Set Of Dynamic Parameters Research Articles

Lie-theory-based dynamic model identification of serial robots considering nonlinear friction and optimal excitation trajectory

Abstract Accurate dynamic model is essential for the model-based control of robotic systems. However, on the one hand, the nonlinearity of the friction is seldom treated in robot dynamics. On the other hand, few of the previous studies reasonably balance the calculation time-consuming and the quality for the excitation trajectory optimization. To address these challenges, this article gives a Lie-theory-based dynamic modeling scheme of multi-degree-of-freedom (DoF) serial robots involving nonlinear friction and excitation trajectory optimization. First, we introduce two coefficients to describe the Stribeck characteristics of Coulomb and static friction and consider the dependency of friction on load torque, so as to propose an improved Stribeck friction model. Whereafter, the improved friction model is simplified in a no-load scenario, a novel nonlinear dynamic model is linearized to capture the features of viscous friction across the entire velocity range. Additionally, a new optimization algorithm of excitation trajectories is presented considering the benefits of three different optimization criteria to design the optimal excitation trajectory. On the basis of the above, we retrieve a feasible dynamic parameter set of serial robots through the hybrid least square algorithm. Finally, our research is supported by simulation and experimental analyses of different combinations on the seven-DoF Franka Emika robot. The results show that the proposed friction has better accuracy performance, and the modified optimization algorithm can reduce the overall time required for the optimization process while maintaining the quality of the identification results.

Numerical prediction of aerodynamic loads acting on a blade section-model oscillating in stall

For blades operating close to stall angle of attack, one of the potential instabilities is known as stall flutter. It is a dynamic instability in torsion for which the mechanism of energy transfer relies on a dynamic stall process where the flow separates partially or completely during each cycle of oscillation. It leads to dynamic loops in lift, drag and moment that affect the aerodynamic performance of the blade, create unsteady stresses in the blades and can lead to fatigue damage. In the present study, dynamic loops of a NACA 634421 airfoil in forced pitch oscillations have been simulated with the FastS CFD solver based on a URANS modelling approach and compared to benchmark experiments as well as results obtained with the ONERA semi-empirical dynamic stall model using a unique set of dynamic parameters that best fit the experimental dynamic loops. The dynamic tests have been conducted for a mean angle of attack of 13.5°, an amplitude of oscillation of 8° and three reduced frequencies k 1 = 0.0183, k 2 = 0.0785 and k 3 = 0.183. This study has shown that the CFD FastS solver can satisfactorily reproduce the unsteady lift and moment coefficients experienced by a section model oscillating in stall.

Orbit of the Patroclus–Menoetius Binary System and Predictions for the 2024/2025 Mutual Events Season

We report on the ephemeris development for Menoetius, the satellite of Patroclus. Our data set consisted of ground–based and Hubble Space Telescope relative astrometry, as well as 42 lightcurves from the mutual events seasons in 2007, 2012, and 2017/2018. Our dynamical model included the effects of oblate, nonspherical shapes of the components, and we assumed that Menoetius contained ∼22% of the system’s mass. We numerically integrated the equations of motion and obtained a set of dynamical parameters that fit the data. We report the fit results in terms of residuals, state vectors, orbital elements and their 1σ uncertainties. The mean osculating semimajor axis is a = 692.5 ± 4.0 km, the mean eccentricity is e = 0.004 ± 0.004, and the International Celestial Reference Frame pole direction in R.A. and decl. is R. A. = 178.0 ± 0.5 deg, δ = −74.1 ± 0.2 deg. We determined the siderial orbital period of P = 4.282753 ± 0.000023 days. The fit yielded the system GM = 0.0950 ± 0.0012 km3 s−2, which, in combination with the system volume determined from the stellar occultation and the assumed volume uncertainty of 20%, suggests a system bulk density of 1.05 ± 0.21 g cm−3(1σ). The next season of mutual events starts in February of 2024 and lasts until January of 2025. The Patroclus system is in opposition for the observers on Earth in late September and is suitable for observations of the mutual events with an edge-on geometry in October.

