A Two-Mass System

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Coupled electric drives

Model description: 

This particular laboratory-scale process simulates the actual industrial problems in tension and speed controls as they occur in magnetic tape drives, textile machines, paper mills, strip metal production plants, etc. To simulate these problems. the coupled electric drives consists of two similar servo-motors which drive a jockey pulley via a continuous flexible belt (see attached image).The jockey pulley assembly constitutes a simulated work station. The basic control problem is to regulate the belt speed and tension by varying the two servo-motor torque.

The structure of the transfer function matrix model (numerator and denominator orders of each transfer function) have been determined from the theoretical modelling of the coupled electric drive system which has given

$$\begin{bmatrix} Y_1(s)\\ Y_2(s) \end{bmatrix} =G(s) \begin{bmatrix} U_1(s)\\ U_2(s) \end{bmatrix}$$

with

$ G(s) = \begin{bmatrix} \dfrac{b_{1,1,0}}{s^2+a_{11}s+a_{12}} & \dfrac{b_{1,2,0}}{s^2+a_{11}s+a_{12}}\\ \dfrac{b_{2,1,0}s+b_{2,1,1}}{s^3+a_{21}s^2+a_{22}s+a_{23}} & \dfrac{b_{2,2,0}}{s^3+a_{21}s^2+a_{22}s+a_{23}} \end{bmatrix} $

The inputs $U(s)$ to the system are the drive voltages to the servo-motor power amplifiers. The outputs $Y_1(s)$ and $Y_2(s)$ are the jockey pulley velocity and the belt tension respectively.

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TitleA new bias-compensating least-squares method for continuous-time MIMO system identification applied to a laboratory-scale process
Publication TypeConference Paper
Year of Publication1994
AuthorsGarnier, H., Sibille P., and Nguyen H.L.
Conference NameProceedings of the Third IEEE Conference on Control Applications, 1994.
Date Published08/1994
PublisherIEEE
Conference LocationGlasgow
ISBN Number0-7803-1872-2
Accession Number4880903
Keywordscontinuous time systems, identification, least squares approximations, MIMO systems, process control, stochastic processes, transfer function matrices
AbstractThis paper presents a new bias-compensating least-squares method for the identification of continuous-time transfer function matrix model of multi-input multi-output (MIMO) systems. The proposed method uses the generalised Poisson moment functional approach for handling time derivatives and is applied to the identification of a laboratory-scale process which simulates industrial material transport control problems. Model validation results show the potentiality of the proposed method in practical applications
DOI10.1109/CCA.1994.381459

A linear system

Model description: 

Consider a linear system represented by the transfer function

$$G(s)=\dfrac{c}{s(s+a)}$$

where $a$ and $c>0$ are unknowns constants, and the reference model

$$G_m(s)=\dfrac{\omega^2}{s^2 + 2\zeta\omega s + \omega^2}.$$

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2

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TitleAdaptive output feedback control of nonlinear systems represented by input-output models
Publication TypeJournal Article
Year of Publication1996
AuthorsKhalil, H.K.
JournalIEEE Transactions on Automatic Control
Volume41
Start Page177
Issue2
Pagination177-188
Date Published02/1996
ISSN0018-9286
Accession Number5202146
Keywordsadaptive control, linearisation techniques, nonlinear control systems, state feedback
AbstractWe consider a single-input-single-output nonlinear system which can be represented globally by an input-output model. The system is input-output linearizable by feedback and is required to satisfy a minimum phase condition. The nonlinearities are not required to satisfy any global growth condition. The model depends linearly on unknown parameters which belong to a known compact convex set. We design a semiglobal adaptive output feedback controller which ensures that the output of the system tracks any given reference signal which is bounded and has bounded derivatives up to the nth order, where n is the order of the system. The reference signal and its derivatives are assumed to belong to a known compact set. It is also assumed to be sufficiently rich to satisfy a persistence of excitation condition. The design process is simple. First we assume that the output and its derivatives are available for feedback and design the adaptive controller as a state feedback controller in appropriate coordinates. Then we saturate the controller outside a domain of interest and use a high-gain observer to estimate the derivatives of the output. We prove, via asymptotic analysis, that when the speed of the high-gain observer is sufficiently high, the adaptive output feedback controller recovers the performance achieved under the state feedback one
DOI10.1109/9.481517

A Three-Mass System

Model description: 

The transfer function of the three-mass-system is much more complex than it is for one dominant elasticity (two-mass-system).

$${G_{\rm mech}}(s) = \underbrace{{\dfrac{1} {T_{ \Sigma} \cdot s}}}_{G_{\rm rs}(s)} \cdot \underbrace{ \dfrac{ a_{7} \cdot s^{4} + a_{6} \cdot s^{3}+a_{5} \cdot s^{2} + a_{4} \cdot s + 1}{a_{3} \cdot s^{4} + a_{2} \cdot s^{3}+ a_{1} \cdot s^{2} + a_{4} \cdot s + 1}} _{G_{\rm nrs}(s)}$$

