Showing papers on "Transfer function published in 2009"

Feedback Control Theory

Abstract: In any system, if there exists a linear relationship between two variables, then it is said that it is a linear system.

Frequency Response Analysis of Current Controllers for Selective Harmonic Compensation in Active Power Filters

Abstract: This paper compares four current control structures for selective harmonic compensation in active power filters. All controllers under scrutiny perform the harmonic compensation by using arrays of resonant controllers, one for the fundamental and one for each harmonic of interest, in order to achieve zero phase shift and unity gain in the closed-loop transfer function for selected harmonics. The complete current controller is the superposition of all individual harmonic controllers and may be implemented in various reference frames. The analysis is focused on the comparison of harmonic and total closed-loop transfer functions for each controller. Analytical similarities and differences between schemes in terms of frequency response characteristics are emphasized. It is concluded that three of them have identical harmonic behavior despite the fact that their implementation is significantly different. It emerges that the fourth one has superior behavior and robustness and can stably work at higher frequencies than the others. Theoretical findings and analysis are supported by comparative experimental results on a 7-kVA laboratory setup. The highest harmonic frequency that can be stably compensated with each control method has been determined, indicating significant differences in the control performance.

Feedforward control of piezoactuators in atomic force microscope systems

Abstract: This article describes an inversion-based feedforward approach to compensate for dynamic and hysteresis effects in piezoactuators with application to AFM technology. To handle the coupled behavior of dynamics and hysteresis, a cascade model is presented to enable the application of inversion-based feedforward control. The dynamics, which include vibration and creep, are modeled using linear transfer functions. A frequency-based method is used to invert the linear model to find an input that compensates for vibration and creep. The inverse is noncausal for nonminimum-phase systems. Similarly, the hysteresis is handled by an inverse-Preisach model. To avoid the complexity of finding the inverse-Preisach model, high- gain feedback control can be used to linearize the system's behavior. A feedforward input is then combined with the feedback system to compensate for the linear dynamics to achieve high-speed AFM imaging. Finally, recent efforts in feedforward control for an SPM application including the use of iteration to handle hysteresis as well as uncertainties and variations in the system model is discussed.

PI state space current control of grid- connected PWM converters with LCL filters

Abstract: Design and analysis of PI state space control for grid-connected PWM converters with LCL filters based on pole placement approach is addressed. State space control offers almost full controllability of system dynamic. However, pole placement design is difficult and usually requires much experience. In this paper a suitable pole placement strategy is proposed, that ensures fulfilling the requirements, which are commonly specified with respect to rise time, overshoot, and proper resonance damping. Controller parameter expressions are derived in terms of system parameters and specified poles and zeros. Hence straightforward controller tuning for a particular system setting is possible. Performance is analyzed by means of transfer function-based calculations, simulations with Matlab, and experimental tests.

The general theory of phase shifting algorithms

Abstract: We have been reporting several new techniques of analysis and synthesis applied to Phase Shifting Interferometry (PSI). These works are based upon the Frequency Transfer Function (FTF) and how this new tool of analysis and synthesis in PSI may be applied to obtain very general results, among them; rotational invariant spectrum; complex PSI algorithms synthesis based on simpler first and second order quadrature filters; more accurate formulae for estimating the detuning error; output-power phase noise estimation. We have made our cases exposing these aspects of PSI separately. Now in the light of a better understanding provided by our past works we present and expand in a more coherent and holistic way the general theory of PSI algorithms. We are also providing herein new material not reported before. These new results are on; a well defined way to combine PSI algorithms and recursive linear PSI algorithms to obtain resonant quadrature filters.

Monitoring Impact Events Using a System-Identification Method

Abstract: An inverse method based on a system-identification technique for identifying impact events on a complex structure with built-in sensors is presented. The method using the transfer functions in the system-identification technique identifies the location and force time history of an impact event on a structure without the need of constructing a full- scale accurate structural model or of acquiring excessive training data on the structure, such as neural-network techniques. The system transfer functions for the entire structure are constructed by two sequential procedures: 1) limited impact tests at selected points to establish the system transfer functions from the selected points to a sensor on the structure and 2) an interpolation function approach based on a linear finite element to approximate the system transfer functions from a point inside four neighboring selected points to the sensor. Comprehensive tests with various impact situations verified the accuracy of load and position predictions by the proposed method.

