Model Output Error
Search All Support Resources Support Documentation MathWorks Search MathWorks.com MathWorks Documentation Support Documentation Toggle navigation Trial Software Product Updates Documentation Home System output error model system identification Identification Toolbox Examples Functions and Other Reference Release Notes PDF Documentation pem matlab Linear Model Identification Input-Output Polynomial Models System Identification Toolbox Functions oe On this page Syntax Description Input matlab tfest Arguments Name-Value Pair Arguments Output Arguments Examples Estimate Continuous-Time Model Using Frequency Response Estimate Output-Error Model Using Regularization Estimate Model Using Band-Limited Discrete-Time Frequency-Domain Data Alternatives More About arx model Output-Error (OE) Model Continuous-Time, Output-Error Model Tips Algorithms See Also This is machine translation Translated by Mouse over text to see original. Click the button below to return to the English verison of the page. Back to English × Translate This Page Select Language Bulgarian Catalan Chinese Simplified Chinese Traditional Czech Danish Dutch English Estonian Finnish French German Greek Haitian Creole Hindi Hmong Daw Hungarian Indonesian Italian Japanese Korean Latvian Lithuanian Malay Maltese Norwegian Polish Portuguese Romanian Russian Slovak Slovenian Spanish Swedish Thai Turkish Ukrainian Vietnamese Welsh MathWorks Machine Translation The automated translation of this page is provided by a general purpose third party translator tool. MathWorks does not warrant, and disclaims all liability for, the accuracy, suitability, or fitness for purpose of the translation. Translate oeEstimate Output-Error polynomial model using time or frequency domain datacollapse all in page Syntaxsys = oe(data,[nb nf nk])
sys = oe(data,[nb nf nk],Name,Value)
sys = oe(data,init_sys)
sys = oe(data,___,opt)
Descriptionsys
= oe(data,[nb nf nk]) estimates an Output-Error model, sys, represented by:y(t)=B(q)F(q)u(t−nk)+e(t)y(t) is the output, u(t) is the input, and e(t) is the error.sys is estimated for the time- or frequency-domain, measured input-output data, data. The orders, [nb nf nk], parameterize the estimated polynomial.sys
= oe(data,[nb nf nk],Name,Value) specifies model structure attributes using additional options specified by one or more Name,Value pair arguments.sys
= oe(data,init_sys)
and Box-Jenkins. The General Structure A general input-output linear model for a single-output system with input u and output y can be written Here ui denotes input #i, and A, Bi, C, D, and Fi, are polynomials in the shift operator (z or q). (Don't get intimidated by this: It is just a compact way of writing difference equations; see below.) The general structure is defined by giving the time-delays nk and the orders of these polynomials (i.e., the number of poles and https://www.mathworks.com/help/ident/ref/oe.html zeros of the dynamic model from u to y, as well as of the disturbance model from e to y). The Special Cases Most often the choices are confined to one of the following special cases. ARX: ARMAX: OE: (Output-Error) BJ: (Box-Jenkins) The "shift operator polynomials" are just compact ways of writing difference equations. For example the ARMAX http://www-rohan.sdsu.edu/doc/matlab/toolbox/ident/ch2gui21.html model in longhand would be Note that A(q) corresponds to poles that are common between the dynamic model and the disturbance model (useful if disturbances enter the system "close to" the input). Likewise determines the poles that are unique for the dynamics from input # i, and D(q) the poles that are unique for the disturbances. The reason for introducing all these model variants is to provide for flexibility in the disturbance description and to allow for common or different poles (dynamics) for the different inputs. Entering the Model Structure Use the Structure pop-up menu in the Parametric Models dialog to choose between the ARX, ARMAX, Output-Error, and Box-Jenkins structures. Note that if the Working Data set has several outputs, only the first choice is available. For time series (data with no input signal) only AR and ARMA are available among these choices. These are the time series counterparts of ARX and ARMAX. The orders of the polynomials are selected by the pop-up menus in the Order Editor dialog window, or by direc
Please note that Internet Explorer version 8.x will not be supported as of January http://www.sciencedirect.com/science/article/pii/S0895717711005875 1, 2016. Please refer to this blog post for more information. Close ScienceDirectJournalsBooksRegisterSign inSign in using your ScienceDirect credentialsUsernamePasswordRemember meForgotten username or password?Sign in via your institutionOpenAthens loginOther institution loginHelpJournalsBooksRegisterSign inHelpcloseSign in using your ScienceDirect credentialsUsernamePasswordRemember meForgotten username or password?Sign in via your institutionOpenAthens loginOther institution login Download PDF Opens output error in a new window. Article suggestions will be shown in a dialog on return to ScienceDirect. Help Direct export Export file RIS(for EndNote, Reference Manager, ProCite) BibTeX Text RefWorks Direct Export Content Citation Only Citation and Abstract Advanced search JavaScript is disabled on your model output error browser. Please enable JavaScript to use all the features on this page. JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. This page uses JavaScript to progressively load the article content as a user scrolls. Click the View full text link to bypass dynamically loaded article content. View full text Mathematical and Computer ModellingVolume 55, Issues 3–4, February 2012, Pages 1151–1159 Two-stage recursive least squares parameter estimation algorithm for output error modelsHonghong Duana, , Jie Jiab, , Ruifeng Dingc, b, , a Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi214122, PR Chinab Institute of Aerospace Information and Security Technology, Nanchang Hangkong University, Nanchang330063, PR Chinac School of Internet of Things Engineering, Jiangnan University, Wuxi214122, PR ChinaReceived 12 July 2011, Revised 28 September 2011, Accepted 28 September 2011, Available online 3 October 201
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