БАЗОВЫЕ ХАРАКТЕРИСТИКИ МОРСКОГО ПОРТА В НАЦИОНАЛЬНОЙ ЛОГИСТИЧЕСКОЙ СИСТЕМЕ

transshipment and clearance of goods should become transparent and predictable. At the stage of conclusion of
 the contract, the client should be informed about basic characteristics of seaport and the situation at the terminal
 at the time of arrival of the client cargo shipment. It is necessary to determine the basic parameters of the cargo
 terminal, which must be transmitted to the national logistic system, as well as a set of dynamic parameters that
 affect the creation of a forecast for the terminal's workload

OPTIMIZED ADAPTIVE LOAD BALANCING METHOD IN SDN NETWORKS USING THE ADAPTIVE ANT COLONY APPROACH

In modern software-defined networks, providing efficient load balancing is a crucial task for optimal resource utilization and ensuring stable quality of service. To achieve these goals, in this paper, we propose a new innovative load- balancing method for SDN networks based on an anticolonial approach with dynamic parameter settings. This proposed method demonstrates high efficiency in the face of variable network dynamics and diverse node loads. Its main advantage is the ability to adapt to changing load and traffic conditions in real-time. The algorithm continuously analyses the load on the nodes and dynamically adjusts the weighting factors to ensure optimal traffic distribution. The proposed method stands out due to its ability to effectively maintain load balance under a variety of calls and loads, making it a powerful tool for ensuring reliability and performance in networks.

A digital twin-based multi-objective optimization method for technical schemes in process industry

ABSTRACT To solve problems of technical objective conflicts, untimely feedback, and inaccurate decision making, a multi-objective optimization method was developed for technical schemes in process industry based on digital twin. According to actual requirements, a multi-objective optimization problem was established with key technical parameters and constraints determined. A digital twin model was built to achieve a real-time interaction between physical and virtual production systems and assist in optimization. For optimization efficiency and adaptability to different working conditions, a dynamic acquisition function-based Bayesian method was adopted to fit original complicated functions and obtain Pareto optimal solutions. A rapid decision-making was carried out by comprehensively utilizing dynamic parameter set correlation evaluation, entropy weight method, and technique for order preference by similarity to ideal solution. A typical case study of optical fiber preform drawing process was presented to prove the method effectiveness. Results demonstrated that the proposed method was valuable for actual application with better product quality (an improvement by 0.71% for preform rod diameter precision control), higher utilization rate of raw materials (an increase by 3.64%), and lower total energy consumption (a reduction by 4.37%).

Aircraft conceptual design using metaheuristic-based reliability optimisation

The reliability optimisation methodology is developed to solve a conceptual design problem of a fixed-wing Unmanned Aerial Vehicle (UAV). The reliability quantification is based on the most probable point (MPP) concept, leading to a double-loop optimisation problem. The design problem is formulated as an outer-loop multiobjective optimisation for the main design problem and an inner-loop optimisation for estimating a reliability index (β) of a design solution. The goal of the outer-loop optimisation is to minimise the aircraft take-off weight, and simultaneously maximise β. The aerodynamic and stability properties of an aircraft solution are calculated by a vortex lattice method (VLM), while various types of empirical weight methods are obtained. The design problem is set up to have uncertainties in calculating aircraft empty weight and aerodynamic coefficients and derivatives. For the inner loop optimisation, the MPP is used for approximating the reliability index and probability of failure (pf). Multiobjective Meta-heuristic with Iterative Parameter Distribution Estimation (MMIPDE) and Success-History based Adaptive Differential Evolution (SHADE) are used for solving the outer- and inner-loop optimisations respectively. Four parameters setting strategies for running metaheuristics are proposed for use with the proposed metaheuristic-based reliability optimisation. The comparative results reveal that the best dynamic parameter setting from this study can reduce runtime by 22.5% compared to the traditional metaheuristic run while maintaining competitive results.

