scholarly journals A New Data-Driven Control System for MEMSs Gyroscopes: Dynamics Estimation by Type-3 Fuzzy Systems

Micromachines ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1390
Author(s):  
Khalid A. Alattas ◽  
Ardashir Mohammadzadeh ◽  
Saleh Mobayen ◽  
Ayman A. Aly ◽  
Bassem F. Felemban ◽  
...  
Keyword(s):  
Fuzzy System ◽  
Measurement Errors ◽  
Fuzzy Systems ◽  
Data Driven ◽  
Output Data ◽  
Data Set ◽  
Control Scheme ◽  
Mems Gyroscopes ◽  
The Stability ◽  
Type 3

In this study, a novel data-driven control scheme is presented for MEMS gyroscopes (MEMS-Gs). The uncertainties are tackled by suggested type-3 fuzzy system with non-singleton fuzzification (NT3FS). Besides the dynamics uncertainties, the suggested NT3FS can also handle the input measurement errors. The rules of NT3FS are online tuned to better compensate the disturbances. By the input-output data set a data-driven scheme is designed, and a new LMI set is presented to ensure the stability. By several simulations and comparisons the superiority of the introduced control scheme is demonstrated.

Conception and Implementation of a New Data-Driven Fuzzy Method for Reliability and Safety Analysis

2020 ◽  
Vol 16 (03) ◽  
pp. 517-539
Author(s):  
F. Abbasi ◽  
T. Allahviranloo
Keyword(s):  
System Reliability ◽  
Fuzzy Number ◽  
Fuzzy System ◽  
Fuzzy Systems ◽  
Fuzzy Numbers ◽  
Accurate Estimate ◽  
Data Driven ◽  
Proposed Model ◽  
Parameters Uncertainty ◽  
New Type

In this paper, the probability of failure of the components is introduced as a new type of fuzzy numbers called Gaussian patchy fuzzy number to insert parameters’ uncertainty. The reason for the use of such fuzzy numbers is also due to their realistic estimation. Hence, in order to obtain a more accurate estimate of each failure occurrence and overall system reliability analysis, we assume that the fundamental events of fault tree are in the form of Gaussian patchy fuzzy number on [0, 1], and then, by applying the fuzzy transmission average (TA) [F. Abbasi, T. Allahviranloo and S. Abbasbandy, A new attitude coupled with fuzzy thinking to fuzzy rings and fields, Journal of Intelligent and Fuzzy Systems, 29 (2015) 851-861], we will model the reliability of the fuzzy system (especially the series and the parallel). Applying such fuzzy operations and numbers will lead to a more realistic analysis of the reliability of the fuzzy system. Finally, the proposed model has been used for the lack of satisfaction of the University’s administrative and financial assistant.

Conception and Implementation of a New Data-Driven Fuzzy Method for Reliability and Safety Analysis

2020 ◽  
Vol 16 (02) ◽  
pp. 339-361
Author(s):  
F. Abbasi ◽  
T. Allahviranloo
Keyword(s):  
System Reliability ◽  
Fuzzy Number ◽  
Fuzzy System ◽  
Fuzzy Systems ◽  
Fuzzy Numbers ◽  
Accurate Estimate ◽  
Data Driven ◽  
Proposed Model ◽  
Parameters Uncertainty ◽  
New Type

In this paper, the probability of failure of the components is introduced as a new type of fuzzy number called Gaussian patchy fuzzy number to insert parameters’ uncertainty. The reason for the use of such fuzzy numbers is also due to their realistic estimation. Hence, in order to obtain a more accurate estimate of each failure occurrence and overall system reliability analysis, we assume that the fundamental events of fault tree are in the form of Gaussian patchy fuzzy number on [0, 1], and then, by applying the fuzzy transmission average (TA) [F. Abbasi, T. Allahviranloo and S. Abbasbandy, A new attitude coupled with fuzzy thinking to fuzzy rings and fields, Journal of Intelligent and Fuzzy Systems 29 (2015) 851–861.], we will model the reliability of the fuzzy system (especially the series and the parallel). Applying such fuzzy operations and numbers will lead to a more realistic analysis of the reliability of the fuzzy system. Finally, the proposed model has been used for the lack of satisfaction of the University’s administrative and financial assistant.

