic impact index were estimated using theoretical model calculations to improve computing velocity and accuracy. [ABSTRACT FROM AUTHOR]

Both environment protection and energy saving have attracted more and more attention in the electric vehicles (EVs) field. In fact, regarding control performance, electric motor has more advantages over conventional internal combustion engine. To decouple the interaction force between vehicle and various coordinating and integrating active control subsystems and estimate the real-time friction force for Advanced Emergency Braking System (AEBS), this paper's primary intention is uniform distribution of longitudinal tire-road friction force and control strategy for a Novel Anti-lock Braking System (Nov- ABS) which is designed to estimate and track not only any tire-road friction force, but the maximum tire-road friction force, based on the Anti-Lock Braking System (ABS). The longitudinal tire-road friction force is computed through real-time measurement of breaking force and angular acceleration of wheels. The Magic Formula Tire Model can be expressed by the reference model. The evolution of the tire-road friction is described by the constrained active-set SQP algorithm with regard to wheel slip, and as a result, it is feasible to identify the key parameters of the Magic Formula Tire Model. Accordingly, Inverse Quadratic Interpolation method is a proper way to estimate the desired wheel slip in regards to the reference of tireroad friction force from the top layer. Then, this paper adapts the Nonlinear Sliding Mode Control method to construct proposed Nov-ABS. According to the simulation results, the objective control strategy turns out to be feasible and satisfactory. [ABSTRACT FROM AUTHOR]

Copyright of Electric Machines & Control / Dianji Yu Kongzhi Xuebao is the property of Electric Machines & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Basic Sciences Journal of Textile Universities / Fangzhi Gaoxiao Jichu Kexue Xuebao is the property of Basic Sciences Journal of Textile Universities and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Targeted at one kind of on-orbit servicing spacecraft that contains flue containers, momentum actuators, space manipulators, and captured unknown objects, a specific attitude control problem during orbital maneuvers is under investigation in this paper. To overcome strong uncertainties during the onboard service, a parameter-identification algorithm is developed to estimate all inertial parameters of each part of the spacecraft system, and the identification results are obtained based solely on the measurement of the inertial navigation system. Therefore, the disturbance from the torque coupling of the orbital engine can be thus effectively compensated. Based on the identified parameters, the attitude stabilization problem is taken into practical consideration to tackle the strong influence from the orbital engine disturbance of concern. In order to specifically suppress the disturbance, a hybrid control strategy based on the momentum actuators and thrusters is proposed, which not only provides better precision than the conventional thruster-based method but also guarantees the momentum actuators against the momentum saturation issues. Numerical simulations are conducted to verify the effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]

This research work deals with the modeling of the CO adsorption on a commercial adsorbent, based on the temperature dependent Sips and Toth models. In fact, these semi-empirical approaches can properly predict the equilibrium of adsorption of CO, and more specifically in the case of energetically heterogeneous surfaces. In addition, the investigated adsorption models involve several unknown parameters to be estimated from the available adsorption equilibrium experimental data, measured between 303 and 343 K and up to a CO partial pressure of 101 kPa. An estimability analysis was therefore carried out in order to evaluate which parameters are estimable and those that can be fixed either from literature or from previous studies. According to the estimability analysis, whatever the adsorption model which is used, only one over the six unknown parameters is considered as nonestimable. The estimable model parameters are especially the maximum amount adsorbed (q), the equilibrium constant (b), the heterogeneity factors (s and t) assessed at the reference temperature (T) as well as the constant model parameter (α), which is related to the heterogeneity factors (s and t). The estimable parameters were then identified and their optimized values were used in the comparison of the model predictions and the experimental measurements of CO adsorption equilibrium. The results show finally that the model predictions fit well with the experimental data. [ABSTRACT FROM AUTHOR]

“Small Punch” (SP) tests, at present frequently employed for mechanical characterizations of structural metals, particularly for diagnosis of plant components, are here considered in view of employment also for assessments of stresses. In the procedure proposed herein the standardised sample removal from an in-service component for SP tests is exploited as external action altering the residual stress state possibly present near to the surface in the location considered. Full-field measurements of consequent displacements in the surrounding surface are employed as input for inverse analysis based on the following features: computer simulations of the sample removal as for its consequences due to relaxation of the pre-existing stress state; “non-uniformity” of residual-stress dependence on depth described as layer-dependent with uniformity in each layer of a pre-defined set of layers; “discrepancy function” minimization with employment of the elasticity parameters provided by the subsequent SP test. The advantages of the novel method consist of no-more need of traditional usual “Hole Drilling” (HD) tests or other tests for residual-stress estimation. The SP experimental procedure proposed herein for estimations of both stress state and elastic-plastic material properties would imply reductions of damages, costs and times in structural diagnoses. [ABSTRACT FROM AUTHOR]

