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Affine Takagi-Sugeno fuzzy modelling algorithm by fuzzy c-regression models clustering with a novel cluster validity criterion

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IET CONTROL THEORY AND APPLICATIONS 2007年第5期1卷 1255-1265页

作者： Kung, C. C. Su, J. Y. Tatung Univ Dept Elect Engn Taipei Taiwan

An effective approach is developed to establish affine Takagi-Sugeno (T-S) fuzzy model for a given nonlinear system from its input-output data. Firstly, the fuzzy c-regression model (FCRM) clustering technique is applied to partition the product space of the given input-output data into hyper-plan-shaped clusters. Each cluster is essentially a basis of the fuzzy rule that describes the system behaviour, and the number of clusters is just the number of fuzzy rules. Particularly, a novel cluster validity criterion for FCRM is set up to choose the appropriate number of clusters (rules). Once the number of clusters is determined, the consequent parameters of each IF-THEN rule are directly obtained from the functional cluster representatives (affine linear functions). The antecedent fuzzy sets of each IF-THEN fuzzy rule are acquired by projecting the fuzzy partitions matrix U onto the axes of individual antecedent variable to obtain point-wise defined fuzzy sets and to approximate these point-wise defined fuzzy sets by normal bell-shaped membership functions. Additionally, a check and repartition algorithm is suggested to prevent the inappropriate premise structure where separate regions of data shared the same regression model. Finally, the gradient descent algorithm is included to adjust the fuzzy model precisely. An affine T-S fuzzy model with compact IF-THEN rules could thus be generated systematically. Several simulation examples are provided to demonstrate the accuracy and effectiveness of the affine T-S fuzzy modelling algorithm.

关键词： affineTakagi-Sugeno fuzzy modelling algorithm matrix algebra nonlinear system fuzzy control antecedent fuzzy sets pattern clustering input-output data fuzzy c-regression model clustering gradient methods regression analysis fuzzy set theory bell-shaped membership function hyper-plan-shaped clusters matrix partitioning cluster validity criterion gradient descent algorithm nonlinear systems if-then fuzzy rules

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data-Driven Model Order Reduction Simultaneously Matching Linear and Nonlinear Moments

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IEEE CONTROL SYSTEMS LETTERS 2024年 8卷 2331-2336页

作者： Mao, Junyu Scarciotti, Giordano Imperial Coll London Dept Elect & Elect Engn London SW7 2AZ England

In this letter, we address a model reduction problem in which the resulting reduced-order model simultaneously matches sets of linear and nonlinear moments. We propose a framework for approximating the reduced-order models from time-domain input-output data without requiring knowledge of the state-space representation of the system. The developed theory and the proposed data-driven procedure are demonstrated on a benchmark model showing matching of signals generated by a linear filter and a (nonlinear) Van der Pol oscillator, simultaneously.

关键词： Filters Mathematical models Signal generators Reduced order systems Interpolation Generators Steady-state Model reduction moment matching nonlinear interpolation time-domain input-output data

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The effect of industry delocalization on global energy use: A global sectoral perspective

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ENERGY ECONOMICS 2018年第Feb.期70卷 233-243页

作者： Forin, Silvia Radebach, Alexander Steckel, Jan Christoph Ward, Hauke Tech Univ Berlin Str 17Juni 135 D-10623 Berlin Germany Mercator Res Inst Global Commons & Climate Change Torgauer Str 12-15 D-10829 Berlin Germany Potsdam Inst Climate Impact Res Postfach 60 12 03 D-14412 Potsdam Germany

Sectoral production technologies differ largely across countries, so do sectoral energy intensities. Hence, shifts in production locations within global sectors, possibly caused by environmental regulations, are likely to have an impact on aggregated energy usage and emissions. Applying a Logarithmic Mean Divisia Index decomposition we decompose changes of sectoral energy use from 2001-2011 into three effects: (sectoral) value added, energy efficiency and delocalization, which in this paper is conceived as a structural effect within sectors, between regions. Our results show that although economic activity and technological progress dominate global energy use developments, for most sectors a delocalization towards less efficient production places is ongoing. It contributes to annual increases in energy use in the range of 1-6%. Especially, manufacturing sectors, which are among the most energy consuming sectors, reveal significant increases in energy usage due to delocalization since 2004. This development is accompanied by declining energy intensity improvement rates, indicating that delocalization induces second order effects. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Energy use Delocalization Index decomposition analysis input-output data Production technology

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Modelling of Grewia mollis Stem Bark Gum Extraction Yield Using Neuro-Fuzzy Technique

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INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH IN AFRICA 2018年 34卷 70-80页

作者： Oke, Emmanuel Olusola Adeyi, Oladayo Adeyi, Abiola John Adekunle, Kayode Feyisetan Micheal Okpara Univ Agr Chem Engn Dept Umudike Abia State Nigeria Landmark Univ Chem Engn Dept Omu Aran Kwara State Nigeria Ladoke Akintola Univ Technol Ogbomoso Mech Engn Dept Ogbomosho Oyo State Nigeria