with

$T_{\Sigma} = T_{\rm M} + T_{{\rm L}1} + T_{{\rm L}2}$

and

$\begin{align*} a_{1}&=d_{1}d_{2}T_{{\rm C}1}T_{{\rm C}2}+T_{{\rm L}2}\left(T_{\rm M}+T_{{ \rm L}1}\right) \cdot \frac{T_{C2}}{T_{\Sigma }}+T_{\rm M}\left(T_{{\rm L}1}+T_{{\rm L}2}\right) \cdot \frac{T_{{\rm C}1}}{T_{\Sigma}} \\ a_{2}&=\frac{T_{{\rm C}1}T_{{\rm C}2}}{T_{\Sigma}}\cdot\left(d_{1}T_{{\rm L}2}\left(T_{\rm M}+T_{{\rm L}1}\right)+d_{2}T_{\rm M} \left(T_{{\rm L}1}+T_{{\rm L}2}\right)\right) \\ a_{3}&=\frac{T_{\rm M}T_{{\rm L}1}T_{{\rm L}2}T_{{\rm C}1}T_{{\rm C}2}}{T_{\Sigma}} \\ a_{4}&=d_{1}T_{{\rm C}1}+d_{2}T_{{\rm C}2} \\ a_{5}&=d_{1}d_{2}T_{{\rm C}1}T_{{\rm C}2}+T_{{\rm L}2}T_{{\rm C}2}+\left(T_{{\rm L}1}+T_{{\rm L}2}\right)\cdot T_{{\rm C}1} \\ a_{6}&=\left(\left(d_{1}+d_{2}\right)T_{{\rm L}2}+d_{2}T_{{\rm L}1}\right)\cdot T_{{\rm C}1}T_{{\rm C}2} \\ a_{7}&=T_{{\rm L}1}T_{{\rm L}2}T_{{\rm C}1}T_{{\rm C}2}. \end{align*}$

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TitleApplication of the Welch-Method for the Identification of Two- and Three-Mass-Systems
Publication TypeJournal Article
Year of Publication2008
AuthorsVillwock, S., and Pacas M.
JournalIEEE Transactions on Industrial Electronics
Volume55
Start Page457
Issue1
Pagination457-466
Date Published01/2008
ISSN0278-0046
Accession Number9756566
Keywordselectric drives, frequency response, identification, machine control, spectral analysis
AbstractThis paper deals with the measurement of the frequency response of the mechanical part of a drive for the parameter identification of a plant. The system is stimulated by pseudorandom binary signals. The measurement of the frequency response is part of a system identification procedure being carried out during an automatic commissioning of the drive. For the calculation of the frequency response of the mechanics, the Welch-method is applied for spectral analysis. The Welch-method is known from the fields of communications and measurement engineering. This paper addresses the application of this powerful method for the identification of electrical drives. Investigations have pointed out that the pure utilization of conventional identification strategies does not yield satisfying experimental results. Experimental results presented in this paper point out clearly the efficiency and flexibility of the proposed Welch-method. This paper contains many practical aspects and realization details that are important for their implementation on industrial systems. Although in principle, commercial software tools can be utilized for identifying the parameters of the plant, this paper addresses the implementation of the necessary identification algorithms on the embedded control electronics of the drives. The utilization of the Levenberg-Marquardt-algorithm yields excellent results for the identified parameters on the basis of the measured frequency response data.
DOI10.1109/TIE.2007.909753

A Two-Mass System

Model description: 

The transfer function of a nonrigid mechanical system with two concentrated masses is given by

$$G_{\rm mech}(s) = \underbrace{ \dfrac{1}{s \cdot \left(T_{\rm M} + T_{\rm L}\right)} }_{G_{\rm rs}(s)} \cdot \underbrace{ \dfrac{T_{ \rm L} \cdot T_{\rm C} \cdot s^{2} + d \cdot T_{\rm C} s + 1} {\dfrac{ T_{\rm L} \cdot T_{\rm C} \cdot T_{\rm M}}{T_{\rm M} + T_{\rm L}} \cdot s^{2} + d \cdot T_{\rm C} \cdot s + 1}}_{G_{\rm nrs}(s)}.$$

$T_M$ and $T_L$ are the run-up times of the motor and the load. The nonrigid shaft of the two-mass-configuration is modeled as a damper-spring-system. $T_C$ is the normalized spring-constant and $d$ is the related damping of the spring.

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Publication details: 

TitleApplication of the Welch-Method for the Identification of Two- and Three-Mass-Systems
Publication TypeJournal Article
Year of Publication2008
AuthorsVillwock, S., and Pacas M.
JournalIEEE Transactions on Industrial Electronics
Volume55
Start Page457
Issue1
Pagination457-466
Date Published01/2008
ISSN0278-0046
Accession Number9756566
Keywordselectric drives, frequency response, identification, machine control, spectral analysis
AbstractThis paper deals with the measurement of the frequency response of the mechanical part of a drive for the parameter identification of a plant. The system is stimulated by pseudorandom binary signals. The measurement of the frequency response is part of a system identification procedure being carried out during an automatic commissioning of the drive. For the calculation of the frequency response of the mechanics, the Welch-method is applied for spectral analysis. The Welch-method is known from the fields of communications and measurement engineering. This paper addresses the application of this powerful method for the identification of electrical drives. Investigations have pointed out that the pure utilization of conventional identification strategies does not yield satisfying experimental results. Experimental results presented in this paper point out clearly the efficiency and flexibility of the proposed Welch-method. This paper contains many practical aspects and realization details that are important for their implementation on industrial systems. Although in principle, commercial software tools can be utilized for identifying the parameters of the plant, this paper addresses the implementation of the necessary identification algorithms on the embedded control electronics of the drives. The utilization of the Levenberg-Marquardt-algorithm yields excellent results for the identified parameters on the basis of the measured frequency response data.
DOI10.1109/TIE.2007.909753