Wheeled mobile robots (WMR) are often applied to travel on outdoor unstructured environment, such as loose soil or variable field terrain. Learning the knowledge of terrain has played a significant role for better mobility and stability of WMR. In this study, a diagonal recurrent neural network-based adaptive method is proposed to identify terrain parameters by the platform of a single driving wheel. According to the classical terramechanics model of wheel-soil interaction, a decoupling simplification model is developed by closed-form analytical equations. Five unknown terrain parameters are divided into two groups and included in two complex nonlinear equations. These parameters are used to compute the model outputs of force and torque of wheel-soil interaction. Dynamic back propagation algorithm is applied to update these parameters for compensating the errors between the prediction of neural network and measurable data in real time. The results of simulation show that the terrain parameters can be obtained and approximate the experimental value of terrain parameters when the predictive errors converge to zero. [ABSTRACT FROM AUTHOR]

This paper proposes a method to identify system unknown parameters of complex network. Aimed at system unknown parameters, a method using generalized synchronization (GS) is proposed. This method bases on Barbalat lemma and Lyapunov stability scheme and contructs an auxiliary complex network with different topologies and dynamics. Some adaptive controllers are also designed to identify system parameters upon GS with delay coupling. Compared to the method based on complete outer synchronization, the proposed method can construct simple and low dimensional dynamics to identify the parameters of high dimensional dynamics. Numerical simulations are provided to show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, we study an inverse problem of parameters estimation for a new time-fractional heat conduction model in multilayered medium. In the anomalous thermal diffusion model, we consider the fractional derivative boundary conditions and the conduction obeys modified Fourier law with Riemann–Liouville fractional operator of different order in each layer. For the direct problem, we construct an effective finite difference scheme by using the balance method to deal with the discontinuity interface. For the inverse problem, we apply the nonlinear conjugate gradient (NCG) method with different conjugated coefficients to simultaneously identify the fractional exponent in each layer. Finally, we use experimental data to verify the effectiveness of the proposed technique, in which the Jacobian matrix is achieved by a derivative-free approach. We analyze the sensitivity coefficients and the convergence behaviors of the NCG algorithm. The simulation results confirm that the fractional heat conduction model with estimated parameters gives a more accurate fitting than the classical counterpart and the NCG method is a feasible and effective technique for the inverse problem of parameters estimation in fractional model. [ABSTRACT FROM AUTHOR]

A compound scheme is proposed to compensate the effect of nonlinear friction disturbance on the control precision of a three-axis inertially stabilized platform (ISP) for aerial remote sensing applications. The scheme consists of friction parameters identification and adaptive compensation. A LuGre model-based ISP friction model is first developed. Then, a comprehensive experimental scheme is proposed to obtain the static friction parameters. Further, the dynamic parameters are identified by experiments and dynamic optimization. On the basis of identified parameters and Lyapunov stability theory, a backstepping integral adaptive compensator is designed to compensate the nonlinear friction disturbance. Simulations and experiments are carried out to validate the scheme. The results show that the compound scheme can accurately obtain the friction parameters and improve the control precision and stability of ISP. [ABSTRACT FROM AUTHOR]

Mechanical structures usually contain joints or boundary conditions which affect their dynamic characteristics. Dynamic modeling of mechanical structures depends upon precise modeling of joints or boundary conditions. In this paper identification of boundary conditions of a clamped beam in flexible (non-rigid) support is considered. An identification approach for support parameters is introduced based on using natural frequencies. Simulated and experimental case studies are used to show the applicability of the introduced model. The results show the accuracy of the proposed method. [ABSTRACT FROM AUTHOR]

The modeling and state-of-charge estimation of the batteries and ultracapacitors are crucial to the battery/ultracapacitor hybrid energy storage system. In recent years, the model based state estimators are welcomed widely, since they can adjust the gain according to the error between the model predictions and measurements timely. In most of the existing algorithms, the model parameters are either configured by theoretical values or identified off-line without adaption. But in fact, the model parameters always change continuously with loading wave or self-aging, and the lack of adaption will reduce the estimation accuracy significantly. To overcome this drawback, a novel co-estimator is proposed to estimate the model parameters and state-of-charge simultaneously. The extended Kalman filter is employed for parameter updating. To reduce the convergence time, the recursive least square algorithm and the off-line identification method are used to provide initial values with small deviation. The unscented Kalman filter is employed for the state-of-charge estimation. Because the unscented Kalman filter takes not only the measurement uncertainties but also the process uncertainties into account, it is robust to the noise. Experiments are executed to explore the robustness, stability and precision of the proposed method. [ABSTRACT FROM AUTHOR]

