Identification Toolbox Research Articles

Toolbox for Discovering Dynamic System Relations via TAG Guided Genetic Programming

Abstract Data-driven modeling of nonlinear dynamical systems often requires an expert user to take critical decisions a priori to the identification procedure. Recently, an automated strategy for data driven modeling of single-input single-output (SISO) nonlinear dynamical systems based on genetic programming (GP) and tree adjoining grammars (TAG) was introduced. The current paper extends these latest findings by proposing a multi-input multi-output (MIMO) TAG modeling framework for polynomial NARMAX models. Moreover, we introduce a TAG identification toolbox in Matlab that provides implementation of the proposed methodology to solve multi-input multi-output identification problems under NARMAX noise assumption. The capabilities of the toolbox and the modeling methodology are demonstrated in the identification of two SISO and one MIMO nonlinear dynamical benchmark models.

RaPId - A Parameter Estimation Toolbox for Modelica/FMI-Based Models Exploiting Global Optimization Methods

Abstract This paper describes new additions to the Rapid Parameter Identification Toolbox (RaPId), which is an open-source MATLAB toolbox for parameter estimation using models developed with the Modelica language and exported with the functional mock-up interface (FMI) Standard. These additions include an updated graphical user interface (GUI), an optimization method utilizing multiple starting points for a gradient descent optimization, and examples for different cyber-physical system applications such as the Duffing-Holmes equation modeling in a form of electrical circuit and a hydroelectric power plant modeling.

Experimental Simulation and Verification of Position Servo Control of Mechanical Rodless Cylinder

In order to improve the position control accuracy of rodless cylinder, the valve control cylinder system based on pneumatic proportional servo is studied deeply. According to the working principle of the mechanical rodless cylinder control system, under the condition of uniform speed, the driving voltage of the proportional valve is changed to measure multiple sets of friction force and corresponding velocity data. Analyzed the physical structure of each component in pneumatic system, established the mathematical model of pneumatic system, and introduced MATLAB system identification toolbox to identify the parameters of the transfer function. and the experiment verifies its correctness.

Phylogenomic Analysis of Campylobacter fetus Reveals a Clonal Structure of Insertion Element ISCfe1 Positive Genomes.

Subspecies of the species Campylobacter fetus are associated with specific host niches including mammals and reptiles. Campylobacter fetus subsp. fetus is a zoonotic pathogen infecting humans. Infections can vary from an acute intestinal illness to severe systemic infections, with sheep and cattle as major reservoirs. In contrast, Campylobacter fetus subsp. venerealis causes bovine genital campylobacteriosis, which leads to abortion in cattle and a high economic burden for the farmers. Therefore, high-quality molecular subtyping is indispensable for interventional epidemiology. We used whole-genome sequencing (WGS) data of 283 Campylobacter fetus strains from 18 countries and compared several methods for Campylobacter fetus subtyping, including WGS, multilocus sequence typing, PCR assays, and the presence of the insertion element ISCfe1. We identified a highly clonal clade (designated as clade 1) that harbors the insertion sequence ISCfe1. The presence of this insertion sequence is an essential diagnostic tool for the identification of the subspecies Campylobacter fetus subsp. venerealis, serving as a target for several PCR assays. However, we have found a high sequence variability for the ISCfe1 besides the presence of ISCfe1-paralogues in certain other genomes (n = 7) which may cause incorrect diagnostic results. Clade 1 seems to be the cattle-specific clade of this species. We propose that only this clade might be designated as Campylobacter fetus subsp. venerealis as it harbors the ISCfe1 marker sequence, which is a major target for molecular methods currently used for Campylobacter fetus subspecies identification. Fostering this proposal, we defined eleven stable nucleotide markers specific for this clade. Additionally, we developed a bioinformatics toolbox for the fast identification of this clade based on WGS data. In conclusion, our results demonstrate that WGS can be used for Campylobacter fetus subtyping overcoming limitations of current PCR and MLST protocols.