Generation of Random Road Profiles

Abstract: In this work we review two of the most commonly adopted methods, namely shaping filter and sinusoidal approximation, for generating one-dimensional random road profiles, that are used in the simulation of a quarter car (or half car) vehicle suspension control system. The major contribution of this work is the following: for the shaping filter method, it is found that the time constant of the first order transfer function generating the road profile is independent of the grade of road. While for the sinusoidal approximation method, a detail derivation of the amplitude of each sinusoidal function is re-derived for completeness.

Impact of Nonlinear LED Transfer Function on Discrete Multitone Modulation: Analytical Approach

Abstract: Light-emitting diodes constitute a low-cost choice for optical transmitters in medium-bit-rate optical links. An example for the latter is local-area networks. However, one of the disadvantageous properties of light-emitting diodes is their nonlinear characteristic, which may limit the data transmission performance of the system, especially in the case of multiple subcarrier modulation, which is starting to attract attention in various applications, such as visible-light communications and data transmission over polymer optical fibers. In this paper, the influence of the nonlinear transfer function of the light-emitting diodes on discrete multitone modulation is studied. The transfer function describes the dependence of the emitted optical power on the driving current. Analytical expressions for an idealized link were derived, and these equations allow the estimation of the power of the noise-like, nonlinear crosstalk between the orthogonal subcarriers. The crosstalk components of the quadrature and in-phase subcarrier components were found to be independent and approximately normally distributed. Using these results, the influence of light-emitting-diode nonlinearity on the performance of the system was investigated. The main finding was that systems using a small number of subcarriers and/or high QAM level exhibit a large signal-to-noise-ratio penalty due to the nonlinear crosstalk. The model was applied to systems with white and resonant-cavity light-emitting diodes. It is shown that the nonlinearity may severely limit the performance of the system, particularly in the case of resonant-cavity light-emitting diodes, which exhibit a strong nonlinear behavior.

Digital simulation of scalar optical diffraction: revisiting chirp function sampling criteria and consequences.

Abstract: Accurate simulation of scalar optical diffraction requires consideration of the sampling requirement for the phase chirp function that appears in the Fresnel diffraction expression. We describe three sampling regimes for FFT-based propagation approaches: ideally sampled, oversampled, and undersampled. Ideal sampling, where the chirp and its FFT both have values that match analytic chirp expressions, usually provides the most accurate results but can be difficult to realize in practical simulations. Under- or oversampling leads to a reduction in the available source plane support size, the available source bandwidth, or the available observation support size, depending on the approach and simulation scenario. We discuss three Fresnel propagation approaches: the impulse response/transfer function (angular spectrum) method, the single FFT (direct) method, and the two-step method. With illustrations and simulation examples we show the form of the sampled chirp functions and their discrete transforms, common relationships between the three methods under ideal sampling conditions, and define conditions and consequences to be considered when using nonideal sampling. The analysis is extended to describe the sampling limitations for the more exact Rayleigh-Sommerfeld diffraction solution.

