Adaptive Mismatch Compensation for Rate Integrating Vibratory Gyroscopes With Improved Convergence Rate

2014 ◽  
Author(s):  
Fu Zhang ◽  
Ehsan Keikha ◽  
Behrooz Shahsavari ◽  
Roberto Horowitz
Keyword(s):  
Convergence Rate ◽  
Degrees Of Freedom ◽  
Rotation Angle ◽  
Least Square ◽  
Parameter Estimates ◽  
Unknown Parameters ◽  
Least Square Estimator ◽  
Vibratory Gyroscopes ◽  
Adaptive Compensator ◽  
Simulation Results

This paper presents an online adaptive algorithm to compensate damping and stiffness frequency mismatches in rate integrating Coriolis Vibratory Gyroscopes (CVGs). The proposed adaptive compensator consists of a least square estimator that estimates the damping and frequency mismatches, and an online compensator that corrects the mismatches. In order to improve the adaptive compensator’s convergence rate, we introduce a calibration phase where we identify relations between the unknown parameters (i.e. mismatches, rotation rate and rotation angle). Calibration results show that the unknown parameters lie on a hyperplane. When the gyro is in operation, we project parameters estimated from the least square estimator onto the hyperplane. The projection will reduce the degrees of freedom in parameter estimates, thus guaranteeing persistence of excitation and improving convergence rate. Simulation results show that utilization of the projection method will drastically improve convergence rate of the least square estimator and improve gyro performance.

scholarly journals Modified Robust Ridge M-Estimators in Two-Parameter Ridge Regression Model

2021 ◽  
Vol 2021 ◽  
pp. 1-24
Author(s):  
Seyab Yasin ◽  
Sultan Salem ◽  
Hamdi Ayed ◽  
Shahid Kamal ◽  
Muhammad Suhail ◽  
...  
Keyword(s):  
Ridge Regression ◽  
Mean Squared Error ◽  
Least Square ◽  
Ridge Estimator ◽  
Least Square Estimator ◽  
Squared Error ◽  
Joint Problem ◽  
Ridge Regression Estimator ◽  
Simulation Results ◽  
Two Parameter

The methods of two-parameter ridge and ordinary ridge regression are very sensitive to the presence of the joint problem of multicollinearity and outliers in the y-direction. To overcome this problem, modified robust ridge M-estimators are proposed. The new estimators are then compared with the existing ones by means of extensive Monte Carlo simulations. According to mean squared error (MSE) criterion, the new estimators outperform the least square estimator, ridge regression estimator, and two-parameter ridge estimator in many considered scenarios. Two numerical examples are also presented to illustrate the simulation results.

Time-varying threshold cointegration with an application to the Fisher hypothesis

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Lixiong Yang
Keyword(s):  
Convergence Rate ◽  
Threshold Effect ◽  
Least Square ◽  
Time Varying ◽  
Threshold Cointegration ◽  
Test Statistics ◽  
Least Square Estimator ◽  
Proposed Model ◽  
Fisher Hypothesis ◽  
The Us

Abstract This paper extends the threshold cointegration model developed by Gonzalo, J., and J. Y. Pitarakis. 2006. “Threshold Effects in Cointegrating Relationships.” Oxford Bulletin of Economics & Statistics 68: 813–33 and Chen, H. 2015. “Robust Estimation and Inference for Threshold Models with Integrated Regressors.” Econometric Theory 31 (4): 778–810 to allow for a time-varying threshold, which is a function of candidate variables that affect the separation of regimes. We derive the asymptotic distribution of the proposed least-square estimator of the threshold, and study the convergence rate of the threshold estimator. We also suggest test statistics for threshold effect and threshold constancy. Monte Carlo simulations point out that the convergence rate of the threshold estimator is consistent with the asymptotic theory, and the proposed tests have good size and power properties. The empirical usefulness of the proposed model is illustrated by an application to the US data to investigate the Fisher hypothesis.