Defect identification and statistics toolbox: automated defect analysis for scanning probe microscopy images

Identifying and classifying defects in scanning probe microscopy (SPM) images is an important task that is tedious to perform by hand. In this paper we present the defect identification and statistics toolbox (DIST), an image processing toolbox for identifying and analyzing atomic defects in SPM images. DIST combines automation with user input to accurately and efficiently identify defects and automatically compute critical statistics. We describe using DIST for interactive image processing, generating contour plots for isolating extrema from an image background, and processes for identifying defects.

Enhancing the Accuracy of Vertical Ground Reaction Force Measurement During Walking Using Pressure-Measuring Insoles.

Pressure-measuring insoles can be an attractive tool for measuring ground reaction force (GRF) since they are portable and can record multiple consecutive steps. Several researchers have, however, observed that these insoles are less accurate than instrumented force platforms. To address this issue, the authors identified transfer functions that best described each insole size to enhance the measurements of the vertical component of GRF during walking. GRF data were collected from 29 participants (6/23 male/female, 24.3 ± 6.7 yrs, 70.4 ± 23.9 kg, 1.66 ± 0.11 m) using Medilogic® pressure-measuring insoles and Kistler® force platforms for three walking trials. Participants provided the institutionally approved written consent (IRB #724468). The data from both instruments were preprocessed. A subset of the data was used to train the system identification toolbox (matlab) to identify the coefficients of several candidate transfer functions for each insole size. The resulting transfer functions were compared using all available data for each insole to assess which one modified the insole data to be closer to that of the force platform. All tested transfer functions moved the vertical component of GRF closer to the corresponding force platform data. Each insole size had a specific transfer model that that yielded the best results. Using system identification techniques produced transfer functions that, when using insole data of the vertical component of GRF as input, produced output that is comparable to the corresponding measurement using an instrumented force platform.

The utility of DNA barcodes to confirm the identification of palm collections in botanical gardens.

The palm family (Arecaceae) is of high ecological and economic value, yet identification in the family remains a challenge for both taxonomists and horticulturalists. The family consists of approximately 2600 species across 181 genera and DNA barcoding may be a useful tool for species identification within the group. However, there have been few systematic evaluations of DNA barcodes for the palm family. In the present study, five DNA barcodes (rbcL, matK, trnH-psbA, ITS, ITS2) were evaluated for species identification ability across 669 samples representing 314 species and 100 genera in the Arecaceae, employing four analytical methods. The ITS gene region was found to not be a suitable barcode for the palm family, due in part, to low recovery rates and paralogous gene copies. Among the four analyses used, species resolution for ITS2 was much higher than that achieved with the plastid barcodes alone (rbcL, matK, trnH-psbA), and the barcode combination ITS2 + matK + rbcL gave the highest resolution among all single barcodes and their combinations, followed by ITS2 + matK. Among 669 palm samples analyzed, 110 samples (16.3%) were found to be misidentified. The 2992 DNA barcode sequences generated in this study greatly enriches the existing identification toolbox available to plant taxonomists that are interested in researching genetic relationships among palm taxa as well as for horticulturalists that need to confirm palm collections for botanical garden curation and horticultural applications. Our results indicate that the use of the ITS2 DNA barcode gene region provides a useful and cost-effective tool to confirm the identity of taxa in the Palm family.

Transfer function identification of a liquid flow-line pressure control system from simple relay auto-tuning

Accurate modeling of liquid flow systems is necessary for the effective operation of the plant under different conditions. The plant dynamics may change with time, and due to this, the operation may not be satisfactory. In this article, relay autotuning of a liquid flow-line is proposed. Well-known describing function approximation is utilized for the estimation of gain of relay used in a feedback loop to excite the plant to be identified. The expressions are derived for the identification of a class of overdamped second-order plus dead-time and first-order plus dead-time plant dynamics. The identification method tested on different standard systems shows that the proposed method has good identification accuracy. Therefore, the proposed identification method is applied to a liquid flow line pressure control system. The experimental results show that an accurate dynamic model is extracted using the proposed method with a minimal set of data from an obtained limit cycle oscillation. The measured quantities of the limit cycle are utilized in the derived explicit expressions for the identification of unknown variables of the dynamic plant model. A distributed process control system is utilized here as a standard industrial platform to design virtual relay and conduct the proposed autotuning. The efficiency of the modeling method is demonstrated through the comparison of Nyquist and relay response plots with the transfer functions obtained from the MATLAB system identification toolbox.