Process Identification and PID Control

Abstract: Preface. Part One Basics of Process Dynamics. 1 Mathematical Representations of Linear Processes. 1.1 Introduction to Process Control and Identification. 1.2 Properties of Linear Processes. 1.3 Laplace Transform. 1.4 Transfer Function and State-Space Systems. Problems. 2 Simulations. 2.1 Simulating Processes Composed of Differential Equations. 2.2 Simulating Processes Including Time Delay. 2.3 Simulating Closed-Loop Control Systems. 2.4 Useful Numerical Analysis Methods. Problems. 3 Dynamic Behavior of Linear Processes. 3.1 Low-Order Plus Time-Delay Processes. 3.2 Process Reaction Curve Method. 3.3 Poles and Zeroes. 3.4 Block Diagram. 3.5 Frequency Responses. Problems. Part Two Process Control. 4 Proportional-Integral-Derivative Control. 4.1 Structure of Proportional-Integral-Derivative Controllers and Implementation in Computers/Microprocessors. 4.2 Roles of Three Parts of Proportional-Integral-Derivative Controllers. 4.3 Integral Windup. 4.4 Commercial Proportional-Integral-Derivative Controllers. Problems. 5 Proportional-Integral-Derivative Controller Tuning. 5.1 Trial-and-Error Tuning. 5.2 Simple Process Identification Methods. 5.3 Ziegler-Nichols Tuning Rule. 5.4 Internal Model Control Tuning Rule. 5.5 Integral of the Time-Weighted Absolute Value of the Error Tunning Rule for a First-Order Plus Time-Delay Model (ITAE-1). 5.6 Integral of the Time-Weighted Absolute Value of the Error Tunning Rule for a Second-Order Plus Time-Delay Model (ITAE-2). 5.7 Optimal Gain Margin Tuning Rule for an Unstable Second-Order Plus Time-Delay Model (OGM-unstable). 5.8 Model Reduction Method for Proportional-Integral-Derivative Controller Tuning. 5.9 Consideration of Modeling Errors. 5.10 Concluding Remarks. Problems. 6 Dynamic Behavior of Closed-Loop Control Systems. 6.1 Closed-Loop Transfer Function and Characteristic Equation. 6.2 Bode Stability Criterion. 6.3 Nyquist Stability Criterion. 6.4 Gain Margin and Phase Margin. Problems. 7 Enhanced Control Strategies. 7.1 Cascade Control. 7.2 Time-Delay Compensators. 7.3 Gain Scheduling. 7.4 Proportional-Integral-Derivative Control using Internal Feedback Loop. Problems. Part Three Process Identification. 8 Process Identification Methods for Frequency Response Models. 8.1 Fourier Series. 8.2 Frequency Response Analysis and Autotuning. 8.3 Describing Function Analysis. 8.4 Fourier Analysis. 8.5 Modified Fourier Transform. 8.6 Frequency Response Analysis with Integrals. Problems. 9 Process Identification Methods for Continuous-Time Differential Equation Models. 9.1 Identification Methods Using Integral Transforms. 9.2 Prediction Error Identification Method. Problems. 10 Process Identification Methods for Discrete-Time Difference Equation Models. 10.1 Prediction Model: Autoregressive Exogenous Input Model and Output Error Model. 10.2 Prediction Error Identification Method for the Autoregressive Exogenous Input Model. 10.3 Prediction Error Identification Method for the Output Error Model. 10.4 Concluding Remarks. Problems. 11 Model Conversion from Discrete-Time to Continuous-Time Linear Models. 11.1 Transfer Function of Discrete-Time Processes. 11.2 Frequency Responses of Discrete-Time Processes and Model Conversion. Problems. Part Four Process Activation. 12 Relay Feedback Methods. 12.1 Conventional Relay Feedback Methods. 12.2 Relay Feedback Method to Reject Static Disturbances. 12.3 Relay Feedback Method under Nonlinearity and Static Disturbances. 12.4 Relay Feedback Method for a Large Range of Operation. Problems. 13 Modifications of Relay Feedback Methods. 13.1 Process Activation Method Using Pulse Signals. 13.2 Process Activation Method Using Sine Signals. Problems. Appendix Use of Virtual Control System. A.1 Setup of the Virtual Control System. A.2 Examples. Index.

Relative Transfer Function Identification Using Convolutive Transfer Function Approximation

Abstract: In this paper, we present a relative transfer function (RTF) identification method for speech sources in reverberant environments. The proposed method is based on the convolutive transfer function (CTF) approximation, which enables to represent a linear convolution in the time domain as a linear convolution in the short-time Fourier transform (STFT) domain. Unlike the restrictive and commonly used multiplicative transfer function (MTF) approximation, which becomes more accurate when the length of a time frame increases relative to the length of the impulse response, the CTF approximation enables representation of long impulse responses using short time frames. We develop an unbiased RTF estimator that exploits the nonstationarity and presence probability of the speech signal and derive an analytic expression for the estimator variance. Experimental results show that the proposed method is advantageous compared to common RTF identification methods in various acoustic environments, especially when identifying long RTFs typical to real rooms.

