Application of gap metric to model bank determination in multilinear model approach

Du, Junping; Song, Chunyue; Li, Ping

doi:10.1016/j.jprocont.2008.04.015

Cited by 69 publications

(79 citation statements)

References 20 publications

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“…Recently, a nonlinearity measure via gap metric is proposed to assess the nonlinearity of the nonlinear system [20], [21]. Grid the operating space of the forcedcirculation byNoperating points, and the nonlinearity measure is defined as [21] (27) where L i N L, L j N L are linearization systems of the nonlinear plant at the i -th and the j -th operating point, respectively.…”

Section: ) Gap-metric-based Nonlinearity Measure For the Forcedcircumentioning

confidence: 99%

“…Grid the operating space of the forcedcirculation byNoperating points, and the nonlinearity measure is defined as [21] (27) where L i N L, L j N L are linearization systems of the nonlinear plant at the i -th and the j -th operating point, respectively.…”

Section: ) Gap-metric-based Nonlinearity Measure For the Forcedcircumentioning

confidence: 99%

“…In this case, the linearized system of the nonlinear system would behave quite differently, namely, the dynamics of the nonlinear system in the operating space are rather inconsistent. A single linear controller may not be sufficient to achieve satisfactory performance for the nonlinear system over the entire the operating range, and a nonlinear controller is necessary [21]. On the other hand, the process could be approximated by a linear system if v is close to 0.…”

Section: ) Gap-metric-based Nonlinearity Measure For the Forcedcircumentioning

confidence: 99%

See 2 more Smart Citations

Adaptive Decoupling Switching Control of the Forced-Circulation Evaporation System Using Neural Networks

Wang

Chai

et al. 2013

IEEE Trans. Contr. Syst. Technol.

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Abstract-For the forced-circulation evaporation process of alumina production, the control objectives include maintaining the liquid level and fast tracking of the product density with respect to its setpoint. However, with the strong coupling between the level control and product density control loops and the process exhibits strong nonlinearities, conventional control strategies, such as proportional-integral-derivative and other linear control design, cannot achieve satisfactory control performance and meet production demands. By augmenting the forced-circulation evaporation system model with dynamics of its operating valves, a nonlinear adaptive decoupling switching control strategy is proposed. This control strategy includes a linear adaptive decoupling controller, a neural-network-based nonlinear adaptive decoupling controller, and a switching mechanism. The linear adaptive decoupling controller is used to reduce the coupling between the two control loops. The neural-network-based nonlinear adaptive decoupling controller is employed to improve the transient performance and reduce the effects of the nonlinearities on the system, and the switching mechanism is introduced to guarantee the input-output stability of the closed-loop system. Simulation results show that the proposed method can decouple the loops effectively for the forced-circulation evaporation system and thus improve the evaporation efficiency.

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Section: ) Gap-metric-based Nonlinearity Measure For the Forcedcircumentioning

confidence: 99%

Section: ) Gap-metric-based Nonlinearity Measure For the Forcedcircumentioning

confidence: 99%

Section: ) Gap-metric-based Nonlinearity Measure For the Forcedcircumentioning

confidence: 99%

See 1 more Smart Citation

Adaptive Decoupling Switching Control of the Forced-Circulation Evaporation System Using Neural Networks

Wang

Chai

et al. 2013

IEEE Trans. Contr. Syst. Technol.

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“…This has triggered the development of multilinear model approaches to tackle nonlinear systems problems. Multilinear model approaches turn out to be an ideal candidate for dealing with strong nonlinear chemical processes with wide operating ranges and large set-point changes, and has attracted much attention and been studied extensively in the past years (see [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21] and the references therein).…”

Section: Introductionmentioning

confidence: 99%

“…[13] extends the method in [9] to integrate the procedure of selecting operating points and local controller design. Along with the concept of gap metric, [15] presents a gap metric-based method which aims to perform the operating range decomposition and the minimum linear model bank determination of a nonlinear system. For a given threshold value, the minimum linear model bank determined by the proposed method in [15] can provide sufficient information for multilinear model controller design of nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

An integrated state space partition and optimal control method of multi-model for nonlinear systems based on hybrid systems

Song

Zhao

et al. 2015

Journal of Process Control

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Gap metric–based model bank construction for wind turbine predictive control

Chen

2018

Optim Control Appl Methods

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This paper presents a novel model bank construction method for the multiple model predictive control of wind turbine system. The gap metric is used to measure the dynamic difference between the linearized models of the wind turbine system at different wind speed. Two algorithms are then proposed to divide the wind speed range in different operating regions. Meanwhile, a complete and nonredundant linear model bank is established to approximate the wind turbine system in the whole operating region. We take the robust model predictive control algorithm to design the local controller and utilize the wind speed as the switching criterion to combine the submodels. The simulation study on a 5-MW wind turbine verifies the efficiency of the proposed method.KEYWORDS gap metric, model bank construction, multiple model predictive control, wind turbine system 1610

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Application of gap metric to model bank determination in multilinear model approach

Cited by 69 publications

References 20 publications

Adaptive Decoupling Switching Control of the Forced-Circulation Evaporation System Using Neural Networks

Adaptive Decoupling Switching Control of the Forced-Circulation Evaporation System Using Neural Networks

An integrated state space partition and optimal control method of multi-model for nonlinear systems based on hybrid systems

Gap metric–based model bank construction for wind turbine predictive control

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