Dynamic Parameters Identification for Tong & Tong-Carrier of a Forging Manipulator

2011 ◽  
Vol 121-126 ◽  
pp. 2006-2010
Author(s):  
Ning Bo Cheng ◽  
Li Wen Guan ◽  
Li Ping Wang ◽  
Jian Han
Keyword(s):  
Dynamic Model ◽  
Relative Error ◽  
Linear Form ◽  
Least Square Method ◽  
Least Square ◽  
Dynamic Parameters ◽  
Mass Center ◽  
Simulation Results ◽  
Forging Manipulator ◽  
Center Parameter

This paper deals with the dynamic parameters of the combination of the tong, the tong-carrier and (or without) a forging (link TCF). Two linear form equations of the dynamic model of link TCF about the dynamic parameters are obtained. And then based on two linear form equations, the least square method is adopted to identify the parameters. Simulation results show that the identified dynamic parameters, mass m, moment of inertia IL and the mass center parameter b1, have a small relative error that no more than 5%.

scholarly journals Online Parameter Identification and State of Charge Estimation of Battery Based on Multitimescale Adaptive Double Kalman Filter Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Wenxian Duan ◽  
Chuanxue Song ◽  
Yuan Chen ◽  
Feng Xiao ◽  
Silun Peng ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Parameter Identification ◽  
Unscented Kalman Filter ◽  
Least Square Method ◽  
State Of Charge ◽  
Least Square ◽  
Accurate Estimation ◽  
Battery Life ◽  
Model Parameters ◽  
Simulation Results

An accurate state of charge (SOC) can provide effective judgment for the BMS, which is conducive for prolonging battery life and protecting the working state of the entire battery pack. In this study, the first-order RC battery model is used as the research object and two parameter identification methods based on the least square method (RLS) are analyzed and discussed in detail. The simulation results show that the model parameters identified under the Federal Urban Driving Schedule (HPPC) condition are not suitable for the Federal Urban Driving Schedule (FUDS) condition. The parameters of the model are not universal through the HPPC condition. A multitimescale prediction model is also proposed to estimate the SOC of the battery. That is, the extended Kalman filter (EKF) is adopted to update the model parameters and the adaptive unscented Kalman filter (AUKF) is used to predict the battery SOC. The experimental results at different temperatures show that the EKF-AUKF method is superior to other methods. The algorithm is simulated and verified under different initial SOC errors. In the whole FUDS operating condition, the RSME of the SOC is within 1%, and that of the voltage is within 0.01 V. It indicates that the proposed algorithm can obtain accurate estimation results and has strong robustness. Moreover, the simulation results after adding noise errors to the current and voltage values reveal that the algorithm can eliminate the sensor accuracy effect to a certain extent.

A parameter identification method for robot dynamic models using a balancing mechanism

Robotica ◽  
1989 ◽  
Vol 7 (4) ◽  
pp. 327-337 ◽  
Author(s):  
T. G. Lim ◽  
H. S. Cho ◽  
W. K. Chung
Keyword(s):  
Dynamic Model ◽  
Dynamic Models ◽  
Least Square ◽  
Estimation Accuracy ◽  
Model Parameters ◽  
Robot Dynamics ◽  
Dynamic Parameters ◽  
Joint Torques ◽  
Motion Data ◽  
Identification Method

SUMMARYAccurate modeling of robot dynamics is a prerequisite for the design of model-based control schemes and enhancement of the performance of the robot. The dynamic parameters associated with a pseudo-inertia matrix are often difficult to identify accurately because the inertia torques are small in comparison to gravity loadings, thus creating signal processing problem. The identification method presented in this paper utilizes a balancing mechanism which increases the estimation accuracy of the dynamic parameters. The balancing mechanism has the effect of amplifying the inertia-related torque signal by eliminating gravity loadings acting on the robot joints. A series of motion data were experimentally obtained through sequential test steps. By incorporating the measured information about joint torques, angular positions, velocities and accelerations the least square algorithm was used to identify the dynamic parameters. The estimated values were converted to those of the original robot model to obtain its dynamic model parameters. The identified robot dynamic model was shown to be accurate enough to predict the actual robot motions.

