Pendulum System with Relative Degree Two

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Two van der Pol oscillators coupled via a bath (2)

Model description: 

Consider the model described in Two van der Pol oscillators coupled via a bath (1).

The current model is using a slightly different notation:

$$\begin{align*} \dot{\xi}_{1}^{1} &= \dot{x}_1 \\ \dot{\xi}_{2}^{1} &= \dot{x}_2 \\ \dot{\xi}_{1}^{2} &= \dot{x}_3 \\ \dot{\xi}_{2}^{2} &= \dot{x}_4 \\ \dot{\eta}_{1} &= \dot{x}_5 \end{align*}$$

Note that this system is decouplable by static state feedback because the decoupling matrix of this system is

$D_{1}(\xi,\eta)=\left[\matrix{1 &0 \cr 0 &1}\right]$

The authors have proposed the following Yuz and Goodwin type approximate model which is more accurate than the Euler model.

$$\begin{align*} x_{1,k+1}&=x_{1,k}+T_{x_{2,k}}+\frac{T^2}{2}\{u_{1,k}-x_{1,k}+\epsilon\{1-x_{1,k}^{2}\}x_{2,k}+k(x_{5,k}-x_{1,k})\} \\ x_{2,k+1}&=x_{2,k}+T\{u_{1,k}-x_{1,k}+\epsilon\{1-x_{1,k}^{2}\}x_{2,k}+k(x_{5,k}-x_{1,k})\} \\ x_{3,k+1}&=x_{3,k}+T_{x_{4,k}}+\frac{T^2}{2}\{u_{2,k}-x_{1,k}+\epsilon\{1-x_{3,k}^{2}\}x_{4,k}+k(x_{5,k}-x_{1,k})\} \\ x_{4,k+1}&=x_{4,k}+T_{x_{4,k}}+T\{u_{2,k}-x_{2,k}+\epsilon\{1-x_{3,k}^{2}\}x_{4,k}+k(x_{5,k}-x_{3,k})\} \\ x_{5,k+1}&=x_{5,k}+T\{k(x_{1,k}-x_{5,k})+k(x_{3,k}-x_{5,k})\} \\ y_{1,k}&=x_{1,k} \\ y_{2,k}&=x_{3,k} \end{align*}$$

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Publication details: 

TitleSampled-data model for nonlinear coupled Van der Pol oscillators
Publication TypeConference Paper
Year of Publication2011
AuthorsNishi, M., Ishitobi M., and Kunimatsu S.
Conference Name2011 Proceedings of SICE Annual Conference (SICE)
Date Published09/2011
PublisherIEEE
ISBN Number978-1-4577-0714-8
Accession Number12354559
Keywordsclosed loop systems, continuous time systems, control system synthesis, MIMO systems, nonlinear control systems, relaxation oscillators, sampled data systems, stability
AbstractFor sampled-data controller design of nonlinear continuous-time systems, it is important to derive a good approximate sampled-data model because the exact sampled-data model for nonlinear systems is often unavailable to the controller designers. In the multi-input multi-output (MIMO) case, the authors have proposed an accurate approximate model which includes extra zero dynamics corresponding to the relative degree of the continuous-time nonlinear system. Such extra zero dynamics are called sampling zero dynamics. A more accurate sampled-data model is, however, required when the relative degrees of a continuous-time nonlinear plant are two. The reason is that the closed-loop system becomes unstable when the more accurate sampled-data model has unstable sampling zero dynamics. This paper derives the sampling zero dynamics of the more accurate sampled-data model for coupled Van der Pol oscillators and analyzes the relationship between the stability of the closed-loop system and the stability of the sampling zero dynamics of a proposed model.
URLhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6060620&queryText%3DSampled-data+model+for+nonlinear+coupled+Van+der+Pol+oscillators

Point-Mass Satellite Moving in a Plane (2)

Model description: 

This is a more complex model of the system in Point-Mass Satellite Moving in a Plane (1).

$$\begin{align*} \dot{y}_{1} &=x_{1,2}+\psi(y_{2}) \\ \dot{x}_{1,2} &=u_{1} \\ \dot{y}_{2} &=u_{2}. \end{align*}$$

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Publication details: 

