scholarly journals Variable Sign-Sign Wilcoxon Algorithm: A Novel Approach for System Identification

2012 ◽  
Vol 2 (4) ◽  
Author(s):  
Mihir Narayan Mohanty ◽  
Sidhartha Dash
Keyword(s):  
System Identification ◽  
Variable Sign ◽  
Novel Approach

Über das Potenzial von Secondary Encodern zur Vermessung/Dynamic behaviour of industrial robots – about the potential of secondary encoders for system identification

2020 ◽  
Vol 110 (03) ◽  
pp. 130-134
Author(s):  
Michael Neubauer ◽  
Patrick Mesmer ◽  
Armin Lechler ◽  
Alexander Verl
Keyword(s):  
System Identification ◽  
Dynamic Behavior ◽  
Dynamic Behaviour ◽  
Industrial Robots ◽  
Novel Approach ◽  
Dynamic Path ◽  
Main Factor

Industrieroboter werden zunehmend für Anwendungen eingesetzt, in denen es wichtig ist, die programmierte Bahn exakt einzuhalten. Hierfür ist vorwiegend das dynamische Verhalten der Roboterachsen entscheidend. Stetig steigende Anforderungen an die dynamische Bahngenauigkeit motivieren die Analyse und Quantifizierung der Achsdynamik. In diesem Beitrag wird ein neuer Ansatz vorgestellt, bei dem das dynamische Verhalten von Roboterachsen mithilfe von Secondary Encodern ermittelt wird.   Industrial robots are increasingly used for applications with high requirements on path accuracy. The main factor here is the dynamic behavior of the robot joints. To satisfy rising demands on dynamic path accuracy, it is essential to analyze and quantify the axis dynamics. This paper presents a novel approach to determine the dynamic behavior of robot axes using secondary encoders.

System Identification of a Floating Oscillating Water Column Wave Energy Converter

2011 ◽  
Author(s):  
Brad Stappenbelt ◽  
Massimo Fiorentini ◽  
Paul Cooper ◽  
Song-Ping Zhu ◽  
Jean-Roch Nader
Keyword(s):  
System Identification ◽  
Water Column ◽  
Wave Energy ◽  
Forced Vibration ◽  
Lumped Parameter Model ◽  
Oscillating Water Column ◽  
Floating Structure ◽  
Novel Approach ◽  
Heave Motion ◽  
Energy Conversion Devices

One of the objectives of studies regarding the performance of floating oscillating water column (OWC) wave energy conversion devices is the prediction of the heave motion of the chamber and the water column. This paper presents a method to evaluate the parameters involved in the dynamics of partially submerged bodies in order to predict the coupled movement of the chamber and the water column in the frequency domain. System identification was performed and a lumped parameter model of the heave motions of a floating OWC was proposed. A novel approach utilising the reverse SISO method was employed to allow frequency dependent parameters for both the floating structure and the oscillating water column to be determined from several forced vibration experiments. Experimental results under forced vibration and wave excitation agree reasonably well with the dynamic model established.

scholarly journals WH-EA: An Evolutionary Algorithm for Wiener-Hammerstein System Identification

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
J. Zambrano ◽  
J. Sanchis ◽  
J. M. Herrero ◽  
M. Martínez
Keyword(s):  
System Identification ◽  
Evolutionary Algorithm ◽  
Nonlinear System Identification ◽  
Search Space ◽  
Single Step ◽  
Fine Tuning ◽  
Hammerstein Model ◽  
Hammerstein System ◽  
Hammerstein Systems ◽  
Novel Approach

Current methods to identify Wiener-Hammerstein systems using Best Linear Approximation (BLA) involve at least two steps. First, BLA is divided into obtaining front and back linear dynamics of the Wiener-Hammerstein model. Second, a refitting procedure of all parameters is carried out to reduce modelling errors. In this paper, a novel approach to identify Wiener-Hammerstein systems in a single step is proposed. This approach is based on a customized evolutionary algorithm (WH-EA) able to look for the best BLA split, capturing at the same time the process static nonlinearity with high precision. Furthermore, to correct possible errors in BLA estimation, the locations of poles and zeros are subtly modified within an adequate search space to allow a fine-tuning of the model. The performance of the proposed approach is analysed by using a demonstration example and a nonlinear system identification benchmark.