Optimization design method of upper limb exoskeleton cam mechanism’s motion trajectory model

In order to solve the problem caused by the coupling clearance of the upper-limb cam mechanism, based on cam entity structure’s data and motion trajectory characteristics, with the cam axle acceleration αc and the output torque accuracy σT as the optimization targets, a mathematical model of cam mechanism is established in the study. Cam mechanisms was established with the radial basis function (RBF) method to restore the physical model of upper-limb exoskeleton’s motion trajectory model accurately. Then, global optimization was performed with adaptive non-dominated sorting genetic algorithm-II (NSGA-II) to get αc and σT s’ Pareto solution sets and form a data mapping cam mechanism with the dynamic feedback between the motion trajectory model and the entity model. In the verification experiments, the motion trajectory model established with only 37 response points only required a low amount of computation, and the response point verification error was within 3%, indicating the high restoration accuracy. After physical parameters were optimized with NSGA-II, the optimal pareto solution sets of dynamic characteristic parameters of the cam mechanism were obtained. αc and σT were respectively decreased by 52% and 81%. The deviation of αc between the entity model test data and simulation data was 3.84°/s2 and σT was 30.23 N·mm, indicating that cam motion deviation could be adjusted by dynamic data feedback. This study verifies that the dynamic characteristics of the cam mechanism can be optimized by optimizing the material parameters of the rollers, thereby improving the performance of the upper limb exoskeleton.

An Optimum Weighted Energy Efficiency Approach for Low Complexity Power Allocation in Downlink NOMA

Non-orthogonal multiple access (NOMA) has emerged as a significant technique for 5G wireless networks because it increases device connectivity, spectral efficiency, and energy efficiency. The advantages of the NOMA system rely on the employed resource allocation schemes, which include power allocation (PA) and subcarrier user assignment (SUA). Therefore, this paper concentrates on suggesting a PA approach called a weighted energy efficiency power allocation (WEE-PA) approach to maximize the total weighted energy efficiency (WEE) in the NOMA system. Also, the proposed WEE-PA approach boosts the fairness between users, the minimum user rate in the system, the outage probability, and the average data rate per weak user. Therefore, the PA optimization problem defines as an optimization problem with a total power constraint and a set of dynamic PA parameters to maximize the WEE and ensure user fairness. The original optimization problem separates into two sub-problems, and an iterative approach is employed to solve these two sub-problems alternatingly and reduce the computational complexity. Since the optimization problem is non-convex, the sequential quadratic programming (SQP) technique is applied to resolve it and find the corresponding optimal solution. Our simulations confirm that using our proposed WEE-PA algorithm to allocate mutual resources furnishes better results than existing PA schemes.

Stochastic identification of minimum set of dynamics parameters that has small sensitivity on controlled velocity field in state-space

Stochastic identification of minimum set of dynamics parameters that has small sensitivity on controlled velocity field in state-space

The Stand For Fin Drives Energy Testing

The development of recreational diving and the new biomimetic vehicles for civilian and military purposes indicates that fins drives’ effectiveness should be a standard research procedure. The different sizes, construction and technical solutions of fin thrusters are the reason that no standard has been introduced for evaluating their efficiency. The paper presents an episode of the research carried out as part of a project financed by The National Centre for Research and Development in Poland concerning fin drives development. The first chapter presents a literature analysis of currently used research methods. A different approach to assessing efficiency was indicated, ranging from the study of the diver’s respiratory efficiency to the manipulator measurement methods. The hydrodynamic parameters, which analyzed the propellers, including fins, and the fish swimming motility characteristics, were indicated. The next chapter presents the water tunnel for basic research with measuring equipment and the range of applications. The methodology for assessing the hydrodynamic and energy efficiency of fin’s drives is presented in the third chapter. The fins’ kinematics and dynamics analysis indicated an initial set of geometric, kinematic, and dynamic parameters for energy and functional assessment purposes. The scope of available tests covered issues complex to quantify unambiguously; hence the obtained results were initial. The form made this assessment of successive pool tests, the aim of which was to analyze the kinematics of the fin’s operation. The trials of a representative fins thruster and the comments indicate the test stand’s practical use for testing various propellers.

