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1

Implementation of PID Autotuning Procedure Based on Doublet-Pulse Method in PLC Controller

Awtoniuk Michał, Sałat Robert, Worwa Miłosz, Reshetiuk Volodymyr

Advances in Science and Technology. Research Journal

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2024

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Vol. 18, no 1

89--97

EN

The paper describes the implementation of a PI controller autotuning procedure based on the doublet-pulse method. The doublet-pulse method is used as a tool to identify the control object. Its main advantage is its simplicity, requiring only two parameters to be declared, i.e., the amplitude and duration of the two step signals. We combined the Doublet-Pulse method with the Approximate M-constrained Integral Gain Optimisation tuning rules and implemented this combination as a stand-alone autotuning procedure in Siemens S7-1200 PLC controller. The procedure was tested for three types of simulated plant models. The simulated models were diverse in terms of dynamics, as we used lag-dominated, balanced, and delay-dominated models. We compared the doublet-pulse method with the classical identification method in the form of step response, i.e. method of moments. We conducted tests for three scenarios, i.e., a step change in the set point, set point trajectory tracking and load disturbances. To assess the control quality, we used integral index IAE. The described method is universal and can also be implemented in controllers from other manufacturers.

2

ARMAX-based identification and diagnosis of vibration behavior of gas turbine bearings

Mahroug Youcef, Khaldi Belgacem Said, Guemana Mouloud, Hafaifa Ahmed, Iratni Abdelhamid, Colak Ilhami

Diagnostyka

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2023

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Vol. 24, No. 3

art. no. 2023310

EN

Parametric identification approaches play a crucial role in the control and monitoring of industrial systems. They facilitate the identification of system variables and enable the prediction of their evolution based on the input-output relationship. In this study, we employ the ARMAX approach to accurately predict the dynamic vibratory behavior of MS5002B gas turbine bearings. By utilizing real input-output data obtained from their operation, this approach effectively captures the vibration characteristics of the bearings. Additionally, the ARMAX technique serves as a valuable diagnostic tool for the bearings, enhancing the quality of identification of turbine variables. This enables continuous monitoring of the bearings and real-time prediction of their behavior. Furthermore, the ARMAX approach facilitates the detection of all potential vibration patterns that may occur in the bearings, with monitoring thresholds established by the methodology. Consequently, this enhances the availability of the bearings and reduces turbine downtime. The efficacy of the proposed ARMAX approach is demonstrated through comprehensive results obtained in this study. Robustness tests are conducted, comparing the real behavior observed through various probes with the reference model, thereby validating the approach.

3

The buffered optimization methods for online transfer function identification employed on DEAP actuator

Bernat Jakub, Kołota Jakub

Archives of Control Sciences

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2023

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Vol. 33, No. 3

565--587

EN

Identification plays an important role in relation to control objects and processes as it enables the control system to be properly tuned. The identification methods described in this paper use the Stochastic Gradient Descent algorithms, which have so far been successfully presented in machine learning. The article presents the results of the Adam and AMSGrad algorithms for online estimation of the Dielectric Electroactive Polymer actuator (DEAP) parameters. This work also aims to validate the learning by batch methodology, which allows to obtain faster convergence and more reliable parameter estimation. This approach is innovative in the field of identification of control systems. The research was supplemented with the analysis of the variable amplitude of the input signal. The dynamics of the DEAP parameter convergence depending on the normalization process was presented. Our research has shown how to effectively identify parameters with the use of innovative optimization methods. The results presented graphically confirm that this approach can be successfully applied in the field of control systems.

4

Discrete identification of continuous non-linear andnon-stationary dynamical systems that is insensitive to noise correlation and measurement outliers