TitleGlobal Tracking via Output Feedback for Nonlinear MIMO Systems
Publication TypeJournal Article
Year of Publication2011
AuthorsKvaternik, K., and Lynch A.F.
JournalIEEE Transactions on Automatic Control
Volume56
Start Page2179
Issue9
Pagination2179-2184
Date Published05/2011
ISSN0018-9286
Accession Number12216413
Keywordscontrol system synthesis, feedback, MIMO systems, nonlinear control systems, observers, tracking
AbstractIn this note we present a constructive method for the design of global asymptotic tracking control for a class of MIMO nonlinear systems by output feedback. The class of systems considered is a special case of those in nonlinear observer form and coincides with the Output Feedback Form when there is only one input and one output. This approach generalizes a SISO method which uses filtered transformations and backstepping. The technique presented here may be useful in accommodating subsystem coupling in other MIMO design contexts. We demonstrate our method by example and observe several interesting features that distinguish it from the SISO case.
DOI10.1109/TAC.2011.2158134

Point-Mass Satellite Moving in a Plane (1)

Model description: 

The point-mass satellite moving in a plane, subject to an inverse-square law force field

$$\begin{align*} \dot{r} &=v \\ \dot{v} &=r\omega^{2}-a_{1}\frac{1}{r^2}+a_{2}u_{1} \\ \dot{\phi} &=\omega \\ \dot{\omega} &=-2\frac{v\omega}{r}+a_{2}\frac{1}{r}u_2, \end{align*}$$

where the states are: the satellite's radial position $r < 0$, its radial velocity $v$, its angular position $\phi$ and its angular velocity $\omega$. The satellite is equipped with a radial thruster $u_1$ and a tangential thruster $u_2$, and the known constant model parameters $a_1$ and $a_2$ are related to the strength of the force field and the mass of the satellite. If the outputs are taken as $y_1=\sin{\phi}$ and $y_2=\cos{\phi}$, then the transformation $z_{1,1}=r\sin{\phi}$, $z_{1,2}=v\sin{\phi}+r\omega\sin{\phi}$, $z_{2,1} = r\cos{\phi}$ and $z_{2,2}=v\cos{\phi} - r\omega\cos{\phi}$, brings the system into the NOF

$$\begin{align*} \dot{z}_{1,1} &=z_{1,2} \\ \dot{z}_{1,2} &=-a_{1}\frac{y_1}{\left(y_{1}^{2}+y_{2}^{2}\right)^{3/2}}+\bar{u}_{1} \\ \dot{z}_{2,1} &=z_{2,2} \\ \dot{z}_{2,2} &=-a_{1}\frac{y_2}{\left(y_{1}^{2}+y_{2}^{2}\right)^{3/2}}+\bar{u}_{2}, \end{align*}$$

where $\bar{u}_1 = a_2 ((u_1y_1 + u_2y_2)/(y_1^2 + y_2^2)^{1/2})$ and $\bar{u}_2 = a_2 ((u_1y_2 + u_2y_1)/(y_1^2 + y_2^2)^{1/2})$.

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4

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Publication details: 

TitleGlobal Tracking via Output Feedback for Nonlinear MIMO Systems
Publication TypeJournal Article
Year of Publication2011
AuthorsKvaternik, K., and Lynch A.F.
JournalIEEE Transactions on Automatic Control
Volume56
Start Page2179
Issue9
Pagination2179-2184
Date Published05/2011
ISSN0018-9286
Accession Number12216413
Keywordscontrol system synthesis, feedback, MIMO systems, nonlinear control systems, observers, tracking
AbstractIn this note we present a constructive method for the design of global asymptotic tracking control for a class of MIMO nonlinear systems by output feedback. The class of systems considered is a special case of those in nonlinear observer form and coincides with the Output Feedback Form when there is only one input and one output. This approach generalizes a SISO method which uses filtered transformations and backstepping. The technique presented here may be useful in accommodating subsystem coupling in other MIMO design contexts. We demonstrate our method by example and observe several interesting features that distinguish it from the SISO case.
DOI10.1109/TAC.2011.2158134

Mathematical Model of the PM Stepper Motor

Model description: 

The equations describing the stepped motor in the attached image are given as follows:

$$\begin{align*} \dot{x}_1 &= -K_1x_1 + K_2x_3\sin{(K_5x_4)} + u_1 \\ \dot{x}_2 &= -K_1x_2 + K_2x_3\sin{(K_5x_4)} + u_2 \\ \dot{x}_3 &= -K_3x_1\sin{(K_5x_4)} + K_3x_2\cos{(K_5x_4)} - K_4x_3 - K_6\sin{(4K_5x_4)} - \tau_L/J \\ \dot{x}_4 &= x_3, \end{align*}$$

where $K_1 = R/L$, $K_2 = K_m/L$, $K_3=K_m/J$, $K_4 = B/J$, $K_5 = N_r$, $K_6 = K_D/J$, $K_5 = N_r$, $K_6 = K_D/J$, $u_1=v_a/L$.