Spinning gasodynamic projectile system identification experiment design

2020 ◽  
Vol 92 (3) ◽  
pp. 452-459 ◽  
Author(s):  
Piotr Lichota ◽  
Mariusz Jacewicz ◽  
Joanna Szulczyk
Keyword(s):  
System Identification ◽  
High Speed ◽  
Content Type ◽  
Stability And Control ◽  
Novel Approach ◽  
Control Derivatives ◽  
Designed Experiment ◽  
Regions Of Stability ◽  
Short Time ◽  
And Control

Purpose The purpose of this paper is to present the methodology that was used to design a system identification experiment of a generic spinning gasodynamic projectile. For this object, because the high-speed spinning motion, it was not possible to excite the aircraft motion along body axes independently. Moreover, it was not possible to apply simultaneous multi-axes excitations because of the short time in which system identification experiments can be performed (multi-step inputs) or because it is not possible to excite the aircraft with a complex input (multi-sine signals) because of the impulse gasodynamic engines (lateral thrusters) usage. Design/methodology/approach A linear projectile model was used to obtain information about identifiability regions of stability and control derivatives. On this basis various sets of lateral thrusters’ launching sequences, imitating continuous multi-step inputs were used to excite the nonlinear projectile model. Subsequently, the nonlinear model for each excitation set was identified from frequency responses, and the results were assessed. For comparison, the same approach was used for the same projectile exited with aerodynamic controls. Findings It was found possible to design launching sequences of lateral thrusters that imitate continuous multi-step input and allow to obtain accurate system identification results in specified frequency range. Practical implications The designed experiment can be used during polygonal shooting to obtain a true projectile aerodynamic model. Originality/value The paper proposes a novel approach to gasodynamic projectiles system identification and can be easily applied for similar cases.

NONLINEAR SYSTEM IDENTIFICATION BASED ON INTERNAL RECURRENT NEURAL NETWORKS

2009 ◽  
Vol 19 (02) ◽  
pp. 115-125 ◽  
Author(s):  
GHEORGHE PUSCASU ◽  
BOGDAN CODRES ◽  
ALEXANDRU STANCU ◽  
GABRIEL MURARIU
Keyword(s):  
Neural Networks ◽  
System Identification ◽  
Nonlinear System ◽  
Recurrent Neural Networks ◽  
Internal State ◽  
Nonlinear System Identification ◽  
Backpropagation Algorithm ◽  
Novel Approach ◽  
System States

A novel approach for nonlinear complex system identification based on internal recurrent neural networks (IRNN) is proposed in this paper. The computational complexity of neural identification can be greatly reduced if the whole system is decomposed into several subsystems. This approach employs internal state estimation when no measurements coming from the sensors are available for the system states. A modified backpropagation algorithm is introduced in order to train the IRNN for nonlinear system identification. The performance of the proposed design approach is proven on a car simulator case study.

scholarly journals A Novel Approach of Speech Recognition Using System Identification

2019 ◽  
Vol 12 (3) ◽  
pp. 72-83
Author(s):  
Ibrahim Sadoon Fatah
Keyword(s):  
Artificial Intelligence ◽  
Speech Recognition ◽  
System Identification ◽  
Wiener Filter ◽  
High Accuracy ◽  
Accurate Prediction ◽  
Novel Approach ◽  
Noisy Signals ◽  
Noisy Background

