2023
DOI: 10.1109/tii.2021.3133893
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Structurally Optimized Neural Fuzzy Modeling for Model Predictive Control

Abstract: This paper investigates the local linear model tree (LOLIMOT), a typical neural fuzzy model, in the multipleinput-multiple-output model predictive control (MPC). In the conventional LOLIMOT, the structural parameters including centres and variances of its Gaussian kernels are set based on equally dividing the input data space. In this paper, after the structural parameters are initially obtained from the input space partition, they are optimized by the gradient descent search, from which the space partitions a… Show more

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Cited by 4 publications
(2 citation statements)
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“…That is why we turn our attention into (26) which matrices for the considered case can be rewritten as follows Usage of the above-mentioned software requires to define linear time-invariant subsystems, which we define by using transfer functions W11-W14, W21-W24 from (23).…”
Section: The Case Of Drive Deceleration From Somementioning
confidence: 99%
See 1 more Smart Citation
“…That is why we turn our attention into (26) which matrices for the considered case can be rewritten as follows Usage of the above-mentioned software requires to define linear time-invariant subsystems, which we define by using transfer functions W11-W14, W21-W24 from (23).…”
Section: The Case Of Drive Deceleration From Somementioning
confidence: 99%
“…That is why a lot of methods and approaches to designing closed-loop control systems are developed [15,16], [17,18], [19,20], [21]. One of them is based on the intellectual control paradigm and allows us to design controllers by intellectual control methods such as neuro and fuzzy control [22,23], [24].…”
Section: Introductionmentioning
confidence: 99%