TY - JOUR

T1 - A Matlab/Simulink toolbox for inversion of local linear model trees

AU - Nentwig, M.

AU - Mercorelli, P.

N1 - Export Date: 22 May 2012 Source: Scopus Language of Original Document: English Correspondence Address: Nentwig, M.; University of Applied Sciences Ostfalia, Department of Automotive Engineering, Robert-Koch-Platz 10 - 14, 38440 Wolfsburg, Germany; email: mail@mnentwig.de References: Toepfer, A., Fink, A., (2003), Technical report - on the inversion of nonlinear modelsIsermann, R., Fink, A., Toepfer, S., Neuro and neurofuzzy identification for model-based control (2001) IFAC Workshop on Advanced Fuzzy/Neural Control, Valencia, Spain, Q, pp. 111-116; Isermann, R., Fink, A., Toepfer, S., Nonlinear modelbased control with local linear neuro-fuzzy models (2003) Archive of Applied Mechanics, 72 (11-12), pp. 911-922; Fink, A., Nelles, O., Nonlinear internal model control based on local linear neural networks (2001) IEEE Systems, Man, and Cybernetics, Tucson, , USA; Mercorelli, P., An optimal minimum phase approximating pd regulator for robust control of a throttle plate (2006) 45th IEEE Conference on Decision and Control (CDC2006), , San Diego (USA), 13th-15th December; Nelles, O., (1999) Nonlinear System Identification with Local Linear Neuro-Fuzzy Models, , Shaker Verlag; Isermann, R., Nelles, O., Fink, A., Local linear model trees (lolimot) toolbox for nonlinear system identification (2000) 12th IFAC Symposium on System Identification (SYSID), , Santa Barbara, USA

PY - 2010/2

Y1 - 2010/2

N2 - Models in the form of characteristic diagrams or more specifically, in the form of engine operating maps are mostly used in the automobile industry. This yields a large amount of measurements and involves the use of advanced instrumentations. This paper shows a developed software environment, namely a toolbox for the program Matlab/Simulink developed by company Mathworks. The name of the toolbox is "Inversion of the Local Linear Model Trees" and it basically consists of a local inversion of the Local Linear Model Trees (LOLIMOT). The importance of the inversion in control problems is widely known. Neural networks are a very effective and popular tools mostly used for modeling. The inversion of a neural network produces real possibilities to involve the networks in the control problem schemes. The developed toolbox is explained with the help of diagrams and GUI structure from Matlab which tend to clarify the idea of the program and its structure. The presentation is organized as a short tutorial of the toolbox, so that a potential user can directly understand how to access it. Nevertheless, formal mathematical equations, concerning the neural networks and membership functions, need to be explained together with the LOLIMOT structure. To validate and to clarify the explained toolbox, an example from a system used in the automobile industry is briefly shown.

AB - Models in the form of characteristic diagrams or more specifically, in the form of engine operating maps are mostly used in the automobile industry. This yields a large amount of measurements and involves the use of advanced instrumentations. This paper shows a developed software environment, namely a toolbox for the program Matlab/Simulink developed by company Mathworks. The name of the toolbox is "Inversion of the Local Linear Model Trees" and it basically consists of a local inversion of the Local Linear Model Trees (LOLIMOT). The importance of the inversion in control problems is widely known. Neural networks are a very effective and popular tools mostly used for modeling. The inversion of a neural network produces real possibilities to involve the networks in the control problem schemes. The developed toolbox is explained with the help of diagrams and GUI structure from Matlab which tend to clarify the idea of the program and its structure. The presentation is organized as a short tutorial of the toolbox, so that a potential user can directly understand how to access it. Nevertheless, formal mathematical equations, concerning the neural networks and membership functions, need to be explained together with the LOLIMOT structure. To validate and to clarify the explained toolbox, an example from a system used in the automobile industry is briefly shown.

KW - Engineering

KW - Inversion

KW - Local linear model trees (LOLIMOT)

KW - Matlab/Simulink

KW - Neuro-fuzzy identification

KW - Nonlinear systems

UR - http://www.scopus.com/inward/record.url?scp=77956486937&partnerID=8YFLogxK

M3 - Journal articles

VL - 37

SP - 19

EP - 26

JO - IAENG International Journal of Computer Science

JF - IAENG International Journal of Computer Science

SN - 1819-656X

IS - 1

ER -