MO568STATIC PARAMETERS OF HISTOMORPHOMETRY FOR THE EVALUATION OF BONE TURNOVER IN RENAL OSTEODYSTROPHY

Abstract Background and Aims A full histomorphometric analysis of a transiliac bone biopsy with prior tetracycline labeling remains the gold standard to diagnose renal osteodystrophy. Bone turnover is primarly evaluated by the dynamic parameter bone formation rate, calculated from the incorporation of tetracycline in bone. In cases of failed tetracycline labels, however, an evaluation of bone turnover based on static parameters is warranted. This study investigates the diagnostic accuracy of static histomorphometric parameters for the diagnosis of high and low bone turnover. Method Bone biopsies with prior tetracycline labeling of sufficient quality for a full histomorpometric analysis were included (n = 205). Mean age of participants was 56±13 years, 67% were men, and 22% had diabetes mellitus. Diagnostic accuracy of static histomorphometric parameters for bone turnover was evaluated by area under the receiver operator characteristics curve (AUC) statistics, against the full set of static and dynamic histomorphometric parameters. The cohort was randomly split to allow calculation of optimal diagnostic cutoffs in an exploration cohort (n=105), with subsequent validation in a separate subset of patients (n=100). Results All histomorphometric parameters were significantly different across categories of low (24%), normal (60%), and high (16%) bone turnover (p < 0.01), and all were significant predictors of both high and low bone turnover (Figure 1). Calculated optimal cutoffs and their sensitivities and specificities in the validation cohort are shown in Table 1. Diagnostic accuracy was very good for high turnover, as the combination of presence of fibrosis with ObPm>5.4%, OcPm>1.5%, and OAr>2.4% provided a correct diagnosis in 94% of patients, with positive (PPV) and negative (NPV) predictive values of 80% and 96%, respectively. Using the same predefined combination, an accuracy of 80% was achieved for low turnover (no fibrosis, ObPm≤1.9% OcPm≤0.9% and OAr≤1.6%), with a PPV of 71% and a NPV of 82%. Conclusion Static histomorphometric parameters provide an acceptable alternative for the diagnosis of high and low bone turnover. In the absence of successful tetracycline labeling, the proposed cutoffs may provide a suitable alternative for the evaluation of bone turnover in renal osteodystrophy.

Robust Estimation for an Extended Dynamic Parameter Set of Serial Manipulators and Unmodeled Dynamics Compensation

Advanced robotic applications have revived interest in identification of a high-precision dynamic model. In this article, we propose an extended dynamic parameter set (EDS). The EDS breaks through the limitation that the base dynamic parameter set needs <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a priori</i> knowledge of the gravity direction for modeling. Moreover, we present a novel parameters identification technique (RSIH), which is a complete solution and can significantly mitigate negative effects of the measurement noise and outliers. Besides, an incremental learning technique combined with a compensation limit criterion is employed to compensate for unmodeled dynamics. Simulations and experiments demonstrate the EDS-based model can adapt to any installation angle of a base plate, and confirm the RSIH technique outperforms the widely used identification techniques in industry and is equal to or even better than the state-of-the-art physical feasibility technique in terms of identification precision and robustness. In addition, the modeling errors, especially the uncertainty of the friction model, can be greatly compensated.

Formation of the dynamic system of the test bench for transmissions at the design stage

