scholarly journals Theoretical Limits of Parameter Estimation Based on Quantized Data

2017 ◽  
Vol 61 (4) ◽  
pp. 312
Author(s):  
Tamás Virosztek ◽  
István Kollár
Keyword(s):  
Parameter Estimation ◽  
Transfer Characteristic ◽  
Analog Signal ◽  
Complex Signal ◽  
Measurement Technology ◽  
Ml Estimation ◽  
Analog To Digital ◽  
Signal Parameters ◽  
Band Limited ◽  
And Control

Parameter estimation of band-limited periodic signals (sine and multisine waves) is a very common task in the field of measurement technology and control engineering. In the overwhelming majority of data acquisition and control systems the analog signals of the real world are sampled an quantized using analog-to-digital converters (ADCs). To estimate the parameters of the analog signal and the parameters of the quantizer from the same measurement record is an obvious need in these cases. The parameters of the recorded signal can be used to calculate the response of our system (e.g. signals of the actuators) while the parameters of the quantizer can be used to identify the transfer characteristic of the measurement channel. Maximum likelihood (ML) estimation of the quantizer and analog signal parameters has been developed to perform this task and to provide asymptotically unbiased and efficient estimators for the quantizer and signal parameters. This paper investigates the theoretical limits of this kind of estimation: provides the Cramér-Rao Lower Bound (CRLB) for the covariance of the achieved estimators and compares them to CRLB values obtained using less complex signal and channel models. This article also provides a comparison of the empirical covariance of estimator populations achieved different ways to the CRLB of estimation. The major tendencies are drawn and explanation for them is provided as well.

scholarly journals Visceral pressure stimulator for exploring hollow organ pain: a pilot study

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Michael DeLong ◽  
Mauricio Gil-Silva ◽  
Veronica Minsu Hong ◽  
Olivia Babyok ◽  
Benedict J. Kolber
Keyword(s):  
Visceral Pain ◽  
Bladder Pressure ◽  
Abdominal Muscles ◽  
Analog To Digital ◽  
In Vivo Experiments ◽  
Digital Pressure ◽  
Hollow Organ ◽  
Specialized Hardware ◽  
And Control

Abstract Background The regulation and control of pressure stimuli is useful for many studies of pain and nociception especially those in the visceral pain field. In many in vivo experiments, distinct air and liquid stimuli at varying pressures are delivered to hollow organs such as the bladder, vagina, and colon. These stimuli are coupled with behavioral, molecular, or physiological read-outs of the response to the stimulus. Care must be taken to deliver precise timed stimuli during experimentation. For example, stimuli signals can be used online to precisely time-lock the stimulus with a physiological output. Such precision requires the development of specialized hardware to control the stimulus (e.g., air) while providing a precise read-out of pressure and stimulus signal markers. Methods In this study, we designed a timed pressure regulator [termed visceral pressure stimulator (VPS)] to control air flow, measure pressure (in mmHg), and send stimuli markers to online software. The device was built using a simple circuit and primarily off-the-shelf parts. A separate custom inline analog-to-digital pressure converter was used to validate the real pressure output of the VPS. Results Using commercial physiological software (Spike2, CED), we were able to measure mouse bladder pressure continuously during delivery of unique air stimulus trials in a mouse while simultaneously recording an electromyogram (EMG) of the overlying abdominal muscles. Conclusions This device will be useful for those who need to (1) deliver distinct pressure stimuli while (2) measuring the pressure in real-time and (3) monitoring stimulus on–off using physiological software.

Parameter Normalization in Multibody Dynamics

2008 ◽  
Author(s):  
Saeed Ebrahimi ◽  
Jo´zsef Ko¨vecses
Keyword(s):  
Parameter Estimation ◽  
Multibody Dynamics ◽  
Eigenvalue Problems ◽  
Physical Structure ◽  
Control Problems ◽  
Inertial Parameters ◽  
Parametric Studies ◽  
Novel Concept ◽  
And Control

In this paper, we introduce a novel concept for parametric studies in multibody dynamics. This is based on a technique that makes it possible to perform a natural normalization of the dynamics in terms of inertial parameters. This normalization technique rises out from the underlying physical structure of the system, which is mathematically expressed in the form of eigenvalue problems. It leads to the introduction of the concept of dimensionless inertial parameters. This, in turn, makes the decomposition of the array of parameters possible for studying design and control problems where parameter estimation and sensitivity is of importance.