Kozłowski Janusz, Kowalczuk Zdzisław

Archives of Control Sciences

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2023

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Vol. 33, No. 2

391--411

EN

The paper uses specific parameter estimation methods to identify the coefficients of continuous-time models represented by linear and non-linear ordinary differential equations. The necessary approximation of such systems in discrete time in the form of utility models is achieved by the use of properly tuned ‘integrating filters’ of the FIR type. The resulting discrete-time descriptions retain the original continuous parameterization and can be identified, for example, by the classical least squares procedure. Since in the presence of correlated noise, the estimated parameter values are burdened with an unavoidable systematic error (manifested by asymptotic bias of the estimates), in order to significantly improve the identification consistency, the method of instrumental variables is used here. In our research we use an estimation algorithm based on the least absolute values (LA) criterion of the least sum of absolute values, which is optimal in identifying linear and non-linear systems in the case of sporadic measurement errors. In the paper, we propose a procedure for determining the instrumental variable for a continuous model with non-linearity (related to the Wienerian system) in order to remove the evaluation bias, and a recursive sub-optimal version of the LA estmator. This algorithm is given in a simple (LA) version and in an instrumental variable version (IV-LA), which is robust to outliers, removes evaluation bias, and is suited to the task of identifying processes with non-linear dynamics (semi-Wienerian/NLID). In conclusion, the effectiveness of the proposed algorithmic solutions has been demonstrated by numerical simulations of the mechanical system, which is an essential part of the suspension system of a wheeled vehicle.

5

Cascade tanks system identification for robust predictive control

Jakowluk Wiktor, Jaszczak Sławomir

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2022

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Vol. 70, nr 6

art. no. e143646

EN

The main goal of estimating models for industrial applications is to guarantee the cheapest system identification. The requirements for the identification experiment should not be allowed to affect product quality under normal operating conditions. This paper deals with ensuring the required liquid levels of the cascade system tanks using the model predictive control (MPC) method. The MPC strategy was extended with the Kalman filter (KF) to predict the system’s succeeding states subject to a reference trajectory in the presence of both process and measurement noise covariances. The main contribution is to use the application-oriented input design to update the parameters of the model during system degradation. This framework delivers the least-costly identification experiment and guarantees high performance of the system with the updated model. The methods presented are evaluated both in the experiments on a real process and in the computer simulations. The results of the robust MPC application for cascade system water levels control are discussed.

6

Arriving air traffic separations generalized model identification

Pawełek Adrian, Lichota Piotr

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2022

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Vol. 70, nr 2

art. no. e140694

EN

Quick development of computer techniques and increasing computational power allow for building high-fidelity models of various complex objects and processes using historical data. One of the processes of this kind is an air traffic, and there is a growing need for traffic mathematical models as air traffic is increasing and becoming more complex to manage. This study concerned the modelling of a part of the arrival process. The first part of the research was air separation modelling by using continuous probability distributions. Fisher information matrix was used for the best fit selection. The second part of the research consisted of applying regression models that best match the parameters of representative distributions. Over a dozen airports were analyzed in the study and that allowed to build a generalized model for aircraft air separation in function of traffic intensity. Results showed that building a generalized model which comprises traffic from various airports is possible. Moreover, aircraft air separation can be expressed by easy to use mathematical functions. Models of this kind can be used for various applications, e.g.: air separation management between aircraft, airports arrival capacity management, and higher-level air traffic simulation or optimization tasks.

7

On-line process identification using the Modulating Functions Method and non-asymptotic state estimation

Byrski Witold, Drapała Michał

Archives of Control Sciences

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2022

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Vol. 32, No. 3

535--555

EN

The paper presents an iterative identification method dedicated for industrial processes. The method consists of two steps. In the first step, a MISO system is identified with the Modulating Functions Method to obtain sub-models with a common denominator. In the second step, the obtained subsystems are re-identified. This procedure enables to obtain the set of models with different denominators of the transfer functions. The algorithm was used for on-line identification of a glass conditioning process. Identification window is divided into intervals, in which the models can be updated based on recent process data, with the use of the integral state observer. Results of the performed simulations for the identified models are compared with the historical process data.

8

Online continuous-time adaptive predictive control of the technological glass conditioning process

Drapała Michał, Byrski Witold

Archives of Control Sciences

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2022

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Vol. 32, No. 4

755--782

EN

Glass production has a great industrial importance and is associated with many technological challenges. Control related problems concern especially the last part of the process, so called glass conditioning. Molten glass is gradually cooled down in a long ceramic channels called forehearths during glass conditioning. The glass temperature in each zone of the forehearth should be precisely adjusted according to the assumed profile. Due to cross-couplings and unmeasured disturbances, traditional control systems based on PID controllers, often do not ensure sufficient control quality. This problem is the main motivation for the research presented in the paper. A Model Predictive Control algorithm is proposed for the analysed process. It is assumed the dynamic model for each zone of the forehearth is identified on-line with the Modulating Functions Method. These continuous-time linear models are subsequently used for two purposes: for the predictive controller tuning, measurable disturbances compensation and for a static set point optimisation. Proposed approach was tested using Partial Differential Equation model to simulate two adjacent zones of the forehearth. The experimental results proved that it can be successfully applied for the aforementioned model.