$i_a, i_b$, and $v_a, v_b$ currents and voltages in phase $A$ and $B$, respectively.
$L$ and $R$ self-inductance and resistance of each phase winding
$K_m$ motor torque constant
$N_r$ number of rotor teeth
$J$ rotor inertia
$B$ vicious friction constant
$\omega$ rotor speed
$\theta$ motor position
$\tau_L$ Load torque

The term $K_D\sin{(4N_r\theta)}$ represents the detent torque due to the permanent rotor magnet interacting with the magnetic materia of the stator poles. $K_D$ is typically 5% to 10% of the value of $K_mi_0$, where $i_0$ is the rated current.

The state variables $x_1, x_2, x_3$ and $x_4$ are assigned by $x^{\mathrm T}=[i_a, i_b, i_c, i_d]^{\mathrm T}.$

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4

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Attachment: 

Publication details: 

TitlePosition Control of a PM Stepper Motor by Exact Linearization
Publication TypeJournal Article
Year of Publication1991
AuthorsZribi, M., and Chiasson J.
JournalIEEE Transactions on Automatic Control
Volume36
Start Page620
Issue5
Pagination620-625
Date Published05/1991
ISSN0018-9286
Accession Number3939472
Keywordsfeedback, linearisation techniques, machine control, permanent magnet motors, position control, state estimation, stepping motors
AbstractThe authors consider the position control of a permanent magnet (PM) stepper motor using the exact linearization method. This nonlinear controller takes into account the full dynamics of the stepper motor. In particular, the phase shift between voltage and current in each phase is automatically taken into account. The feedback linearization controller makes the stepper motor into a fast accurate positioning system. The authors consider the feedback linearization technique for the PM stepper motor and show, when the detent torque is neglected, how it quite naturally leads to the well-known DQ transformation of electric machine theory. The authors indicate how constant load torques may be asymptotically rejected by using a nonlinear observer
DOI10.1109/9.76368

Pendulum System with Relative Degree Two

Model description: 

Consider the pendulum system with the relative degree two

$$\begin{align*} \dot{x}_{1} &= x_{2}\\ \dot{x}_{2} &= -cx_{2}-d\sin x_{1}+u \\ y &= x_{1} \end{align*}$$

with $c > 0$.

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2

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Publication details: 

TitleNonlinear sampled-data models and zero dynamics
Publication TypeConference Paper
Year of Publication2009
AuthorsNishi, M., Ishitobi M., and Kunimatsu S.
Conference NameInternational Conference on Networking, Sensing and Control, 2009. ICNSC '09.
Date Published03/2009
PublisherIEEE
Conference LocationOkayama
ISBN Number978-1-4244-3491-6
Accession Number10646009
Keywordsclosed loop systems, continuous time systems, control system synthesis, nonlinear control systems, poles and zeros, sampled data systems, stability
AbstractOne of the approaches to sampled-data controller design for nonlinear continuous-time systems consists of obtaining an appropriate model and then proceeding to design a controller for the model. Hence, it is important to derive a good approximate sampled-data model because the exact sampled-data model for nonlinear systems is often unavailable to the controller designers. Recently, Yuz and Goodwin have proposed an accurate approximate model which includes extra zero dynamics corresponding to the relative degree of the continuous-time nonlinear system. Such extra zero dynamics are called sampling zero dynamics. A more accurate sampled-data model is, however, required when the relative degree of a continuous-time nonlinear plant is two. The reason is that the closed-loop system becomes unstable when the more accurate sampled-data model has unstable sampling zero dynamics and a controller design method based on cancellation of the zero dynamics is applied. This paper derives the sampling zero dynamics of the more accurate sampled-data model and shows a condition which assures the stability of the sampling zero dynamics of the model.
DOI10.1109/ICNSC.2009.4919304

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