ERRORS CONVERSION ON TRANSFER FUNCTIONS OF MEASUREMENT AND CONTROL

2021 ◽  
Vol 4 ◽  
pp. 92-104
Author(s):  
Valentin Bahatskyi ◽  
◽  
Aleksey Bahatskyi ◽  
Keyword(s):  
Transfer Functions ◽  
Systematic Errors ◽  
Step Function ◽  
Control Device ◽  
Point Of View ◽  
Correct Operation ◽  
Analog To Digital ◽  
Analog To Digital Conversion ◽  
And Control ◽  
Measurement And Control

Currently, the measurement of electrical and non-electrical quantities is performed using analog-to-digital conversion channels, which consist of analog signal conditioning circuits and analog-to-digital converters (ADC) of electrical quantities into a digital code. The paper considers the case when the defining errors of the measurement and control channel are systematic errors of the ADC. The reliability of measurements is assessed by their errors, and the reliability of control - by the likelihood of correct operation of the control device. In our opinion, evaluating the reliability of such similar processes as measurement and control using different criteria seems illogical. The aim of the work is to study the effect of systematic errors of an analog-to-digital converter on the errors of parameter control depending on the type of conformity functions and the width of the control window, as well as the choice of the resolution of the ADC for various control tasks. The paper analyzes the transfer functions of measurement and control. It is shown that they are formed using step functions. It is proposed to use not a step function as a control transfer function, but other functions of conformity to the norm, for example, a linear function or functions of higher orders. In this case, the control result is assessed not according to the criterion of the probability of correct operation, but using the control error. Analyzed from the point of view of reconfiguring the errors of the line, parabolic and state parabolic functions of the norms for the development of changes windows in control. A recommendation has been given for the selection of functions for the conformity of standards and for the distribution of analog-to-digital conversions for industrial control enterprises.

Invariants of Chaotic Attractor in a Nonlinearly Damped System

1998 ◽  
Vol 65 (4) ◽  
pp. 875-879 ◽  
Author(s):  
B. Ravindra ◽  
P. Hagedorn
Keyword(s):  
Power Law ◽  
Chaotic Attractor ◽  
Correlation Dimension ◽  
Ml Estimation ◽  
State Space Reconstruction ◽  
Damped System ◽  
Building Models ◽  
Prediction And Control ◽  
And Control

The characterization of a chaotic attractor in a driven, Duffing-Holmes oscillator with power-law damping is considered. State space reconstruction of the time series of the attractor is carried out to investigate its structure. The invariants associated with the attractor such as correlation dimension and entropy are computed. Also the maximum-likelihood (ML) estimation of dimension and entropy are carried out. The use of obtained invariants in building models for prediction and control using power-law dampers is discussed.

On-Line Chatter Detection Using Wavelet-Based Parameter Estimation

2000 ◽  
Author(s):  
Taejun Choi ◽  
Yung C. Shin
Keyword(s):  
Parameter Estimation ◽  
Estimation Algorithm ◽  
Cutting Process ◽  
High Dimensional ◽  
Detection Accuracy ◽  
Chatter Detection ◽  
Ml Estimation ◽  
On Line ◽  
Low Dimensional ◽  
Low Dimensional Dynamics

Abstract A new method for on-line chatter detection is presented. The proposed method characterizes the significant transition from high dimensional to low dimensional dynamics in the cutting process at the onset of chatter. Based on the likeness of the cutting process to the nearly-1/f process, this wavelet-based maximum likelihood (ML) estimation algorithm is applied for on-line chatter detection. The presented chatter detection index γ is independent of the cutting conditions and gives excellent detection accuracy and permissible computational efficiency, which makes it suitable for on-line implementation. The validity of the proposed method is demonstrated through the tests with extensive actual data obtained from turning and milling processes.

Genetic Algorithm-Based Maximum Likelihood Parameter Estimation for Transit Buses

2001 ◽  
Author(s):  
Jie Xiao ◽  
Bohdan T. Kulakowski
Keyword(s):  
Parameter Estimation ◽  
Maximum Likelihood ◽  
Dynamic Models ◽  
Estimation Method ◽  
Optimization Techniques ◽  
Model Parameters ◽  
Parameter Estimation Method ◽  
Transit Buses ◽  
Simulation And Control ◽  
And Control

Abstract Vehicle dynamic models include parameters that qualify the dependence of input forces and moments on state and control variables. The accuracy of the model parameter estimates is important for modeling, simulation, and control. In general, the most accurate method for determining values of model parameters is by direct measurement. However, some parameters of vehicle dynamics, such as suspension damping or moments of inertia, are difficult to measure accurately. This study aims at establishing an efficient and accurate parameter estimation method for developing dynamic models for transit buses, such that this method can be easily implemented for simulation and control design purposes. Based on the analysis of robustness, as well as accuracy and efficiency of optimization techniques, a parameter estimation method that integrates Genetic Algorithms and the Maximum Likelihood Estimation is proposed. Choices of output signals and estimation criterion are discussed involving an extensive sensitivity analysis of the predicted output with respect to model parameters. Other experiment-related aspects, such as imperfection of data acquisition, are also considered. Finally, asymptotic Cramer-Rao lower bounds for the covariance of estimated parameters are obtained. Computer simulation results show that the proposed method is superior to gradient-based methods in accuracy, as well as robustness to the initial guesses and measurement uncertainty.

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