In this paper, Adaptive Neuro-Fuzzy Inference System (ANFIS) was used to model and predict Grewia Polysaccharide Gum (GPG) extraction yield from Grewia mollis (GM) powder/water system. The data for modelling the process behaviour consisted of four inputs (process temperature, GM powder/water ratio, process time and pH) and GPG yield as the output. The gbell Membership Function (MF) was used for the fuzzification of input variables and hybrid algorithm was chosen for the learning method of input-output data of the process. Simulation study was conducted on the developed ANFIS architecture at different MFs and epoch numbers to establish minimum error and maximum correlation coefficient (R) of the model. From the results obtained, ANFIS can be used as a reliable tool for modelling and prediction of GPG powder/water extraction process behaviour. The R between the experimental and predicted values was found to be high (> 0.96) and the mean percentage error was less than 2%, showing the great efficiency and reliability of the developed model.

关键词： ANFIS Grewia mollis Process behaviour input-output data Grewia Polysaccharide Gum

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Reinforcement Learning based data-driven Optimal Control Strategy for Systems with Disturbance 12

Reinforcement Learning based Data-driven Optimal Control Str...

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IEEE 12th data Driven Control and Learning Systems Conference (DDCLS)

作者： Fan, Zhong-Xin Li, Shihua Liu, Rongjie Southeast Univ Sch Automat Nanjing 210096 Peoples R China Minist Educ Key Lab Measurement & Control Complex Syst Engn Nanjing 210096 Peoples R China Florida State Univ Dept Stat Tallahassee FL 32306 USA

ISBN: (纸本)9798350321050

This paper proposes a partially model-free optimal control strategy for a class of continuous-time systems in a datadriven way. Although a series of optimal control have achieving superior performance, the following challenges still exist: (i) The controller designed based on the nominal system is difficult to cope with sudden disturbances. (ii) Feedback control is highly dependent on system dynamics and generally requires full state information. A novel composite control method combining output feedback reinforcement learning and input-output disturbance observer for these two challenges is concluded in this paper. Firstly, an output feedback policy iteration (PI) algorithm is given to acquire the feedback gain iteratively. Simultaneously, the observer continuously provides estimates of the disturbance. System dynamic information and states information are not needed to be known in advance in our approach, thus offering a higher degree of robustness and practical implementation prospects. Finally, an example is given to show the effectiveness of the proposed controller.

关键词： Reinforcement learning data-driven input-output data disturbance observer adaptive dynamic programming output feedback

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Closed-loop Identification of Plant and Disturbance Models Based on Generalized Minimum Variance Evaluation

Closed-loop Identification of Plant and Disturbance Models B...

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IEEE Conference on Control and Applications (CCA)

作者： Uematsu, Ryota Masuda, Shiro Kano, Manabu Tokyo Metropolitan Univ Dept Management Syst Engn Grad Sch Syst Design 6-6 Asahigaoka Tokyo 1910065 Japan Kyoto Univ Dept Syst Sci Sakyo Ku Kyoto 6068501 Japan

ISBN: (纸本)9781479977871

A closed-loop identification method based on generalized minimum variance (GMV) evaluation is proposed. Parameters of plant and disturbance models can be estimated simultaneously based on the data-driven control technique that minimizes the variance of the generalized output. This feature distinguishes the proposed method from conventional closedloop identification methods. In particular, an advantage of the proposed method is ease of use like data-driven controller design methods. For the purpose of identification, we introduce a new variance criterion, which is derived from a set of inputoutput data generated by stochastic disturbance. The paper proves that the optimization of the proposed criterion results in the unique optimal solution which corresponds to the true plant and disturbance model parameters. The proposed method is applied to datasets obtained from a continuous stirred tank reactor (CSTR), which is operated around an unstable steady state. The result illustrates the effectiveness of the proposed closed-loop identification method.

关键词： closed loop systems control system synthesis identification optimisation stochastic systems CSTR GMV evaluation closed-loop identification continuous stirred tank reactor data-driven control technique data-driven controller design methods disturbance model parameters generalized minimum variance evaluation generalized output variance input-output data optimal solution optimization plant parameters stochastic control theory stochastic disturbance unstable steady state variance criterion Closed loop systems data models Delays Mathematical model Optimization Polynomials Closed loop systems variance criterion Continuously stirred tank reactors Disturbance model stochastic disturbance Stochastic control theory optimal solution data models control system synthesis plant parameters stochastic systems Polynomial input/output data Mathematical Model

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The evolving geography of production hubs and regional value chains across East Asia: Trade in value-added

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JOURNAL OF WORLD BUSINESS 2015年第3期50卷 404-416页