Robust decentralized proportional–integral controller design for an activated sludge process

AbstractThis paper presents the design of a decentralized proportional–integral (PI) controller for a wastewater treatment plant (WWTP). The aeration rate and the return recycle sludge rate are manipulated inputs to the WWTP process, while substrate and biomass concentration are considered as the output variables. The study is divided into two segments: A decentralized controller is designed based on the best pairing in the first segment, and in the second segment, a decoupler is developed to reduce the interactions. Decouplers are generally used to create independent loops in the multivariable control loops. Each decoupled subsystem is converted to first order plus time delay (FOPTD) model using a system identification toolbox to design independent diagonal controllers. The numerical simulations have been performed to evaluate the effectiveness of the presented methods. Furthermore, a robustness study has also been carried out by taking into account multiplicative input and output uncertainties, and it is found that the controller designed based on minimizing the integral of absolute error (IAE) criteria shows more robust.

Construction of greenhouse environment temperature adaptive model based on parameter identification

Rich literature has reported that there exists a nonlinear and time varying association between natural ventilation and temperature. This paper focus on the model of greenhouse temperature and parameter states estimation online. Adaptive control allows self-tuning of control parameters in the face of changing dynamics. The parameter identification of the model can select a suitable mathematical model according to the input and output of the data, and compare the matching with the original system model to determine the model category. The research has identified the assumed parameters in the model using system identification toolbox. A total of 90 groups of data were processed and model identification operations were performed for 3 months, then the transfer function of the greenhouse model was obtained. Detailed information has been acquired about the relevant model reference adaptive control system, including the description of the system structure, which is beneficial to the sub-module design of the model. The research suggests that the determined model is beneficial to the design of the controller. Finally, the stability test is carried out to ensure the designed adaptive control system basically stable. The research work has brought about a discovery of the error converges over time. Moreover, the output of the controlled object model after adaptive adjustment is gradually approached to the output of the reference model, achieving the adaptive control of the system.

Simplified Analysis for Multiple Input Systems: A Toolbox Study Illustrated on F-16 Measurements

This paper introduces a nonparametric, nonlinear system identification toolbox called SAMI (simplified analysis for multiple input systems) developed for industrial measurements of vibro-acoustic systems with multiple inputs. It addresses the questions related to the user-friendly (semi-)automatic processing of multiple-input, multiple-output measurements with respect to the design of an experiment and the analysis of the measured data. When the proposed toolbox is used, with minimal user interaction, it is easily possible (a) to decide whether the underlying system is linear or not, (b) to decide whether the linear framework is still adequate to be used, and (c) to tell an inexperienced user how much can be gained using an advanced nonlinear framework. The toolbox is illustrated on openly accessible F-16 ground vibration testing measurements.

Model predictive control of vinyl chloride monomer process by Aspen Plus Dynamics and MATLAB/Simulink co-simulation approach

Characteristics of a vinyl chloride monomer (VCM) process is complex and nonlinear due to interactions between units in a reaction-separation network, multiple process streams, and multiple control loops involved. A fluctuation of the thermal cracking unit could result in a difficulty in maintaining downstream units at the setpoints. In this work, an approach to develop a model predictive control (MPC) for the VCM process by deploying a co-simulation between MATLAB/Simulink and Aspen Plus Dynamics is presented. The co-simulation provides more capability and comfortability to design the MPC controller, and evaluate controllability. The VCM process consisting of thermal cracking, quench and distillation is modelled by Aspen Plus Dynamics. The MPC is developed by integrating the concept of plant-wide control and subsystem partitioning. To reduce the burden of mathematical modeling, the MATLAB system identification toolbox is used to develop a multivariable linear model for the MPC controller by reconciling dynamics data from the VCM plant model. Performances of the developed MPC is evaluated under the regulatory test of the EDC feed disturbance. By comparison with the multiple single-input-single-output proportional-integral controllers through the efficiency indexes—an integral squared error, an overshoot and a settling time. Simulation results supported that the MPC controller outperforms proportional-integral controllers.