With the growing of artificial intelligence and the usage of sound commands the needs for a high accuracy speech recognition increases. Many researches are done in this area using different kinds of methods and approaches. In this research two algorithms have been introduced. The autoregressive system identification and the FIR Wiener filter. The objective of this research is to show the robustness of system identification in terms of speech recognition.Both algorithms have been implemented and tested using MATLAB where the process is done by recording full sentences from different subjects under two conditions which are clear and noisy background. For each sentence, it has been recorded two timesfor each subject; the first one was used for testing and the second sentence was used for validation. The results show that both algorithms are giving an accurate prediction when the used data are from the same subject with clear background. The advantage of system identification over the Weiner filter is shine when using noisy signals. Another advantage of using system identification for speech recognition is it can distinguish the sound difference when same sentence from different subjects is used where the Weiner filter in some cases passes them as from the same subject. This could be a huge issue if the algorithm is used for security reasons

Nonlinear System Identification Applied to the Biomechanical Response of the Human Trunk during Sudden Loading

2002 ◽  
Vol 46 (13) ◽  
pp. 1076-1080
Author(s):  
Brad M. Lawrence ◽  
Gary A. Mirka ◽  
Gregory D. Buckner
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
System Identification ◽  
Nonlinear System ◽  
Nonlinear System Identification ◽  
Low Back ◽  
Novel Approach ◽  
Biomechanical Response ◽  
Sudden Loading ◽  
And Training

Epidemiological and biomechanical studies have indicated that sudden loading of the trunk may be a risk factor for low back pain development. Sudden loads may contribute significantly to the development of low back pain, due to the large muscular force responses associated with these loads. To date, most sudden loading studies have been observational studies that provide rich informational content, but do not provide a solid theoretical model to investigate kinematic and kinetic responses. A novel approach using nonlinear system identification and a time-varying model is introduced in this study to investigate the underlying dynamics of the trunk biomechanical system during sudden loading. This model has been used to study the effects of warning signals, muscular fatigue, and training on the biomechanical response of one subject. Data from this subject and additional subjects may provide recommendations for training protocols and administrative and engineering interventions that minimize exposure to potentially hazardous sudden loads.

Copper-dependent ATP7B up-regulation drives the resistance of TMEM16A-overexpressing head-and-neck cancer models to platinum toxicity

2019 ◽  
Vol 476 (24) ◽  
pp. 3705-3719 ◽  
Author(s):  
Avani Vyas ◽  
Umamaheswar Duvvuri ◽  
Kirill Kiselyov
Keyword(s):  
Oxidative Stress ◽  
Head And Neck ◽  
Transcriptional Activation ◽  
Platinum Resistance ◽  
Mrna Levels ◽  
Strong Positive Correlation ◽  
Platinum Compounds ◽  
Copper Chelation ◽  
Novel Approach ◽  
Cancer Models

Platinum-containing drugs such as cisplatin and carboplatin are routinely used for the treatment of many solid tumors including squamous cell carcinoma of the head and neck (SCCHN). However, SCCHN resistance to platinum compounds is well documented. The resistance to platinum has been linked to the activity of divalent transporter ATP7B, which pumps platinum from the cytoplasm into lysosomes, decreasing its concentration in the cytoplasm. Several cancer models show increased expression of ATP7B; however, the reason for such an increase is not known. Here we show a strong positive correlation between mRNA levels of TMEM16A and ATP7B in human SCCHN tumors. TMEM16A overexpression and depletion in SCCHN cell lines caused parallel changes in the ATP7B mRNA levels. The ATP7B increase in TMEM16A-overexpressing cells was reversed by suppression of NADPH oxidase 2 (NOX2), by the antioxidant N-Acetyl-Cysteine (NAC) and by copper chelation using cuprizone and bathocuproine sulphonate (BCS). Pretreatment with either chelator significantly increased cisplatin's sensitivity, particularly in the context of TMEM16A overexpression. We propose that increased oxidative stress in TMEM16A-overexpressing cells liberates the chelated copper in the cytoplasm, leading to the transcriptional activation of ATP7B expression. This, in turn, decreases the efficacy of platinum compounds by promoting their vesicular sequestration. We think that such a new explanation of the mechanism of SCCHN tumors’ platinum resistance identifies novel approach to treating these tumors.

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