When a rotor operates in very low rotating speeds, the fluid-film in hydrodynamic bearings is not completely formed, which allows direct metal to metal contact between the bearing and the journal. Numerous start/stop cycles also may lead to bearing wear. In this context, the present work aims to evaluate a model-based method for identification of hydrodynamic bearing wear parameters: more specifically, wear depth and angular position. The proposed method is based on minimizing an objective function, which compares the directional Frequency Response Function ( dFRF ) of the physical system with the response of the model developed here. It contemplates the numerical model of the rotor and the worn bearings, in this case, represented by linearized coefficients of damping and stiffness. Through experimental results, a deeper evaluation of the identification method is presented, such as the sensitivity to the number of points of the dFRF used in the objective function, different meshes of starting points, and the region of the dFRF used – around the resonance peak or around the oil-whirl peak. The analyses are conducted for different levels of bearing wear. The precision obtained in the results indicates that the presented method is a promising tool in the identification of bearing wear. [ABSTRACT FROM AUTHOR]

In this paper, a method for the identification of the synchronous machine parameters using data from field flashing (FF) and load rejection (LR) tests performed during commissioning, is proposed. The identification using data acquired during field flashing, a commissioning standard procedure, allows an initial estimation of the d -axis open-circuit transient time constant. A model dependent on that time constant, which relates the applied field voltage and the field current, the model inputs, and the generator terminal voltage, the model output, is derived. In the conventional load rejection, the applied field voltage is constant. This poses a practical restriction, since a constant voltage source must be available. In the load rejection identification method proposed in this paper, a model is derived which relates variable field voltage and field current, the model inputs to the generator terminal voltage, the model output, following load rejection. From the field flashing and load rejection models, the synchronous machine parameters are determined solving an optimization problem, formulated as a nonlinear least-squares problem or as an orthogonal distance regression. The orthogonal distance regression is suited to take into account noise in the model input. The proposed method is applied to synthetic data generated by simulation of a generator with known parameters. Statistical analysis shows a maximum error with relation to the true values of 35.8% for the nonlinear least-squares problem and 5.8% for the orthogonal distance regression. The method is also tested using real data acquired during commissioning of a 140 MVA hydro powerplant. The Normalized Sum of Squared Errors (NSSE), a metric to evaluate the deviation of the simulated response with relation to the measurements, gives a value less than 1% in most of the cases and a maximum of 2.3%, corroborating the accuracy of the proposed method. [ABSTRACT FROM AUTHOR]

In the paper, the fixed-time and finite-time synchronizations of multi-links complex network are investigated. Compared with finite-time synchronization, the settling time of fixed-time synchronization is independent of initial conditions. For uncertain multi-links complex networks, this paper further analyzes synchronization mechanism and unknown parameters based on the drive-response concept and finite-time stability theory. Novel synchronization control criteria and the result of parameters identification are, respectively, obtained in a finite time by utilizing Lyapunov function and linear matrix inequality (LMI). Besides, we give other two versions of finite-time synchronization and parameters identification for uncertain multi-links complex network with impulsive control input. Finally, numerical examples are given to illustrate the effectiveness of our theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, a novel inverse computation method is proposed to estimate the elastic-plastic properties of metal materials by using only the residual imprint of spherical indentation. The advantage of this method is that it does not need to know the entire loading history. The indentation experiment can be easily implemented on a hardness tester while the residual imprint can be measured using a 3D measuring laser microscope. We correlate the imprint snapshot with material constitutive parameters using proper orthogonal decomposition and parametric approximation, and then we solve the inverse problem using the “Interior-point” optimization algorithm. The effectiveness of this method is verified by application on 2099-T83 Al-Li alloys. Results show the inverse analysis gives well-posed solution of parameters of materials only when the penetration depth or the prescribed indentation load is sufficient, and the elastic-plastic properties obtained from indentation and uniaxial experimental data show good agreement. Besides, the sensitivity investigation indicates the use of weighting imprint obtained from different experiment loads is able to give a more stable and reliable result. [ABSTRACT FROM AUTHOR]