IMPULSIVE CONTROL FOR T–S FUZZY SYSTEM AND ITS APPLICATION TO CHAOTIC SYSTEMS

2006 ◽  
Vol 16 (08) ◽  
pp. 2417-2423 ◽  
Author(s):  
YAN-WU WANG ◽  
ZHI-HONG GUAN ◽  
HUA O. WANG ◽  
JIANG-WEN XIAO
Keyword(s):  
Chaotic System ◽  
Fuzzy System ◽  
Chaotic Systems ◽  
Lorenz System ◽  
Control Structure ◽  
Impulsive Control ◽  
Fuzzy Model ◽  
Chua's Circuit ◽  
Control Scheme ◽  
The Stability

An impulsive T–S fuzzy model is presented in this paper. The stability of impulsive controlled T–S fuzzy system has been analyzed theoretically. The proposed impulsive control scheme seems to have a simple control structure and may need less control energy than the normal continuous ones for the stabilization of T–S fuzzy system. Some typical chaotic systems, such as Chua's circuit, Lorenz system and Chen's chaotic system, are considered as illustrations to demonstrate the effectiveness of the proposed control scheme.

scholarly journals Design of an Unmatching Observer-Based Controller for Discrete-Time Fuzzy Systems with Time Delay

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Zejian Zhang ◽  
Dawei Wang
Keyword(s):  
Time Delay ◽  
Discrete Time ◽  
Fuzzy Systems ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Fuzzy Model ◽  
Membership Functions ◽  
Design Flexibility ◽  
Control Scheme ◽  
The Stability

The problem of an unmatching observer-based controller design for discrete-time fuzzy systems with time delay is investigated, in which the fuzzy controller shares different membership functions from the fuzzy model. The objective is to design a state observer and unmatching fuzzy controller such that the discrete closed-loop system with time delay is asymptotically stable. A sufficient condition that contains the information of the membership functions of fuzzy model and fuzzy controller for the stabilization via an unmatching observer-based output feedback is presented. The proposed control scheme is well capable of enhancing the design flexibility, and the stability condition is less conservative. Three numerical examples are given to illustrate the effectiveness and advantages of the proposed method.

A Review and evaluation of Machine Translation methods for Lumasaaba

2020 ◽  
pp. 3-17
Author(s):  
Peter Nabende
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Machine Translation ◽  
Language Processing ◽  
Research Area ◽  
Data Driven ◽  
East African ◽  
Data Set ◽  
African Languages ◽  
Translation Methods

Natural Language Processing for under-resourced languages is now a mainstream research area. However, there are limited studies on Natural Language Processing applications for many indigenous East African languages. As a contribution to covering the current gap of knowledge, this paper focuses on evaluating the application of well-established machine translation methods for one heavily under-resourced indigenous East African language called Lumasaaba. Specifically, we review the most common machine translation methods in the context of Lumasaaba including both rule-based and data-driven methods. Then we apply a state of the art data-driven machine translation method to learn models for automating translation between Lumasaaba and English using a very limited data set of parallel sentences. Automatic evaluation results show that a transformer-based Neural Machine Translation model architecture leads to consistently better BLEU scores than the recurrent neural network-based models. Moreover, the automatically generated translations can be comprehended to a reasonable extent and are usually associated with the source language input.

scholarly journals Data-Driven Stability Assessment of Multilayer Long Short-Term Memory Networks

2021 ◽  
Vol 11 (4) ◽  
pp. 1829
Author(s):  
Davide Grande ◽  
Catherine A. Harris ◽  
Giles Thomas ◽  
Enrico Anderlini
Keyword(s):  
Neural Network ◽  
Network Architecture ◽  
Short Term Memory ◽  
Moving Average ◽  
Machine Learning Algorithms ◽  
Physical Models ◽  
Data Driven ◽  
The Stability ◽  
And Control ◽  
Nonlinear Autoregressive

Recurrent Neural Networks (RNNs) are increasingly being used for model identification, forecasting and control. When identifying physical models with unknown mathematical knowledge of the system, Nonlinear AutoRegressive models with eXogenous inputs (NARX) or Nonlinear AutoRegressive Moving-Average models with eXogenous inputs (NARMAX) methods are typically used. In the context of data-driven control, machine learning algorithms are proven to have comparable performances to advanced control techniques, but lack the properties of the traditional stability theory. This paper illustrates a method to prove a posteriori the stability of a generic neural network, showing its application to the state-of-the-art RNN architecture. The presented method relies on identifying the poles associated with the network designed starting from the input/output data. Providing a framework to guarantee the stability of any neural network architecture combined with the generalisability properties and applicability to different fields can significantly broaden their use in dynamic systems modelling and control.