Identification parameter system for mathematical modeling BLDC motor using transfer function models

The parameter system identification of Brushless Direct Current (BLDC) motorbike on electric bicycles is one of the important factors that support success in improving a stable and reliable control system. The purpose of this paper is to explain the mathematical modeling of BLDC motors by system identification parameters. The method of system identification parameters used in this study is experimentation, namely the pulse width modulation (PWM) signal generation process and the collection of input data in the form of current, voltage, and output data such as speed is carried out using sensors connected to the microcontroller. The input and output data are then simulated using the transfer function model found in the system identification toolbox in the MATLAB program. From the results of testing and simulations carried out on the BLDC motor system, a mathematical model was obtained in the form of a transfer function with third-order transfer function is the best fit value than the others. The sequential values of the transfer function 1, 2 and 3 are 69.81, -1945, and 83.34.

CONCEPTUAL DESIGN OF AUTONOMOUS CART FOLLOWER FOR WHEELCHAIR USER

This paper focuses on kinematics of the cart follower and the system identification of propulsion system by using brushed DC motor. The cart follower uses Ackermann configuration as the steering system. The modeling of kinematics equation takes into account the instantaneous center of rotation (ICR), velocity of each tire, heading angle, and simple movement of the cart. The cart is propelled by transaxle brushed DC motor. It is important to approximate an accurate transfer function to represent the motor as the plant module is unavailable. The motor is simulated by using Arduino hardware package in MATLAB®. Rotary encoder is used to record the angular velocity of the shaft. MATLAB® code is created in order to calculate the linear velocity and tabulate the datasets. System Identification Toolbox determines the transfer function of the motor and its performance. The variables measured in experiment to identify the transfer function of the DC motor system are output angular velocity and input voltage. The parameters taken from the DC motor’s mathematical model are derived based on existing literatures. The graph of output velocity against time is plotted and the transfer function is estimated by using System Identification Toolbox in MATLAB®. From the results, it is demonstrated that the motor exhibits second order system.
 Keywords: Cart follower, wheel mobile robot, kinematics, system identification

Dynamic model and control system of carbon dioxide capture process in fluidized bed using computational fluid dynamics

Nowadays, the concentration of greenhouse gases in the atmosphere has been growing continuously due to the increase of energy consumption, generated from carbon-based fuels and has created global warming. In this study, a model of carbon dioxide capture adsorption in a fluidized bed reactor was developed based on experimental data using commercial CFD program called ANSYS FLUENT. Then the model was employed to observe the hydrodynamics behavior and the dynamic responses of CO2 capture inside the adsorber when the operating variables were changed. The effects of operating variables on carbon dioxide capture were evaluated. From the simulation results, both the inlet gas velocity and the inlet solid circulation rate affected the carbon dioxide capture. The relationships between inlet gas velocity and inlet solid circulation rate to the percentage of carbon dioxide capture were investigated and analyzed by using system identification toolbox in MATLAB. After that, these relationships were used to design a control system. For the considered control system, the inlet solid circulation rate was selected to be a manipulated variable, while the inlet gas velocity, composition and temperature were designated as system disturbances. The controlled variable was carbon dioxide content remaining in the flue gas at the outlet. It was found that the control system could maintain the concentration of carbon dioxide in the flue gas at a specified value.

KBERG: A MatLab toolbox for nonlinear kernel-based regularization and system identification

We present KBERG, a MatLab package for nonlinear Kernel-BasEd ReGularization and system identification. The toolbox provides a complete environment for running experiments on simulated and experimental data from both static and dynamical systems. The whole identification procedure is supported: (i) data generation, (ii) excitation signals design; (iii) kernel-based estimation and (iv) evaluation of the results. One of the main differences of the proposed package with respect to existing frameworks lies in the possibility to separately define experiments, algorithms and test, then combining them as desired by the user. Once these three quantities are defined, the user can simply run all the computations with only a command, waiting for results to be analyzed. As additional noticeable feature, the toolbox fully supports the manifold regularization rationale, in addition to the standard Tikhonov one, and the possibility to compute different (but equivalent) types of solutions other than the standard one.