9

System identification and heuristic control of segmented ailerons for enhanced stability of fixed wing UAVS

Sattar Abdul, Wang Liuping, Mohamed Abdulghani, Fisher Alex

Journal of Automation Mobile Robotics and Intelligent Systems

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2021

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Vol. 15, No. 3

3--14

EN

Different from a conventional aircraft, an investigation on system identification and control design has been carried out on a small fixed‐wing unmanned aerial vehicle (UAV) with segmented ailerons. The multiple aileron setup is configured as a multi‐input and single‐output system, and each segment is modeled as a control input. Experiments are conducted in the wind tunnel to determine the frequency responses of the system and the corresponding transfer functions. Multiple PID controllers are designed and implemented in a cascaded form for each control surface. Furthermore, a heuristic switching control strategy is implemented for the aircraft where the multiple aileron segments perform as a single aileron pair in a normal flight condition and adapt to multi‐segment control when encountering severe turbulence or significant angle reference changes. Experimental results reveal that although each control surface can stabilize the aircraft, the proposed control strategy by combining the multiple actuation surfaces reduces the mean squared errors for the roll angle up to 38 percent in the highly turbulent en vironment providing superior disturbance rejection properties.

10

Novel solutions on model-based and model-free robotic-assisted ankle rehabilitation

Arceo Juan Carlos, Alvarez Jorge, Armenta Carlos, Lauber Jimmy, Cremoux Sylvian, Simoneau-Buessinger Emilie, Bernal Miguel

Archives of Control Sciences

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2021

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Vol. 31, No. 1

5--27

EN

In this report, ankle rehabilitation routines currently approved by physicians are implemented via novel control algorithms on a recently appeared robotic device known as the motoBOTTE. The physician specifications for gait cycles are translated into robotic trajectories whose tracking is performed twofold depending on the availability of a model: (1) if obtained via the Euler-Lagrange approach along with identification of unknown plant parameters, a new computed-torque control law is proposed; it takes into account the parallel-robot characteristics; (2) if not available, a variation of the active disturbance rejection control technique whose parameters need to be tuned, is employed. A detailed discussion on the advantages and disadvantages of the model-based and model-free results, from the continuous-time simulation to the discrete-time implementation, is included.

11

Modelling of Dry-Low Emission Gas Turbine Fuel System using First Principle Data-Driven Method

Omar Mediah Binti, Ibrahim Rosdiazli, Abdullah Mohd Faris, Tarik Mohammad Haizad Mohd

Journal of Power Technologies

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2020

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Vol. 100, nr 1

1--13

EN

Achieving reliable power generation from Dry Low Emission gas turbines together with low CO2 and NOx discharge is a great challenge, as the rigorous control strategy is susceptible to frequent trips. Therefore, it is crucial to establish a dynamic model of the turbine (such as the one commonly attributed to Rowen) to ascertain the stability of the system. However, the major distinctive fuel system design in the DLE gas turbine is not constructed in the well-established model. With this issue in mind, this paper proposes a modelling approach to the DLE gas turbine fuel system which consists of integrating the main and pilot gas fuel valve into Rowen’s model, using the First Principle Data-Driven (FPDD) method. First, the structure of the fuel system is determined and generated in system identiﬁcation. Subsequently, the validated valve models are integrated into Rowen’s model as the actual setup of the DLE gas turbine system. Ultimately, the core of this modelling approach is fuel system integration based on the FPDD method to accurately represent the actual signals of the pilot and main gas fuel valves, gas fuel ﬂow and average turbine temperature. Then, the actual signals are used to validate the whole structure of the model using MAE and RMSE analysis. The results demonstrate the high accuracy of the DLE gas turbine model representation for future utilization in fault identiﬁcation and prediction study.