The problem of the discrepancy between the dynamic properties of the transmission on the test bench and the transmission of production vehicle was analyzed. When the loads of a dynamic nature are reproduced on the test bench, in a number of cases, after tests, there are obtained the results that do not correspond to the results of its operation. Usually the composition and scheme of the power flow transmission, as well as the elastic-inertial parameters of the elements of the mentioned transmissions, differ significantly. The test bench for transmissions usually does not include the chassis of vehicle, suspension and a number of other components and assemblies. The test bench is also usually driven by an electric machine rather than an internal combustion engine. During operation the dynamic loading of the vehicle's transmission is influenced by the joint work of each of its units, which has a direct or indirect effect on the passage of the power flow through the transmission. In the mode of variable loads of bench tests, this loading is influenced by the joint operation of the tested transmission with the transmission units of the test bench, which have different dynamic characteristics.&#x0D; The authors proposed the method, which allows at the design stage to form a set of dynamic parameters of the stand elements in such a way that the dynamic properties of the stand transmission correspond to the dynamic properties of the transmission of a production vehicle. There was offered a method for converging the dynamic loading of transmission on the test bench and as part of a production vehicle due to the purposeful formation at the design stage of the intrinsic frequency characteristics of the test bench transmission so that they correspond to the maximum extent to the characteristics of the vehicle transmission. The varying of the values of the inertial masses and elastic connections of the transmission elements of the test benches, the spectra of their natural frequencies are formed in such a way that in shaft line on modes, when the main part of fatigue damage accumulates, a picture of torsional vibrations is similar to those observed in the transmission of a production vehicle.

On-Line Determination of Salient-Pole Hydro Generator Parameters by Neural Network Estimator Using Operating Data (PEANN)

A novel application of Artificial Neural Network (ANN) to estimate and track Hydro Generator Dynamic Parameters using online disturbance measurements is presented within this paper. The data for training ANN are obtained through off-line simulation of the generators modelled in a one-machine-infinite-bus environment using the parameters sets that are representative of practical data. The Levenberg-Marquardt algorithm has been adopted and assimilated into the back-propagation learning algorithm for training feed-forward neural networks. The inputs of ANN are organized in coordination with the results obtained from the observability analysis of synchronous generator dynamic parameters in its dynamic behaviour. A collection of 10 ANNs with similar input patterns and different outputs are developed to determine a set of dynamic parameters. The trained ANNs are employed in a real-time operational environment for estimating generator parameters using online measurements acquired during disturbance conditions. The ANNs are employed and tested to identify generator parameters using online measurements obtained during different disturbances. Simulation studies demonstrate the ability of the ANNs to accurately estimate dynamic parameters of hydro-generators. The results also show the impact of test conditions on the accuracy degree of estimation for these parameters. The optimal structure of ANNs is also determined to minimize the error in estimating each dynamic parameter.

Throwing motion design based on minimum sensitivity with respect to error covariance of robot dynamic parameters

Throwing by a powered manipulator is an effective way for wide range transportation of an object and carrying an object in unmanned environments. The main problems of throwing are (i) how far the manipulator can throw the object and (ii) the accuracy of the landing position. Focusing on (ii), this paper proposes sensitivity analysis of the landing position with respect to the error covariance of dynamic parameters. Focusing on a planar 3-DOF manipulator, (1) the minimum set of dynamic parameters is introduced and identified based on a frequency weighted method for a nonlinear system, and its error covariance is also identified. (2) The calculation algorithm for sensitivity of landing position with respect to the minimum set of dynamic parameters is proposed. (3) By considering the error covariance of identification, an optimal throwing is designed and evaluated by simulations and/or experiments. Moreover, (4) the principal of sensitivity analysis is discussed from error ellipsoid point of view, and zero error throwing is designed.

Stochastic Identification of Minimum Set of Dynamics Parameters that has Small Sensitivity for Control System

Stochastic Identification of Minimum Set of Dynamics Parameters that has Small Sensitivity for Control System

Dynamic Identification of Industrial Robot Based on Nonlinear Friction Model and LS-SOS Algorithm

