Study of tensor product model alternatives

被引:8
|
作者
Kuczmann, Miklos [1 ]
机构
[1] Szechenyi Istvan Univ, Dept Automat, Egyet Ter 1, H-9026 Gyor, Hungary
关键词
gantry crane model; HOSVD; tensor product approximation; TRANSFORMATION; SYSTEMS; DESIGN; DISCRETIZATION;
D O I
10.1002/asjc.2446
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A tensor product (TP) model has an infinite number of alternatives. These variants can be readily derived by the TP model transformation that can variate the number of fuzzy rules, the number of antecedent and consequent sets and, further, the shape of the antecedent fuzzy sets. The related literature has quite deep analysis that modifying these features of a TP model has a crucial role in further design. The latest variants of the TP model transformation, emerged about a year ago, are capable of variating the input space of a TP model. The goal of this paper is to analyse this recently emerged new feature through the example of the gantry crane state space model.
引用
收藏
页码:1249 / 1261
页数:13
相关论文
共 50 条
  • [31] The iterative solution of a class of tensor equations via Einstein product with a tensor inequality constraint
    Huang, Baohua
    Ma, Changfeng
    LINEAR & MULTILINEAR ALGEBRA, 2022, 70 (21) : 6321 - 6344
  • [32] Tensor product model HOSVD based polytopic LPV controller for suspension anti-vibration system
    Ma, Fangwu
    Li, Jinhang
    Wu, Liang
    JOURNAL OF VIBRATION AND CONTROL, 2023, 29 (1-2) : 5 - 20
  • [33] Tensor Product based Convex Polytopic Modeling of Nonlinear Insulin-Glucose Dynamics
    Galambos, Peter
    Kuti, Jozsef
    Baranyi, Peter
    Szoegi, Gabor
    Rudas, Imre J.
    2015 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2015): BIG DATA ANALYTICS FOR HUMAN-CENTRIC SYSTEMS, 2015, : 2597 - 2602
  • [34] Local Extrema Refinement Based Tensor Product Model Transformation Controller Design with Vary Input Methods
    Shi, Bao
    Zhao, Guoliang
    Huang, Sharina
    INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2022, 20 (04) : 1351 - 1364
  • [35] Nonlinear H2 Filtering based on Tensor Product Model Transformation for Nonlinear Discrete System
    Wang, Binglei
    Gong, Hengheng
    Zhang, Fengdi
    Yu, Yin
    Dong, Ning
    Li, Zhen
    Liu, Xiangdong
    2018 37TH CHINESE CONTROL CONFERENCE (CCC), 2018, : 1776 - 1781
  • [36] Tensor product model transformation-based reinforcement learning neural network controller with guaranteed stability
    Phothongkum, Kraisak
    Kuntanapreeda, Suwat
    NEUROCOMPUTING, 2024, 608
  • [37] Tensor Product Model Transformation-based Controller for Induction Motor Using Sum of Square Method
    Cai, Shengye
    Zhao, Guoliang
    2022 41ST CHINESE CONTROL CONFERENCE (CCC), 2022, : 2473 - 2477
  • [38] Analytical Upper Bound for the Error on the Discretization of Uncertain Linear Systems by using the Tensor Product Model Transformation
    Campos, Victor C. da S.
    Braga, Marcio F.
    Frezzatto, Luciano
    ACTA POLYTECHNICA HUNGARICA, 2020, 17 (06) : 61 - 74
  • [39] Tensor Product-Based Model Transformation Technique Applied to Modeling Vertical Three Tank Systems
    Hedrea, Elena-Lorena
    Precup, Radu-Emil
    Bojan-Dragos, Claudia-Adina
    Hedrea, Ciprian
    2018 IEEE 12TH INTERNATIONAL SYMPOSIUM ON APPLIED COMPUTATIONAL INTELLIGENCE AND INFORMATICS (SACI), 2018, : 63 - 68
  • [40] QUASI-MIN-MAX MODEL PREDICTIVE CONTROL FOR IMAGE-BASED VISUAL SERVOING WITH TENSOR PRODUCT MODEL TRANSFORMATION
    Wang, T. T.
    Xie, W. F.
    Liu, G. D.
    Zhao, Y. M.
    ASIAN JOURNAL OF CONTROL, 2015, 17 (02) : 402 - 416