12

Fractional discrete model of an electrical drive with brushless micro-motor

Matusiak M., Bąkała M., Wojciechowski R., Ostalczyk P.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2020

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Vol. 68, nr 3

421--427

EN

The use of fractional-order calculus for system modeling is a good alternative to well-known classic integer-order methods, primarily due to the precision with which the modeled object may be mapped. In this study, we created integer and fractional discrete models of a real object – a highspeed brushless micro-motor. The accuracy of the models was verified and compared.

13

Aircraft system identification using simultaneous quantized harmonic input signals

Lichota P.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2020

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Vol. 68, nr 6

1351--1362

EN

In this paper, quanizted multisine inputs for a maneuver with simultaneous elevator, aileron and rudder deflections are presented. The inputs were designed for 9 quantization levels. A nonlinear aircraft model was exited with the designed inputs and its stability and control derivatives were identified. Time domain output error method with maximum likelihood principle and a linear aircraft model were used to perform parameter estimation. Visual match and relative standard deviations of the estimates were used to validate the results for each quantization level for clean signals and signals with measurement noise present in the data. The noise was included into both output and input signals. It was shown that it is possible to obtain accurate results when simultaneous flight controls deflections are quantized and noise is present in the data.

14

Parameter identification and estimation for stage-structured population models

Coll Carmen, Sánchez Elena

International Journal of Applied Mathematics and Computer Science

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2019

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Vol. 29, no. 2

327--336

EN

A stage-structured population model with unknown parameters is considered. Our purpose is to study the identifiability of the model and to develop a parameter estimation procedure. First, we analyze whether the parameter vector can or cannot uniquely be determined with the knowledge of the input-output behavior of the model. Second, we analyze how the information in the experimental data is translated into the parameters of the model. Furthermore, we propose a process to improve the recursive values of the parameters when successive observation data are considered. The structure of the state matrix leads to an analysis of the inverse of a sum of rank-one matrices.

15

An adaptive identification method based on the modulating functions technique and exact state observers for modeling and simulation of a nonlinear MISO glass melting process

Byrski Witold, Drapała Michał, Byrski Jędrzej

International Journal of Applied Mathematics and Computer Science

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2019

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Vol. 29, no. 4

739--757

EN

The paper presents new concepts of the identification method based on modulating functions and exact state observers with its application for identification of a real continuous-time industrial process. The method enables transformation of a system of differential equations into an algebraic one with the same parameters. Then, these parameters can be estimated using the least-squares approach. The main problem is the nonlinearity of the MISO process and its noticeable transport delays. It requires specific modifications to be introduced into the basic identification algorithm. The main goal of the method is to obtain on-line a temporary linear model of the process around the selected operating point, because fast methods for tuning PID controller parameters for such a model are well known. Hence, a special adaptive identification approach with a moving window is proposed, which involves using on-line registered input and output process data. An optimal identification method for a MISO model assuming decomposition to many inner SISO systems is presented. Additionally, a special version of the modulating functions method, in which both model parameters and unknown delays are identified, is tested on real data sets collected from a glass melting installation.

16

System Identification and Model Predictive Control of the Chatter Phenomenon in Turning Process

Karimipour Atiyeh, Emami Mohsen

Advances in Science and Technology. Research Journal

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2019

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Vol. 13, no 3

217--228

EN

Chatter is a series of unwanted and extreme vibrations which frequently happens during different machining processes and impose variety of adverse effects on the machine-tool and surface finish. Chatter has two main types namely forced-chatter and self-existed chatter. The forced-chatter has an external cause; however, self-exited chatter has no external stimuli, rather it is created due to the phase difference between the previous and current waves on the surface of the workpiece. Due to the self-generative nature of this type of chatter, its recognition and prevention is much more difficult. For preventing self-exited chatter its model should be available first. The chatter is usually simulated as a one degree of freedom mass-spring-damper model with unknown parameters that they should be determined somehow. In this paper, the parameters of the tool equation of motion i.e. mass, damping, and stiffness coefficients of the system are predicted through a wavelet-based method online, and then based on the achieved parameters, the system is controlled via Model Predictive Control (MPC) approach. For the validation, the algorithm is applied to 25 different experimental tests in which the acceleration of the tool and cutting force are measured via an accelerometer and a dynamometer. By investigation of the SLDs generated by the predicted parameters, the presented system identification method is validated. Also, it is shown that the chatter vibration is completely restrained by means of MPC. For investigation of the MPC performance, MPC algorithm is compared with PID controller and simulations has indicated a much stronger performance of MPC rather than PID controller in terms of vibration attenuation and control effort.

