A smooth nonlinear system (1)

Deprecation warning

This website is now archived. Please check out the new website for Centre for Intelligent Systems which includes both A-Lab Control Systems Research lab and Re:creation XR lab.

However, the Dynamic System Model Database can still be used and may be updated in the future.

Bilinear system

Model description: 

The time-invariant bilinear system is given by

$$Y(t) = 1.5X(t) + 1.2X(t-1) - 0.2X(t-2) + 0.7X(t-1)Y(t-1) - 0.1X(t-2)Y(t-2) + \epsilon(t),$$

where $A=0, \alpha=0, B=\begin{bmatrix}1.5 &1.2 &-0.2\end{bmatrix}, C = \begin{bmatrix}0.7 &0 &-0.1\end{bmatrix}$. Note that $\Theta = \begin{bmatrix}B & C\end{bmatrix}^{\mathrm T}.$

Type: 

Form: 

Model order: 

2

Time domain: 

Linearity: 

Publication details: 

TitleIdentification of bilinear systems using Bayesian inference
Publication TypeConference Paper
Year of Publication1998
AuthorsMeddeb, S., Tourneret J.Y., and Castanie F.
Conference NameProceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, 1998.
Date Published05/1998
PublisherIEEE
Conference LocationSeattle, WA
ISBN Number0-7803-4428-6
Accession Number6053933
KeywordsBayes methods, bilinear systems, discrete time systems, inference mechanisms, Markov processes, Monte Carlo methods, parameter estimation, signal sampling
AbstractA large class of nonlinear phenomena can be described using bilinear systems. Such systems are very attractive since they usually require few parameters, to approximate most nonlinearities (compared to other systems). This paper addresses the problems of bilinear system identicalness using Bayesian inference. The Gibbs sampler is used to estimate the bilinear system parameters, from measurements of the system input and output signals
DOI10.1109/ICASSP.1998.681761

Bilinear descriptor system

Model description: 

Consider the following bilinear descriptor system:

$$\begin{pmatrix} 1 & -1\\ 0 & 0 \end{pmatrix}x_{k+1}=\begin{pmatrix} -0.5 & 1\\ -1 & 0 \end{pmatrix}x_{k}+\begin{pmatrix} 0.5 & 0.25\\ -1 & 0.5 \end{pmatrix}x_{k}u_{k}.$$

Type: 

Form: 

Time domain: 

Linearity: 

Publication details: 

TitleStabilization of Discrete-time Bilinear Descriptor Systems
Publication TypeConference Paper
Year of Publication2006
AuthorsLu, Guoping, Zhang Xiaomei, Tang Hongji, and Zhou Lei
Conference NameThe Sixth World Congress on Intelligent Control and Automation, 2006.
Date Published06/2006
PublisherIEEE
Conference LocationDalian, China
ISBN Number1-4244-0332-4
Accession Number9187947
Keywordsasymptotic stability, bilinear systems, closed loop systems, discrete time systems, state feedback
AbstractThis paper discusses global asymptotic stabilization of a class of discrete-time bilinear descriptor systems. By means of LaSalle invariant principle and the implicit function theorem, a sufficient condition is presented to guarantee the uniqueness and existence of solution and the global asymptotic stability of the resulting closed-loop systems simultaneously. Finally, the effectiveness of the proposed approach is illustrated by a numerical example
DOI10.1109/WCICA.2006.1712293

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

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

Type: 

Form: 

Model order: 

2

Time domain: 

Linearity: 

Attachment: 

Publication details: 

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
Issue2
Start Page177
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 smooth nonlinear system (2)

Model description: 

The system

$$\begin{align*} \dot{x}_1 & = x_4^2 + x_3^3 + u_1 + au_2 \\ \dot{x}_2 & = x_3 \\ \dot{x}_3 & = \sin{x_4}+\cos{x_1}+bu_1 + u_2 \\ \dot{x}_4 & = -x_4 \\ y_1 &= x_1 \\ y_2 &=x_2. \end{align*}$$

Type: 

Form: 

Model order: 

4

Time domain: 

Linearity: 

Publication details: 

TitleInput-output models for a class of nonlinear systems
Publication TypeConference Paper
Year of Publication1997
AuthorsAtassi, A.N., and Khalil H.K.
Conference NameProceedings of the 36th IEEE Conference on Decision and Control, 1997.
Date Published12/1997
PublisherIEEE
Conference LocationSan Diego, CA
ISBN Number0-7803-4187-2
Accession Number5863848
Keywordsnonlinear control systems
AbstractWe investigate the possibility of having an input-output model that has a specific structure for multivariable input-output linearizable systems
DOI10.1109/CDC.1997.657850

A smooth nonlinear system (1)

Model description: 

The system

$$\begin{align*} \dot{x}_1 & = x_2 \\ \dot{x}_2 & = x_3^2 + x_4 + u_1 + au_2 \\ \dot{x}_3 & = x_4 + bu_1 + u_2 \\ \dot{x}_4 & = -x_4 \\ y_1 &= x_1 \\ y_2 &=x_3 \end{align*}$$

with $ab \neq 1$, has a well-defined vector relative degree (2, 1) and a nonsingular decoupling matrix $\begin{bmatrix} 1 & a \\ b & 1 \end{bmatrix}$.

Type: 

Form: 

Model order: 

4

Time domain: 

Linearity: 

Publication details: 

TitleInput-output models for a class of nonlinear systems
Publication TypeConference Paper
Year of Publication1997
AuthorsAtassi, A.N., and Khalil H.K.
Conference NameProceedings of the 36th IEEE Conference on Decision and Control, 1997.
Date Published12/1997
PublisherIEEE
Conference LocationSan Diego, CA
ISBN Number0-7803-4187-2
Accession Number5863848
Keywordsnonlinear control systems
AbstractWe investigate the possibility of having an input-output model that has a specific structure for multivariable input-output linearizable systems
DOI10.1109/CDC.1997.657850

Pages