Modelling, identification, implementation and MATLAB simulations of multi-input multi-output proportional integral-plus control strategies for a centrifugal chiller system

The objective of this paper is to investigate a new design and real-time implementation approach of a predictive proportional integral-plus (PIP) closed-loop control strategy for a centrifugal chiller HVAC system. By using the analytical model of the plant, linear discrete-time multi-input multi-output (MIMO) autoregressive moving average exogenous (ARMAX) polynomial models were developed. The structure of developed ARMAX models is straightforward, and they are suitable to capture the complex dynamics of the centrifugal chiller plant. Fundamentally, these identified models use the least-squares estimation (LSE) method to evaluate the polynomials coefficients and model parameters implemented using specific tools provided by MATLAB's system identification toolbox. The new modelling approach is beneficial for simulation purposes to prove the efficiency of the proposed closed-loop control strategy, the tracking performance, and its robustness to possible changes in the load disturbance and noise level of measurement sensors.

Modeling, system identification and design of fuzzy PID controller for discharge dynamics of metal hydride hydrogen storage bed

This paper presents the mathematical modeling of metal hydride based hydrogen storage bed. The novelty of this research work is the identification of transfer function for the dynamic discharge process of hydrogen storage bed is carried out using system identification tool box. A Fuzzy PID controller is modeled to regulate the pressure rate of hydrogen storage bed using MATLAB Simulink toolbox. The proposed controller reduces the complexity in controlling the pressure rate of hydrogen storage bed during desorption process for an adequate use in fuel cell and in other applications. To validate the reliability of the hydrogen storage bed model, the obtained results are verified with the results of other literature. The exact system transfer function model chosen is Box-Jenkin model, based on the simulated results of different black box model structures for the parameters such as percentage of fitness, final prediction error and the cost function. Usually, for the safer discharge of hydrogen gas, the classical PID controller is employed to control the pressure by manipulating the heating temperature of the storage bed. In order to have a better control, a Fuzzy-PID controller is proposed in this study. The proposed controller produces improved time domain response and better performance compared to the conventional PID controller.

Controllable and observable control design of wind generator system using PID algorithm

This paper describes a design process of the wind generator control system. Controlling a wind generator, fan, is important to study the design of the wind turbine. A complex wind generator model was approximated with 5th order polynomial function. The paper describes a procedure for identifying system, especially for finding the transfer function of a plant, that based on input and output. The plant’s input is an electric motor fan voltage and output is wind speed produced. It’s important to simplify control’s design of the wind generator for configuring transfer functions of the plant. The identification method that is used is Linear Regression, applying Excel program, which produces a polynomial function. And then, the Matlab’s System Identification Toolbox (SIT), which produces a transfer function. From this study, applying SIT, a model of wind generator, shows the fit estimation data is 90.78% and MSE is 0.078%. A closed-loop control system using PID controller is proposed. Controllable and Observable of the state space model were verified. The best performance of the close-loop system was achieved using Kp=0.2247, Ki=6.05*10-5, and Kd=208.75 applying Ziegler-Nichols. The results showed that the closed loop stability by applying PID can stabilize the wind generator.

Dynamic Matrix Control of a Reactive Distillation Process for Biodiesel Production

This study has been carried out to demonstrate the control of a reactive distillation process in which the production of biodiesel was taken as the case study using an advanced control method, which is known as dynamic matrix control. The control was accomplished by employing the transfer function model of the reactive distillation process developed, using the System Identification Toolbox of MATLAB, from the dynamic data generated when the prototype plant of the process was simulated with the aid of ChemCAD process simulator. The results obtained from the dynamic matrix control were compared with those of a proportional-integral-derivative (PID) control system tuned with Ziegler-Nichols and Cohen-Coon methods, and it was discovered that the dynamic matrix control was able to perform best among the three (dynamic matrix control method, PID tuned with Ziegler-Nichols method and PID tuned with Cohen-Coon method) because it (the dynamic matrix control) was able to make the biodiesel mole fraction response not to exceed the maximum limit value of 1 in addition to having the lowest sum of absolute errors (SAE) and sum of squared errors (SSE) from the control systems that were simulated.