Structuring Feature Space: A Non-Parametric Method for Volumetric Transfer Function Generation

Abstract: The use of multi-dimensional transfer functions for direct volume rendering has been shown to be an effective means of extracting materials and their boundaries for both scalar and multivariate data. The most common multi-dimensional transfer function consists of a two-dimensional (2D) histogram with axes representing a subset of the feature space (e.g., value vs. value gradient magnitude), with each entry in the 2D histogram being the number of voxels at a given feature space pair. Users then assign color and opacity to the voxel distributions within the given feature space through the use of interactive widgets (e.g., box, circular, triangular selection). Unfortunately, such tools lead users through a trial-and-error approach as they assess which data values within the feature space map to a given area of interest within the volumetric space. In this work, we propose the addition of non-parametric clustering within the transfer function feature space in order to extract patterns and guide transfer function generation. We apply a non-parametric kernel density estimation to group voxels of similar features within the 2D histogram. These groups are then binned and colored based on their estimated density, and the user may interactively grow and shrink the binned regions to explore feature boundaries and extract regions of interest. We also extend this scheme to temporal volumetric data in which time steps of 2D histograms are composited into a histogram volume. A three-dimensional (3D) density estimation is then applied, and users can explore regions within the feature space across time without adjusting the transfer function at each time step. Our work enables users to effectively explore the structures found within a feature space of the volume and provide a context in which the user can understand how these structures relate to their volumetric data. We provide tools for enhanced exploration and manipulation of the transfer function, and we show that the initial transfer function generation serves as a reasonable base for volumetric rendering, reducing the trial-and-error overhead typically found in transfer function design.

Method for adaptive control and equalization of electroacoustic channels

Abstract: An electroacoustic channel soundfield is altered. An audio signal is applied by an electromechanical transducer to an acoustic space, causing air pressure changes therein. Another audio signal is obtained by a second electromechanical transducer, responsive to air pressure changes in the acoustic space. A transfer function estimate of the electroacoustic channel is established, responsive to the second audio signal and part of the first audio signal. The transfer function estimate is derived to be adaptive to temporal variations in the electroacoustic channel transfer function. Filters are obtained with transfer functions based on the transfer function estimate. Part of the first audio signal is filtered therewith.

Feedback stabilization of a class of evolution equations with delay

Abstract: In this paper, we characterize the stabilization of some delay systems. The proof of the main result uses the method introduced in Ammari and Tucsnak (ESAIM COCV 6:361–386, 2001) where the exponential stability for the closed loop problem is reduced to an observability estimate for the corresponding uncontrolled system combined with a boundedness property of the transfer function of the associated open loop system.

A New Training Approach for Parametric Modeling of Microwave Passive Components Using Combined Neural Networks and Transfer Functions

Abstract: This paper presents a novel technique to develop combined neural network and transfer function models for parametric modeling of passive components. In this technique, the neural network is trained to map geometrical variables onto coefficients of transfer functions. A major advance is achieved in resolving the discontinuity problem of numerical solutions of the coefficients with respect to the geometrical variables. Minimum orders of transfer functions for different regions of geometrical parameter space are identified. Our investigations show that varied orders used for different regions result in the discontinuity of coefficients. The gaps between orders are bridged by a new order-changing module, which guarantees the continuity of coefficients and simultaneously maintains the modeling accuracy through a neural network optimization process. This technique is also expanded to include bilinear transfer functions. Once trained, the model provides accurate and fast prediction of the electromagnetic behavior of passive components with geometrical parameters as variables. Compared to conventional training methods, the proposed method allows better accuracy in challenging applications involving high-order transfer functions, wide frequency range, and large geometrical variations. Three examples including parametric modeling of slotted patch antennas, bandstop microstrip filters, and bandpass coupled-line filters are examined to demonstrate the validity of this technique.

Compressive sensing for sparsely excited speech signals

Abstract: Compressive sensing (CS) has been proposed for signals with sparsity in a linear transform domain. We explore a signal dependent unknown linear transform, namely the impulse response matrix operating on a sparse excitation, as in the linear model of speech production, for recovering compressive sensed speech. Since the linear transform is signal dependent and unknown, unlike the standard CS formulation, a codebook of transfer functions is proposed in a matching pursuit (MP) framework for CS recovery. It is found that MP is efficient and effective to recover CS encoded speech as well as jointly estimate the linear model. Moderate number of CS measurements and low order sparsity estimate will result in MP converge to the same linear transform as direct VQ of the LP vector derived from the original signal. There is also high positive correlation between signal domain approximation and CS measurement domain approximation for a large variety of speech spectra.

