scholarly journals A Hysteresis Dynamic Mathematical Model Approach to Parametric Estimation System

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Nubia Ilia Ponce de León Puig ◽  
Leonardo Acho ◽  
José Rodellar

The main contribution of this paper is the proposal of a recent hysteresis dynamic model which is successfully employed within a posited signal modulator. The modulation of signals is a commonly required stage in many engineering applications, such as telecommunications, power electronics, and control, among others. In this paper, the effectiveness of a signal modulator based on the well-known Delta modulator when it contains a dynamic hysteresis system within its main structure is presented. To do that, it is resorted to an application of the granted Hysteresis-Delta Modulator. This application consists of including the modulator within an adaptive scheme, since it is well known that the persistent excitation condition is required, for instance, in parameter estimation tasks. Hence, the main functional property of the modulator with hysteresis is its ability of producing a modulated signal with uniform high-frequency content even when its input is not a permanent persistent excitation signal. To highlight the main contribution of this paper, a numerical experiment of a parameter estimation system is developed to compare the performance of the modulator with the proposed hysteresis model and two other previously reported hysteresis systems. That is, three different scenarios have been tested in the parameter estimation of a nonminimum phase system. Finally, the numerical experiments confirm that the proposed hysteresis model along with the modulator provides the best performance as expected.

2019 ◽  
Vol 23 (2) ◽  
Author(s):  
Karen Alicia Aguilar Cruz ◽  
Romeo Urbieta Parrazales ◽  
José de Jesús Medel Juárez

1996 ◽  
Vol 118 (1) ◽  
pp. 58-65 ◽  
Author(s):  
R. I. Milford ◽  
S. F. Asokanthan

This paper presents experimental results for the real-time adaptive identification and control of a flexible, slewing beam. A frequency domain identification algorithm incorporating non-parametric transfer function estimation and least squares parametric estimation is used to reconstruct an accurate parametric model of the system, capable of accurately tracking changing plant dynamics in real time. This model is subsequently used to produce an LQG compensator which actively damps beam vibration caused by rapid slewing manoeuvres with large payload changes. Non-persistent excitation is addressed in the context of identification during nominal motion. It is shown that after a short duration learning period, the proposed identification scheme will yield a model which is sufficiently accurate for controller synthesis.


2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Yuan Chen ◽  
Hing Cheung So

Smart grid is an intelligent power generation and control console in modern electricity networks, where the unbalanced three-phase power system is the commonly used model. Here, parameter estimation for this system is addressed. After converting the three-phase waveforms into a pair of orthogonal signals via theαβ-transformation, the nonlinear least squares (NLS) estimator is developed for accurately finding the frequency, phase, and voltage parameters. The estimator is realized by the Newton-Raphson scheme, whose global convergence is studied in this paper. Computer simulations show that the mean square error performance of NLS method can attain the Cramér-Rao lower bound. Moreover, our proposal provides more accurate frequency estimation when compared with the complex least mean square (CLMS) and augmented CLMS.


Author(s):  
Saeed Ebrahimi ◽  
Jo´zsef Ko¨vecses

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.


Algorithms ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 167 ◽  
Author(s):  
Jun Zhao ◽  
Xian Wang ◽  
Guanbin Gao ◽  
Jing Na ◽  
Hongping Liu ◽  
...  

The stability and robustness of quadrotors are always influenced by unknown or immeasurable system parameters. This paper proposes a novel adaptive parameter estimation technology to obtain high-accuracy parameter estimation for quadrotors. A typical mathematical model of quadrotors is first obtained, which can be used for parameter estimation. Then, an expression of the parameter estimation error is derived by introducing a set of auxiliary filtered variables. Moreover, an augmented matrix is constructed based on the obtained auxiliary filtered variables, which is then used to design new adaptive laws to achieve exponential convergence under the standard persistent excitation (PE) condition. Finally, a simulation and an experimental verification for a typical quadrotor system are shown to illustrate the effectiveness of the proposed method.


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