17

Spatial variability of long-term trends in significant wave height over the Gulf of Gdańsk using System Identification techniques

Badur J., Cieślikiewicz W.

Oceanological and Hydrobiological Studies

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2018

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Vol. 47, No. 2

190--201

EN

The significant wave height field over the Gulf of Gdańsk in the Baltic Sea is simulated back to the late 19th century using selected data-driven System Identification techniques (Takagi-Sugeno-Kang neuro-fuzzy system and non-linear optimization methods) and the NOAA/OAR/ESRL PSD Reanalysis 2 wind fields. Spatial variability of trends in the simulated dataset is briefly presented to show a cumulative “storminess” increase in the open, eastern part of the Gulf of Gdańsk and a decrease in the sheltered, western part of the Gulf.

18

The variability of the Atlantic meridional circulation since 1980, as hindcast by a data-driven nonlinear systems model

Ayala-Solares J. R., Wei H.-L., Bigg G. R.

Acta Geophysica

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2018

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Vol. 66, no. 4

683--695

EN

The Atlantic meridional overturning circulation (AMOC), an important component of the climate system, has only been directly measured since the RAPID array’s installation across the Atlantic at 26N in 2004. This has shown that the AMOC strength is highly variable on monthly timescales; however, after an abrupt, short-lived, halving of the strength of the AMOC early in 2010, its mean has remained * 15% below its pre-2010 level. To attempt to understand the reasons for this variability, we use a control systems identification approach to model the AMOC, with the RAPID data of 2004–2017 providing a trial and test data set. After testing to find the environmental variables, and systems model, that allow us to best match the RAPID observations, we reconstruct AMOC variation back to 1980. Our reconstruction suggests that there is inter-decadal variability in the strength of the AMOC, with periods of both weaker flow than recently, and flow strengths similar to the late 2000s, since 1980. Recent signs of weakening may therefore not reflect the beginning of a sustained decline. It is also shown that there may be predictive power for AMOC variability of around 6 months, as ocean density contrasts between the source and sink regions for the North Atlantic Drift, with lags up to 6 months, are found to be important components of the systems model.

19

System identification and tuning of wireless power transfer systems with multiple magnetically coupled resonators

Winges J., Rylander T., Petersson C., Ekman C., Johansson L.-Å., McKelvey T.

Transactions on Environment and Electrical Engineering

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2017

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Vol. 2, No. 2

86--92

EN

We present a procedure for system identification and tuning of a wireless power transfer (WPT) system with four magnetically coupled resonators, where each resonator consists of a coil and a capacitor bank. The system-identification procedure involves three main steps: 1) individual measurement of the capacitor banks in the system; 2) measurement of the frequency-dependent two-port impedance matrix of the magnetically coupled resonators; and 3) determining the inductance of all coils and their corresponding coupling coefficients using a Bayesian approach. The Bayesian approach involves solving an optimization problem where we minimize the mismatch between the measured and simulated impedance matrix together with a penalization term that incorporates information from a direct measurement procedure of the inductance and losses of the coils. This identification procedure yields an accurate system model which we use to tune the four capacitance values to recover high system-performance and account for, e.g., manufacturing tolerances and coil displacement. For a prototype WPT system, we achieve 3.3 kW power transfer with 91% system efficiency over an air-gap distance of approximately 20 cm.

20

Power spectrum optimization in the design of multisine manoeuvre for identification purposes

Lichota P., Szulczyk J., Noreña D. A., Vallejo Monsalve F. A.

Journal of Theoretical and Applied Mechanics

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2017

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Vol. 55 nr 4

1193--1203

EN

In this paper, two sets of multisine signals are designed for system identification purposes. The first one is obtained without any information about system dynamics. In the second case, the a priori information is given in terms of dimensional stability and control derivatives. Magnitude Bode plots are obtained to design the multisine power spectrum that is optimized afterwards. A genetic algorithm with linear ranking, uniform crossover and mutation operator has been employed for that purpose. Both designed manoeuvres are used to excite the aircraft model, and then system identification is performed. The estimated parameters are obtained by applying two methods: Equation Error and Output Error. The comparison of both investigated cases in terms of accuracy and manoeuvre time is presented afterwards.