Asymmetric Prandtl-Ishlinskii Hysteresis Model for Giant Magnetostrictive Actuator

2016 ◽  
Vol 20 (2) ◽  
pp. 223-230 ◽  
Author(s):  
Zhuoyun Nie ◽  
◽  
Chanjun Fu ◽  
Ruijuan Liu ◽  
Dongsheng Guo ◽  
...  
Keyword(s):  
Linear Function ◽  
Polynomial Function ◽  
Least Square Method ◽  
Least Square ◽  
Hysteresis Model ◽  
Hysteresis Behavior ◽  
Magnetostrictive Actuator ◽  
Simulation Results

An asymmetric Prandtl–Ishlinskii (API) hysteresis model for a giant magnetostrictive actuator (GMA) is proposed in this paper. The classical Prandtl–Ishlinskii (PI) model is analyzed and divided into two parts: linear function and operator summation. To enhance model asymmetry, a polynomial function is used in the API model as the center curve of the hysteresis instead of the linear function. The remaining curve of the hysteresis is modeled by a new operator that provides some basic asymmetric hysteresis. In this manner, the proposed API model requires relatively less operators and fewer parameters to describe the asymmetric hysteresis behavior of the GMA. All parameters of the API model are identified by a standard least square method. Simulation results show that the API model is very successful in formulating an asymmetric hysteresis of the GMA. In addition, it provides better identification results compared with the classical PI model.

The Calculation of Earth Capacitance Based on Least Square Method

2012 ◽  
Vol 433-440 ◽  
pp. 6028-6032
Author(s):  
Heng Xu Ha ◽  
Xiao Liu ◽  
Xi Tong Hu
Keyword(s):  
Power System ◽  
Single Phase ◽  
Least Square Method ◽  
Least Square ◽  
Neutral System ◽  
Negative Effects ◽  
Capacitive Current ◽  
Measurement Results ◽  
Simulation Results ◽  
Capacitance Current

The grounding capacitive current is one of the most important parameters of ungrounded neutral system. Usually this parameter is obtained with the method of additional capacitor or metal grounding. However, the former is complicated and the additional capacitor has negative effects on measurement results, and the later is dangerous when used in testing. In view of that, the paper proposes a new method to calculate grounding capacitance current based on the data of single-phase-grounding faults in power system with indirectly earthed neutral. This method reduces the error by using the least-square method .The ATP simulation results show that this method is accurate basically.

System Identification of a Class of Second-Order Continuous System

2014 ◽  
Vol 651-653 ◽  
pp. 528-533 ◽  
Author(s):  
Zhi Gang Jia ◽  
Xing Xuan Wang
Keyword(s):  
Linear Equations ◽  
Continuous System ◽  
Least Square Method ◽  
Second Order ◽  
Least Square ◽  
Step Response ◽  
Order System ◽  
Simulation Results ◽  
Order Continuous ◽  
Identification Model

An identification method of a class of second-order continuous system is proposed. This method constructs a discrete-time identification model, forms a set of linear equations. The parameters can be obtained by least square method. Simulation results show that the method is effective for a class of second-order system, and is not only for step response but also for square wave signal.

Methods of Feature Weighting Calculation and Case Retrieval in CBR Case Base

2014 ◽  
Vol 490-491 ◽  
pp. 1391-1398
Author(s):  
Xiao Ping Li
Keyword(s):  
Least Squares Method ◽  
Least Square Method ◽  
High Accuracy ◽  
Typical Case ◽  
Feature Weighting ◽  
Least Square ◽  
Case Retrieval ◽  
Use Of Data ◽  
On Line ◽  
Simulation Results

This article proposes the necessity and feasibility of the use of Data Mining and Knowledge Discovery in CBR reasoning. This paper focuses on the method of empowering feature items based on least squares method parameter identification, and achieve the method of Similarity case retrieval on this basis, the object is the typical case database of railway rescue. The simulation results show that: the least square method can effectively make estimation and identification of the feature parameters, and can continuously correct on-line. High accuracy and fast convergence characteristics of the assigned parameters show that the algorithm has a certain application value.