scholarly journals A Data-Driven Surrogate Approach for the Temporal Stability Forecasting of Vegetation Covered Dikes

Water ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 107
Author(s):  
Elahe Jamalinia ◽  
Faraz S. Tehrani ◽  
Susan C. Steele-Dunne ◽  
Philip J. Vardon
Keyword(s):  
Numerical Simulation ◽  
Water Flux ◽  
Temporal Stability ◽  
Synthetic Data ◽  
Climatic Conditions ◽  
Training Data ◽  
Data Driven ◽  
Data Set ◽  
Surface Cracking ◽  
Real Time Analysis

Climatic conditions and vegetation cover influence water flux in a dike, and potentially the dike stability. A comprehensive numerical simulation is computationally too expensive to be used for the near real-time analysis of a dike network. Therefore, this study investigates a random forest (RF) regressor to build a data-driven surrogate for a numerical model to forecast the temporal macro-stability of dikes. To that end, daily inputs and outputs of a ten-year coupled numerical simulation of an idealised dike (2009–2019) are used to create a synthetic data set, comprising features that can be observed from a dike surface, with the calculated factor of safety (FoS) as the target variable. The data set before 2018 is split into training and testing sets to build and train the RF. The predicted FoS is strongly correlated with the numerical FoS for data that belong to the test set (before 2018). However, the trained model shows lower performance for data in the evaluation set (after 2018) if further surface cracking occurs. This proof-of-concept shows that a data-driven surrogate can be used to determine dike stability for conditions similar to the training data, which could be used to identify vulnerable locations in a dike network for further examination.

scholarly journals Finite-Time Adaptive Fuzzy Control for Nonlinear Systems with Unknown Backlash-Like Hysteresis

2021 ◽  
Author(s):  
Shuzhen Diao ◽  
Wei Sun ◽  
Le Wang ◽  
Jing Wu
Keyword(s):  
Fuzzy Control ◽  
Finite Time ◽  
Fuzzy Systems ◽  
Tracking Error ◽  
Adaptive Fuzzy Control ◽  
Finite Time Stability ◽  
Adaptive Fuzzy ◽  
Intermediate Variable ◽  
Control Scheme ◽  
Theoretical Results

AbstractThis study considers the tracking control problem of the nonstrict-feedback nonlinear system with unknown backlash-like hysteresis, and a finite-time adaptive fuzzy control scheme is developed to address this problem. More precisely, the fuzzy systems are employed to approximate the unknown nonlinearities, and the design difficulties caused by the nonlower triangular structure are also overcome by using the property of fuzzy systems. Besides, the effect of unknown hysteresis input is compensated by approximating an intermediate variable. With the aid of finite-time stability theory, the proposed control algorithm could guarantee that the tracking error converges to a smaller region. Finally, a simulation example is provided to further verify the above theoretical results.

Stability of Ring-Type MEMS Gyroscopes Subjected to Stochastic Angular Speed Fluctuation

2017 ◽  
Vol 139 (4) ◽  
Author(s):  
Samuel F. Asokanthan ◽  
Soroush Arghavan ◽  
Mohamed Bognash
Keyword(s):  
Angular Velocity ◽  
Degrees Of Freedom ◽  
Microelectromechanical Systems ◽  
Damping Ratio ◽  
Operating Conditions ◽  
System Stability ◽  
System Response ◽  
Ring Type ◽  
Mems Gyroscopes ◽  
The Stability

Effect of stochastic fluctuations in angular velocity on the stability of two degrees-of-freedom ring-type microelectromechanical systems (MEMS) gyroscopes is investigated. The governing stochastic differential equations (SDEs) are discretized using the higher-order Milstein scheme in order to numerically predict the system response assuming the fluctuations to be white noise. Simulations via Euler scheme as well as a measure of largest Lyapunov exponents (LLEs) are employed for validation purposes due to lack of similar analytical or experimental data. The response of the gyroscope under different noise fluctuation magnitudes has been computed to ascertain the stability behavior of the system. External noise that affect the gyroscope dynamic behavior typically results from environment factors and the nature of the system operation can be exerted on the system at any frequency range depending on the source. Hence, a parametric study is performed to assess the noise intensity stability threshold for a number of damping ratio values. The stability investigation predicts the form of threshold fluctuation intensity dependence on damping ratio. Under typical gyroscope operating conditions, nominal input angular velocity magnitude and mass mismatch appear to have minimal influence on system stability.

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