作者： Suder, Gabriele Liesch, Peter W. Inomata, Satoshi Mihailova, Irina Meng, Bo Univ Melbourne Int Relat Melbourne Business Sch Parkville Vic 3010 Australia Univ Queensland UQ Business Sch Brisbane Qld 4072 Australia JETRO IDE JETRO Inst Developing Econ Chiba Chiba 2618545 Japan Aalto Univ Sch Business Dept Management & Int Business Aalto 00076 Finland Japan External Trade Org IDE JETRO Inst Developing Econ Ctr Dev Studies Int Input Output Anal Studies Grp Chiba Chiba 2618545 Japan

The interdependence of regional trade and production networks has important implications for national prosperity, regional stability and the internationalization of production. We ask: What are the locational patterns of trade in value-added in East Asia and how are these patterns changing over time? The disintermediation of value chains and the externalization of business activity create hubs of capability and extend value chains between countries. We adopt input-output techniques to analyze the evolution of production networks in East Asia over the period 1990-2005 from a value chain perspective. A high density of cross-border interaction is reported alongside changing geographic dynamics, and an informal integration derived from intermediates trade in value-addition. The locational interdependence of developed and less-developed countries across the region leverages on the heterogeneity of location-specific advantages within the region. (C) 2014 Elsevier Inc. All rights reserved.

关键词： Regional integration Production networks input-output data Trade in value-added East Asia

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Global economic crisis and developing countries: Role of vertical specialization

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South Asia Economic Journal 2010年第1期11卷 1-20页

作者： Pitigala, Nihal Nihal Pitigala is an independent scholar. Email:

After a remarkable increase in the previous decade, world trade has been experiencing a dramatic fall in recent months. Vertical production chains have become a 'propagation mechanism' for these dramatic shifts. This article is based on recent research on vertical production chains and its determinants (Pitigala 2008) and highlights the implications of the global financial crisis on vertical production chains, with reference to the South Asia region. The results suggest that traditional policy barriers such as tariffs appear to have become less important for vertical trade;instead political risk, infrastructure and finance are more strongly associated with the growth of vertical specialization. The extent of vertical production chains and the weakening of the financial markets that support them explain the rapid contraction during the ongoing crisis. The effects may be long lasting as producers are forced to reconstruct not just weak, but broken links in their supply chains.

关键词： Financial Crisis Gravity Model input-output data South Asia Trade Vertical Specialization

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Generating detailed commodity forecasts from a computable general equilibrium model

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INTERNATIONAL JOURNAL OF FORECASTING 1997年第2期13卷 223-236页

作者： Adams, PD Dixon, PB MONASH UNIV CTR POLICY STUDIESCLAYTONVIC 3168AUSTRALIA

The largest computable general equilibrium (CGE) models currently in operation produce forecasts for about 100 commodities (goods and services). This level of detail may seem overwhelming to macroeconomists but is often inadequate for micro planning. For example, a forecast for business services (a typical commodity at the 100-level) is of marginal interest in planning educational programs for sub-categories of business services such as accountancy, advertising and architecture. As a step towards generating information for micro planning, this paper describes a tops-down method for disaggregating CGE forecasts. The method relies on detailed sales data often collected by input-output sections of statistical agencies. An application is reported in which forecasts from a 114-commodity CGE model are disaggregated into forecasts for 780 commodities. Within each of the 114 core commodities, differences in prospects are forecast for sub-commodities reflecting differences in their sales patterns and in the degree to which they face import competition.

关键词： computable general equilibrium models disaggregated economic forecasting input-output data microeconomic forecasting

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A Support Vector Machine-based Method for LPV-ARX Identification with Noisy Scheduling Parameters 13

A Support Vector Machine-based Method for LPV-ARX Identifica...

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13th European Control Conference (ECC)

作者： Abbasi, Farshid Mohammadpour, Javad Toth, Roland Meskin, Nader Univ Georgia Coll Engn Complex Syst Control Lab Athens GA 30602 USA

ISBN: (纸本)9783952426913

In this paper, we present a method that utilizes support vector machines (SVM) to identify linear parameter-varying (LPV) auto-regressive exogenous input (ARX) models corrupted by not only noise, but also uncertainties in the LPV scheduling variables. The proposed method employs SVM and takes advantage of the so-called "kernel trick" to allow for the identification of the LPV-ARX model structure solely based on the input-output data. The objective function, as defined in this paper, allows to consider uncertainties related to the LPV scheduling parameters, and hence results in a new formulation that provides a more accurate estimation of the LPV model in the presence of scheduling uncertainties. We further demonstrate the viability of the proposed LPV identification method through numerical examples, where we show that higher best fit rate (BFR) can be achieved under realistic noise conditions using the proposed method compared to the method initially proposed in [6].

关键词： autoregressive processes control system analysis computing identification linear systems scheduling support vector machines BFR LPV scheduling parameters LPV-ARX identification LPV-ARX model structure SVM auto-regressive exogenous input models best fit rate input-output data kernel trick noisy scheduling parameters support vector machine-based method Cost function Kernel Mathematical model Noise Noise measurement Support vector machines Uncertainty Support Vector Network control system analysis computing Foot Rot autoregressive processes Noise measurement Noise Cost functions Linear system Mathematical Model Uncertainty Kernel input/output data

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