This article is concerned with the identification of industrial robot dynamics parameters, and an identification method based on a nonlinear friction model and a least squares (LS) with symbiotic organisms search (SOS) algorithm is proposed. First, according to the friction characteristics of robot joints, for the nonlinear Tustin friction model, two parameters are introduced to describe the Stribeck characteristics of Coulomb friction and static friction. Then, the joint velocity trajectory that can offset the nonfriction torque during the forward and reverse rotation is designed, and friction parameters are estimated by using LS. Based on the optimal criterion constructed by Hadamard’s inequality, the excitation trajectory represented by the Fourier series is designed, and the combined inertial parameter set is estimated by using LS. Second, select the minimum inertial parameters and friction parameters (minimum dynamic parameters) as the center points to search the upper and lower bounds; design the fitness function with adjustable weights of each joint and use the SOS algorithm to estimate the minimum dynamic parameter set as a whole. Finally, a variety of parameter identification algorithms are applied to the Staubli TX-90 robot under the same excitation trajectory. The experiment results show that the root-mean-square (rms) error of the joint torque estimated by the proposed method is the smallest. By executing the verification trajectory, the experiment results show that the rms error of the joint torque is small and the correlation coefficient is close to 1, thereby verifying the effectiveness of the estimated model for different motion trajectories.

A framework for seasonal variations of hydrological model parameters: impact on model results and response to dynamic catchment characteristics

Abstract. Previous studies have shown that the seasonal dynamics of model parameters can compensate for structural defects of hydrological models and improve the accuracy and robustness of the streamflow forecast to some extent. However, some fundamental issues for improving model performance with seasonal dynamic parameters still need to be addressed. In this regard, this study is dedicated to (1) proposing a novel framework for seasonal variations of hydrological model parameters to improve model performance and (2) expanding the discussion on model results and the response of seasonal dynamic parameters to dynamic characteristics of catchments. The procedure of the framework is developed with (1) extraction of the dynamic catchment characteristics using current data-mining techniques, (2) subperiod calibration operations for seasonal dynamic parameters, considering the effects of the significant correlation between the parameters, the number of multiplying parameters, and the temporal memory in the model states in two adjacent subperiods on calibration operations, and (3) multi-metric assessment of model performance designed for various flow phases. The main finding is that (1) the proposed framework significantly improved the accuracy and robustness of the model; (2) however, there was a generally poor response of the seasonal dynamic parameter set to catchment dynamics. Namely, the dynamic changes in parameters did not follow the dynamics of catchment characteristics. Hence, we deepen the discussion on the poor response in terms of (1) the evolutionary processes of seasonal dynamic parameters optimized by global optimization, considering that the possible failure in finding the global optimum might lead to unreasonable seasonal dynamic parameter values. Moreover, a practical tool for visualizing the evolutionary processes of seasonal dynamic parameters was designed using geometry visualization techniques. (2) We also discuss the strong correlation between parameters considering that dynamic changes in one parameter might be interfered with by other parameters due to their interdependence. Consequently, the poor response of the seasonal dynamic parameter set to dynamic catchment characteristics may be attributed in part to the possible failure in finding the global optimum and strong correlation between parameters. Further analysis also revealed that even though individual parameters cannot respond well to dynamic catchment characteristics, a dynamic parameter set could carry the information extracted from dynamic catchment characteristics and improve the model performance.

Synthesis of High-Precision Missile Homing System Using Proportional Guidance Method

Modern air targets are characterized by low visibility, high maneuverability and high survivability. In addition, for some specific targets, for instance ballistic missiles, in order to defeat them the missile need tobe guided and carried out direct hit, i.e. "hit to kill". Therefore, in this paper, we present a high-precision missile homing system (MHS) using the proportional guidance method for firing at the highly maneuverable targets. Specifically, we propose a parametric optimization method for choosing a set of optimal parameters of the missile homing system for each dynamic parameter set of the missile. In addition, the paper gives the recommendations of choosing the initial conditions for the synthesis of missile homing system. In our experience, we should choose the small initial condition for synthesizing the missile homing system. Finally, the article also investigates the influence of systematic error in determining the speed, normal acceleration of missiles and the angular velocity of the line of sight of the missile and target on the accuracy of the missile homing system. We implement the proposed missile homing system and the parametric optimization method in Matlab. The experimental results illustrate that, using proposed system and the parametric optimization method, the missile can defeat the modern air targets with low visibility, high maneuverability and high survivability.