ALGORITHMIC METHOD OF AUTONOMOUS CORRECTION MEASUREMENT ERRORS IN SYSTEMS AUTOMATIC CONTROL AND REGULATION

2021 ◽  
pp. 3-10
Author(s):  
I. S. Kikin
Keyword(s):  
Automatic Control ◽  
Measurement Errors ◽  
Observation Interval ◽  
Estimation Method ◽  
Control Process ◽  
Estimation Algorithm ◽  
A Posteriori ◽  
Sources Of Information ◽  
Control Target ◽  
Posteriori Estimation

A method of autonomous a posteriori estimation of control target’s state coordinates is demonstrated. The method’s accuracy does not depend on automatic control system sensors errors. An algorithmic implementation of the method is proposed – an algorithm for processing the array of data on the control target observed inputs and outputs, obtained by passive information accumulation during the observation interval of the control target normal functioning. At the final stage of the estimation algorithm, the implemented control process is simulated with complete a priori information about the conditions for its implementation (simulation estimation method). The algorithm execution time should be negligible in relation to the duration of the observation interval (instantaneous a posteriori estimation of the control target’s state). The proposed method allows to cyclically correct instrumental errors of automatic control and regulation systems without using external sources of information.

AUTONOMOUS CORRECTION OF A SINGLE-CHANNEL INERTIAL CONTROL SYSTEM

2020 ◽  
pp. 3-12
Author(s):  
I. S. Kikin
Keyword(s):  
Control System ◽  
Measurement Errors ◽  
Single Channel ◽  
Observation Interval ◽  
Operating Conditions ◽  
Sources Of Information ◽  
Disturbing Force ◽  
External Sources ◽  
Inertial Control ◽  
Posteriori Estimation

The problem of algorithmic design of the system of inertial control of a moving object is considered, in which the compensation of number errors caused by errors of accelerometers without external sources of information about the navigation elements of the object is carried out. The principle of solving the problem is demonstrated on the model of a single-channel positional inertial control system. Algorithms of instantaneous a posteriori estimation of calculated variables are investigated, which allow to obtain estimates that are invariant to measurement errors, and to correct the inertial control channel without an external positioning system. For the operating conditions of the system, under which the values of measurement errors and the disturbing force are represented by random numbers that preserve constant values over the observation interval, estimates of the calculated variables corresponding to almost complete compensation of the calculation errors are obtained.

Maximum a posteriori estimation method for aorta localization and coronary seed identification

2017 ◽  
Vol 68 ◽  
pp. 222-232 ◽  
Author(s):  
Byunghwan Jeon ◽  
Yoonmi Hong ◽  
Dongjin Han ◽  
Yeonggul Jang ◽  
Sunghee Jung ◽  
...  
Keyword(s):  
Estimation Method ◽  
Maximum A Posteriori ◽  
A Posteriori ◽  
Maximum A Posteriori Estimation ◽  
Seed Identification ◽  
Posteriori Estimation

scholarly journals Bayesian Analysis of Mixtures of Factor Analyzers

2001 ◽  
Vol 13 (5) ◽  
pp. 993-1002 ◽  
Author(s):  
Akio Utsugi ◽  
Toru Kumagai
Keyword(s):  
Bayesian Inference ◽  
Bayesian Analysis ◽  
Gibbs Sampler ◽  
Simulation Experiment ◽  
Estimation Algorithm ◽  
Deterministic Algorithm ◽  
Maximum A Posteriori ◽  
A Posteriori ◽  
Conjugate Priors ◽  
Posteriori Estimation

For Bayesian inference on the mixture of factor analyzers, natural conjugate priors on the parameters are introduced, and then a Gibbs sampler that generates parameter samples following the posterior is constructed. In addition, a deterministic estimation algorithm is derived by taking modes instead of samples from the conditional posteriors used in the Gibbs sampler. This is regarded as a maximum a posteriori estimation algorithm with hyperparameter search. The behaviors of the Gibbs sampler and the deterministic algorithm are compared on a simulation experiment.

Dynamic Prediction of Individual Customer’s Purchase Behavior

2013 ◽  
Vol 850-851 ◽  
pp. 998-1002
Author(s):  
Lei Guo ◽  
An An Hu ◽  
Er Wa Qin
Keyword(s):  
Prediction Accuracy ◽  
Estimation Method ◽  
Bayes Theorem ◽  
Static Model ◽  
Operating Costs ◽  
Purchase Behavior ◽  
A Posteriori ◽  
Dynamic Prediction ◽  
Current Events ◽  
Posteriori Estimation

Each customer has specific purchase regularity. To predict the customers purchase behavior, some researchers have built a static model which not considere the environmental change and the customers characteristics. To dynamically predict customer purchase behavior, this paper introduces a posteriori estimation method. Based on the customers purchased information, the method combine with the customers current events, then applies the Bayes theorem to posteriori estimate the customers purchase behavior. The new method not only predict individual customers purchase behavior, but also improve the prediction accuracy. It will be helpful for the enterprises to optimize arrangements for the production and inventory and reduce operating costs.