One step ahead adaptive control technique featured by fuzzy-based least square estimator for wind systems

2021 ◽  
pp. 0309524X2110107
Author(s):  
Lorenzo Dambrosio
Keyword(s):  
Convergence Rate ◽  
Synchronous Generator ◽  
Least Square ◽  
Control Technique ◽  
Estimation Accuracy ◽  
Wind System ◽  
Horizontal Axis Wind Turbine ◽  
Least Square Estimator ◽  
One Step ◽  
The One

The present paper proposes the application to a wind system of the One Step Ahead control scheme featured by a Fuzzy-based Least Square Estimator. The considered wind system power generation supplies an electrical load disconnected from the power supply grid. It is composed of a three bladed horizontal-axis wind turbine which drives a synchronous generator by means of gearbox: the mathematical model for both the horizontal-axis wind-turbine and the synchronous generator will be briefly outlined. The adaptive nature of the One-Step-Ahead control algorithm relies on providing consistent estimation of the controlled system. This is achieved by means of a Least Square Algorithm that is able to provide a good estimation of a linear discrete time model of the controlled system, nevertheless its convergence rate reduces very quickly. For this reason, Least Square Algorithm needs a resetting strategy, which allows the achievement of a compromise between estimation accuracy and convergence rate. This not only represents a very problem-dependent issue but also introduces weaknesses in term of control tracking errors, which in turns needs an extra control contribution (integral correction). The proposed Least Square Algorithm enhancement overcomes these issues managing differently the estimation accuracy and the convergence rate. In the Results section, the achievements of the application of the One-Step-Ahead algorithm to the wind system will prove the reliability of the suggested enhanced control technique.

Parameters Identification Strategy for a Generalized Vehicle Concept Model for Ride and Handling Analysis

2013 ◽  
Author(s):  
Mariano Carpinelli ◽  
Marco Gubitosa ◽  
Domenico Mundo ◽  
Wim Desmet
Keyword(s):  
Degrees Of Freedom ◽  
Early Stage ◽  
Parameters Identification ◽  
Least Square ◽  
Identification Algorithm ◽  
Vehicle Concept ◽  
Unknown Parameters ◽  
Multibody Model ◽  
Concept Model ◽  
Predecessor Model

In this paper we propose a structured approach for the parameters identification of a multibody vehicle concept model to be used for the combined analysis of vertical and longitudinal dynamics. The model here proposed adopts eight degrees of freedom in the space. The wheels are connected to the sprung mass in an equivalent trailing arm configuration thus enabling to reproduce the squat and dive phenomena. This conceptual suspension representation allows determining the dynamic response of the vehicle during longitudinal acceleration or braking maneuvers. The identification procedure here suggested evaluates the unknown parameters of the model, being the global stiffness and damping coefficients of the suspensions and the positions of the pivot points of the trailing arms. The identification algorithm is based on non-linear least square costs that can be computed by having as reference the signals of a measurement campaign which is conducted on a real vehicle as well as on a virtual predecessor model. The results here shown make use of virtually measured quantities coming from ride maneuvers performed by means of a high fidelity multibody model of a passenger car. The presented concept model, showing good correlation with respect to the reference signals, is suggested as a reliable prediction and optimization tool in the early stage of the design phase of new vehicles.

scholarly journals Software Sensor to Enhance Online Parametric Identification for Nonlinear Closed-Loop Systems for Robotic Applications

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3653
Author(s):  
Lilia Sidhom ◽  
Ines Chihi ◽  
Ernest Nlandu Kamavuako
Keyword(s):  
Degrees Of Freedom ◽  
Closed Loop ◽  
Sliding Mode ◽  
Robot Manipulator ◽  
Parametric Identification ◽  
Recursive Least Squares ◽  
Unknown Parameters ◽  
Closed Loop Identification ◽  
Input Variables ◽  
Robotic Applications

This paper proposes an online direct closed-loop identification method based on a new dynamic sliding mode technique for robotic applications. The estimated parameters are obtained by minimizing the prediction error with respect to the vector of unknown parameters. The estimation step requires knowledge of the actual input and output of the system, as well as the successive estimate of the output derivatives. Therefore, a special robust differentiator based on higher-order sliding modes with a dynamic gain is defined. A proof of convergence is given for the robust differentiator. The dynamic parameters are estimated using the recursive least squares algorithm by the solution of a system model that is obtained from sampled positions along the closed-loop trajectory. An experimental validation is given for a 2 Degrees Of Freedom (2-DOF) robot manipulator, where direct and cross-validations are carried out. A comparative analysis is detailed to evaluate the algorithm’s effectiveness and reliability. Its performance is demonstrated by a better-quality torque prediction compared to other differentiators recently proposed in the literature. The experimental results highlight that the differentiator design strongly influences the online parametric identification and, thus, the prediction of system input variables.