Automatic Transfer Function Generation Using Contour Tree Controlled Residue Flow Model and Color Harmonics

Abstract: Transfer functions facilitate the volumetric data visualization by assigning optical properties to various data features and scalar values. Automation of transfer function specifications still remains a challenge in volume rendering. This paper presents an approach for automating transfer function generations by utilizing topological attributes derived from the contour tree of a volume. The contour tree acts as a visual index to volume segments, and captures associated topological attributes involved in volumetric data. A residue flow model based on Darcy's law is employed to control distributions of opacity between branches of the contour tree. Topological attributes are also used to control color selection in a perceptual color space and create harmonic color transfer functions. The generated transfer functions can depict inclusion relationship between structures and maximize opacity and color differences between them. The proposed approach allows efficient automation of transfer function generations, and exploration on the data to be carried out based on controlling of opacity residue flow rate instead of complex low-level transfer function parameter adjustments. Experiments on various data sets demonstrate the practical use of our approach in transfer function generations.

Bottom-up transfer function generator for broadband PLC statistical channel modeling

Abstract: We follow a bottom-up approach for modelling the channel transfer function aiming at realizing a fast statistical channel simulator. The simulator is derived from transmission line theory. It computes the transfer function via a fast procedure that calculates the voltage ratio between the receiver port and the transmitter port given a real or randomly generated network topology. The approach allows not only taking into account the cable characteristics, the number and length of branches, but also the effect of loads. In particular the effect of time-variant loads that cause the channel transfer function to be time-variant.

Convolutive Transfer Function Generalized Sidelobe Canceler

Abstract: In this paper, we propose a convolutive transfer function generalized sidelobe canceler (CTF-GSC), which is an adaptive beamformer designed for multichannel speech enhancement in reverberant environments. Using a complete system representation in the short-time Fourier transform (STFT) domain, we formulate a constrained minimization problem of total output noise power subject to the constraint that the signal component of the output is the desired signal, up to some prespecified filter. Then, we employ the general sidelobe canceler (GSC) structure to transform the problem into an equivalent unconstrained form by decoupling the constraint and the minimization. The CTF-GSC is obtained by applying a convolutive transfer function (CTF) approximation on the GSC scheme, which is a more accurate and a less restrictive than a multiplicative transfer function (MTF) approximation. Experimental results demonstrate that the proposed beamformer outperforms the transfer function GSC (TF-GSC) in reverberant environments and achieves both improved noise reduction and reduced speech distortion.

Visual control of stable and unstable loads: what is the feedback delay and extent of linear time-invariant control?

Abstract: Human balance is commonly described using linear-time-invariant (LTI) models. The feedback time delay determines the position of balance in the motor-control hierarchy. The extent of LTI control illuminates the automaticity of the control process. Using non-parametric analysis, we measured the feedback delay, extent of LTI control and visuo-motor transfer function in six randomly disturbed, visuo-manual compensatory tracking tasks analogous to standing with small mechanical perturbations and purely visual information. The delay depended primarily on load order (2nd: 220 ± 30 ms, 1st: 124 ± 20 ms), and secondarily on visual magnification (extent 2nd: 34 ms, 1st: 8 ms) and was unaffected by load stability. LTI control explained 1st order and stable loads relatively well. For unstable (85% passive stabilisation) 2nd order loads, LTI control accounted for 40% of manual output at 0.1 Hz decreasing below 10% as frequency increased through the important 1–3 Hz region where manual power and visuo-motor gain are high. Visual control of unstable 2nd order loads incurs substantial feedback delays and the control process will not be LTI. These features do not result from exclusive use of visual inputs because we found much shorter delays and a greater degree of LTI control when subjects visually controlled a 1st order load. Rather, these results suggest that delay and variability are inevitable when more flexible, intentional mechanisms are required to control 2nd order unstable loads. The high variability of quiet standing, and movement generally, may be indicative of flexible, variable delay, intentional mechanisms rather than the automatic LTI responses usually reported in response to large perturbations.

LTI Systems with Generalized Frequency Variables: A Unified Framework for Homogeneous Multi-agent Dynamical Systems

Abstract: A linear system with a generalized frequency variable denoted by G(s) is a system which is given by replacing the variable ‘s’ in the original transfer function G0(s) with a rational fu...