Modeling of Pulp Washing Process Based on Two-Step BP Neural Network

2012 ◽  
Vol 198-199 ◽  
pp. 1712-1715
Author(s):  
Hua Zhong Wang ◽  
Wen Juan Shan
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Model Simulation ◽  
Least Square Method ◽  
Least Square ◽  
Washing Process ◽  
Optimization Control ◽  
Important Quality ◽  
Simulation Results ◽  
Quality Indexes

The most important quality indexes to evaluate pulp washing performance are residual soda and the Baume degree. But it is difficult to measure the two indexes directly. To solve the problem of optimization control of the washing process, the model of the residual soda and the Baume degree are studied in this paper. Simulating residual soda and the Baume degree via a two-step neural network and modeling them based on least square method and steady-state data obtained by neural network model. Simulation results show that this method can effectively locate the pulp washing process.

Substructuring: Definition of the Analytical Dynamic Model of a Complex System During its Design Stage

1995 ◽  
Author(s):  
Fabrice Llorca ◽  
Alain Gerard ◽  
Denis Hennequin ◽  
Dominique Brenot
Keyword(s):  
Dynamic Model ◽  
Degrees Of Freedom ◽  
Dynamic Properties ◽  
Least Square Method ◽  
Close Correlation ◽  
Least Square ◽  
Component Mode Synthesis ◽  
Design Stage ◽  
Synthesis Methods ◽  
Rectangular Plates

Abstract A structure is often an assembly of several components coupled by various joints such as bolted or riveted joints. Component mode synthesis methods are very practical tools to define a dynamic model. But, several points have to be examined and improved in order to give a complet representation of the modal behaviour of the whole structure. For example, rotational degrees of freedom on connecting points between adjacent substructures should be estimated to give a better representation of the multidirectional connecting forces. These informations may be evaluated through a method based on both interpolation and spatial derivation of the experimental translational displacements of the components. Unlike many other structural elements, the dynamic properties of a connection are very difficult to evaluate. So, we propose a method of determining joint stiffness characteristics. We consider only the conservative problem so the damping properties of the different components of the considered assembly are not taken into account. The joint characteristics are extracted comparing experimental modal data base and component mode synthesis simulation. The updating procedure is based on a nonlinear iterative least-square method. Results are presented concerning a particular assemblie of rectangular plates. Structural modification is applied for one component. We show that the joint properties stay the same if the connecting interface is not modified. The close correlation between predicted and experimental results demonstrate that this method is well adaptated to the study of structural modifications.

Dynamics Modeling and Identification of a Dual-Blade Wafer Handling Robot

2013 ◽  
Author(s):  
Xiaowen Yu ◽  
Cong Wang ◽  
Yu Zhao ◽  
Masayoshi Tomizuka
Keyword(s):  
Dynamic Model ◽  
Coulomb Friction ◽  
Viscous Friction ◽  
Parallel Robot ◽  
Least Square ◽  
Dynamic Parameters ◽  
Dynamics Modeling ◽  
Dynamic Identification ◽  
Least Square Regression ◽  
Reliable Model

This paper presents the dynamics modeling and dynamic identification of a dual-blade wafer handling robot. An explicit form dynamic model for this 8-link parallel robot is proposed. The dynamic model is transformed into a decoupled form to enable dynamic parameters identification with least-square regression. A well conditioned trajectory is chosen for identification experiment. Both viscous friction and Coulomb friction are considered to make the model more reliable. Model has been validated by experiments.

Research on Algorithm for Non-Cooperative Target Inertial Parameters Identification

2014 ◽  
Vol 543-547 ◽  
pp. 1550-1554
Author(s):  
Zhi Gang Chen ◽  
Ju Shu ◽  
Su Xia Zhu
Keyword(s):  
Least Square Method ◽  
High Accuracy ◽  
Least Square ◽  
New Method ◽  
Recursive Method ◽  
Recursive Least Square ◽  
Inertial Parameters ◽  
Conservation Of Momentum ◽  
Simulation Results ◽  
Recursive Least Square Method

It is of great importance to accomplish identifying the non-cooperative targets inertial parameters for capturing and controlling it. This paper adopts an identification method utilizing the tactile and vision to establish the identification equations based on the principle of conservation of momentum. In order to solve the equations precisely and rapidly, two of the most widely used methods: the least square method and the recursive least-square method (RLS) are employed for simulation and calculation utilizing ADAMS and MATLAB, and the limitation of each method is pointed out. Then the paper proposes a new method named the recursive method based on the least square solution. This method provides the identification equation a new solving thought and realizes fast identification of the targets inertial parameters at high accuracy. The simulation results verify the validity and feasibility of the proposed approach.

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