Some observations on fitting assumed diameter distributions to horizontal point sampling data

2000 ◽  
Vol 30 (4) ◽  
pp. 521-533 ◽  
Author(s):  
Jeffrey H Gove
Keyword(s):  
Diameter Distribution ◽  
Parameter Estimates ◽  
Sample Point ◽  
Underlying Distribution ◽  
Weighted Distribution ◽  
Reliable Parameter ◽  
Simulation Results ◽  
Larger Sample ◽  
Horizontal Point Sampling ◽  
Diameter Distributions

This paper revisits the link between assumed diameter distributions arising from horizontal point samples and their unbiased stand-based representation through weighted distribution theory. Examples are presented, which show that the assumption of a common shared parameter set between these two distributional forms, while theoretically valid, may not be reasonable in many operational cases. Simulation results are presented, which relate the conformity (or lack thereof) in these estimates to sampling intensity per point and the underlying shape of the population diameter distribution from which the sample point was drawn. In general, larger sample sizes per point are required to yield reliable parameter estimates than are generally taken for inventory purposes. In addition, a complimentary finding suggests that the more positively skewed the underlying distribution, the more trees per point are required for good parameter estimates.

Dynamic Modeling of a High-Dynamic Flight Simulator

2014 ◽  
Vol 687-691 ◽  
pp. 610-615 ◽  
Author(s):  
Hui Liu ◽  
Li Wen Guan
Keyword(s):  
Dynamic Modeling ◽  
Degrees Of Freedom ◽  
Flight Simulator ◽  
Inverse Dynamic ◽  
Dynamic Formulation ◽  
Time Histories ◽  
Rotational Degrees Of Freedom ◽  
High Dynamic ◽  
Euler Approach ◽  
Simulation Results

High-dynamic flight simulator (HDFS), using a centrifuge as its motion base, is a machine utilized for simulating the acceleration environment associated with modern advanced tactical aircrafts. This paper models the HDFS as a robotic system with three rotational degrees of freedom. The forward and inverse dynamic formulations are carried out by the recursive Newton-Euler approach. The driving torques acting on the joints are determined on the basis of the inverse dynamic formulation. The formulation has been implemented in two numerical simulation examples, which are used for calculating the maximum torques of actuators and simulating the time-histories of kinematic and dynamic parameters of pure trapezoid Gz-load command profiles, respectively. The simulation results can be applied to the design of the control system. The dynamic modeling approach presented in this paper can also be generalized to some similar devices.

scholarly journals Strategies of traversing obstacles and the simulation for a forestry chassis

2018 ◽  
Vol 15 (3) ◽  
pp. 172988141877390 ◽  
Author(s):  
Yue Zhu ◽  
Jiangming Kan ◽  
Wenbin Li ◽  
Feng Kang
Keyword(s):  
Multibody Dynamics ◽  
Inclination Angle ◽  
Degrees Of Freedom ◽  
Ride Comfort ◽  
Hydraulic Cylinder ◽  
Single Side ◽  
Simulation Results ◽  
Maximum Inclination ◽  
Three Degrees Of Freedom ◽  
Small Inclination

As to the complicated terrain in forest, forestry chassis with an articulated body with three degrees of freedom and installed luffing wheel-legs (FC-3DOF&LW) is a novel chassis that can surmount obstacles. In addition, the rear frame of FC-3DOF&LW is regarded as the platform to carry equipment. Small inclination angle for rear frame contributes to stability and ride comfort. This article describes the strategy of traversing obstacles and simulation for FC-3DOF&LW that drives in forest terrain. First, key structures of FC-3DOF&LW are briefly introduced, which include articulated structure with three degrees of freedom and luffing wheel-leg. Based on the sketch of luffing wheel-leg, the movement range of luffing wheel-leg is obtained by hydraulic cylinder operation. Second, the strategy of crossing obstacles that are simplified three models of terrain is presented, and the simulation for surmounting obstacles is constructed in multibody dynamics software. The simulation results demonstrate that the inclination angle of rear frame is 18° when slope is 30°. A maximum 12° decrease of inclination angle for rear frame can be acquired when luffing wheel-legs are applied. For traversing obstacles with both sides, the maximum inclination angle of rear frame is about 1.2° and is only 3° for traversing obstacles with single side.

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