scholarly journals ADAPTIVE GUARANTEED ESTIMATION OF A CONSTANT SIGNAL UNDER UNCERTAINTY OF MEASUREMENT ERRORS

2020 ◽  
Vol 20 (4) ◽  
pp. 22-36
Author(s):  
D.V. Khadanovich ◽  
◽  
V.I. Shiryaev ◽  
Keyword(s):  
Adaptive Algorithm ◽  
Measurement Errors ◽  
Observation Interval ◽  
A Priori ◽  
Estimation Algorithm ◽  
Time Interval ◽  
Short Time Interval ◽  
Residual Variance ◽  
Admissible Sets ◽  
Guaranteed Estimation

In the guaranteed estimation problems under uncertainty relative to disturbances and meas-urement errors, the admissible sets of their possible values are determined. The solution is chosen due to conditions of guaranteed bounded estimates optimization corresponding to the worst realiza-tion of disturbances and measurement errors. The result of the guaranteed estimation is an unim-provable bounded estimate (information set), which turns to be overly pessimistic (reinsurance) if a prior admissible set of measurement errors is too large compared to their realized values. The admis-sible sets of disturbances and measurement errors can turn to be only rough upper estimates on a short observation interval. The goal of research is the accuracy enhancement problem of guaran-teed estimation when measurement errors are not realized in the worst way, i.e. the environment in which the object operates does not behave as aggressively as it is built in a priori data on the permis-sible set of error values. Research design. The problem of adaptive guaranteed estimation of a con-stant signal from noisy measurements is considered. The adaptive filtering problem is, according to the results of measurement processing, from the whole set of possible realizations of errors, to choose the one that would generate the measurement sequence. Results. An adaptive guaranteed estimation algorithm is presented. The adaptive algorithm construction is based on a multi-alternative method based on the Kalman filter bank. The method uses a set of filters, each of which is tuned to a specific hypoth-esis about the measurement error model. Filter residuals are used to compute estimates of realized measurement errors. The choice of the realization of possible errors is performed using a function that has the meaning of the residual variance over a short time interval. Conclusion. The computa-tional scheme of the adaptive algorithm, the numerical example, and comparative analysis of ob-tained estimates are presented.

Expected A Posteriori Estimation of Multiple Latent Traits

2005 ◽  
Author(s):  
Damon U. Bryant ◽  
Ashley K. Smith ◽  
Sandra G. Alexander ◽  
Kathlea Vaughn ◽  
Kristophor G. Canali
Keyword(s):  
A Posteriori ◽  
Latent Traits ◽  
Posteriori Estimation

scholarly journals An Enhanced Smoothed L0-Norm Direction of Arrival Estimation Method Using Covariance Matrix

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4403
Author(s):  
Ji Woong Paik ◽  
Joon-Ho Lee ◽  
Wooyoung Hong
Keyword(s):  
Covariance Matrix ◽  
Phased Array ◽  
Null Space ◽  
Estimation Method ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Direction Of Arrival Estimation ◽  
Improve Performance ◽  
Space Projection

An enhanced smoothed l0-norm algorithm for the passive phased array system, which uses the covariance matrix of the received signal, is proposed in this paper. The SL0 (smoothed l0-norm) algorithm is a fast compressive-sensing-based DOA (direction-of-arrival) estimation algorithm that uses a single snapshot from the received signal. In the conventional SL0 algorithm, there are limitations in the resolution and the DOA estimation performance, since a single sample is used. If multiple snapshots are used, the conventional SL0 algorithm can improve performance in terms of the DOA estimation. In this paper, a covariance-fitting-based SL0 algorithm is proposed to further reduce the number of optimization variables when using multiple snapshots of the received signal. A cost function and a new null-space projection term of the sparse recovery for the proposed scheme are presented. In order to verify the performance of the proposed algorithm, we present the simulation results and the experimental results based on the measured data.

High-precision roll attitude estimation of decoupled canards relative to the projectile body using bipolar hall-effect sensors

2021 ◽  
pp. 1-9
Author(s):  
Tingting Yin ◽  
Zhong Yang ◽  
Youlong Wu ◽  
Fangxiu Jia
Keyword(s):  
Hall Effect ◽  
Real Time ◽  
High Precision ◽  
Solution Method ◽  
Estimation Method ◽  
Estimation Algorithm ◽  
Attitude Estimation ◽  
Fuzzy Algorithms ◽  
Positioning Method ◽  
Hall Effect Sensors

The high-precision roll attitude estimation of the decoupled canards relative to the projectile body based on the bipolar hall-effect sensors is proposed. Firstly, the basis engineering positioning method based on the edge detection is introduced. Secondly, the simplified dynamic relative roll model is established where the feature parameters are identified by fuzzy algorithms, while the high-precision real-time relative roll attitude estimation algorithm is proposed. Finally, the trajectory simulations and grounded experiments have been conducted to evaluate the advantages of the proposed method. The positioning error is compared with the engineering solution method, and it is proved that the proposed estimation method has the advantages of the high accuracy and good real-time performance.

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