Electromechanical mode shape estimation based on transfer function identification using PMU measurements

Abstract: Power system mode shapes are a key indication of how dynamic components participate in low-frequency oscillations. Traditionally, mode shapes are calculated from a linearized dynamic model. For large-scale power systems, obtaining accurate dynamic models is very difficult. Therefore, measurement-based mode shape estimation methods have certain advantages, especially for the application of real-time small signal stability monitoring. In this paper, a measurement-based mode shape identification method is proposed. The general relationship between transfer function (TF) and mode shape is derived. As an example, a least square (LS) method is implemented to estimate mode shape using an autoregressive exogenous (ARX) model. The performance of the proposed method is evaluated by Monte-Carlo studies using simulation data from a 17-machine model. The results indicate the validity of the proposed method in estimating mode shapes with reasonably good accuracy.

Modeling And Control Of Engineering Systems

Abstract: Modeling and Control of Engineering Systems Control Engineering Application Areas Importance of Modeling History of Control Engineering Organization of the Book Modeling of Dynamic Systems Dynamic Systems Dynamic Models Lumped Elements and Analogies Analytical Model Development Model Linearization Model Linearization Nonlinear State-Space Models Nonlinear Electrical Elements Linearization Using Experimental Operating Curves Linear Graphs Variables and Sign Convention Linear Graph Elements Linear Graph Equations State Models from Linear Graphs Miscellaneous Examples Transfer-Function and Frequency-Domain Models Laplace and Fourier Transforms Transfer Function Frequency Domain Models Transfer Functions of Electro-Mechanical Systems Equivalent Circuits and Linear Graph Reduction Block Diagrams and State-Space Models Response Analysis and Simulation Analytical Solution First-Order Systems Second-Order Systems Forced Response of a Damped Oscillator Response Using Laplace Transform Determination of ICs for Step Response Computer Simulation Control System Structure and Performance Control System Structure Control System Performance Control Schemes Steady-State Error and Integral Control System Type and Error Constants Control System Sensitivity Stability and Root Locus Method Stablility Routh-Hurwitz Criterion Root Locus Method Stability in the Frequency Domain Bode Diagram Using Asymptotes Nyquist Stability Criterion Nichols Chart Controller Design and Tuning Controller Design and Tuning Conventional Time-Domain Design Compensator Design in the Frequency Domain Design Using Root Locus Controller Tuning Digital Control Digital Control Signal Sampling and Control Bandwidth Digital Control Using z-Transform Digital Compensation Advanced Control Modern Control Time Response System Stability Controllability and Observability Modal Control Optimal Control Linear Quadratic Regulator (LQR) Other Advanced Control Techniques Fuzzy Logic Control Control System Instrumentation Control System Instrumentation Component Interconnection Motion Sensors Stepper Motors dc Motors Control Experiments Using LabVIEW Appendix A: Transform Techniques Appendix B: Software Tools Appendix C: Review of Linear Algebra Index Problems appear at the end of each chapter.

Fractional-order integral and derivative controller for temperature profile tracking

Abstract: This paper establishes a new strategy to tune a fractional order integral and derivative (ID) controller satisfying gain and phase margins based on Bode’s ideal transfer function as a reference model, for a temperature profile tracking. A systematic analysis resulting in a non-linear equation relating user-defined gain and phase margins to the fractional order controller is derived. The closed-loop system designed has a feature of robustness to gain variations with step responses exhibiting a nearly iso-damping property. This paper aims to apply the analytical tuning procedure to control the heat flow systems at selected points in Quanser experimental platform. Thus, the main purpose of this paper is to examine performances of two different fractional order controllers in temperature profile tracking. From experimental comparisons with the traditional PI/PID controller based on Ziegler-Nichols’ tuning method, it will be shown that the proposed methodologies are specifically beneficial in controlling temperature in time-delay heat flow systems.

On-line identification and control of pneumatic servo drives via a mixed-reality environment

Abstract: This paper presents a method to identify and control electro-pneumatic servo drives in a real-time environment. Acquiring the system’s transfer function accurately can be difficult for nonlinear systems. This causes a great difficulty in servo-pneumatic system modeling and control. In order to avoid the complexity associated with nonlinear system modeling, a mixed-reality environment (MRE) is employed to identify the transfer function of the system using a recursive least squares (RLS) algorithm based on the auto-regressive moving-average (ARMA) model. On-line system identification can be conducted effectively and efficiently using the proposed method. The advantages of the proposed method include high accuracy in the identified system, low cost, and time reduction in tuning the controller parameters. Furthermore, the proposed method allows for on-line system control using different control schemes. The results obtained from the on-line experimental measured data are used to determine a discrete transfer function of the system. The best performance results are obtained using a fourth-order model with one-step prediction.