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Fuzzy-based interaction prediction approach for hierarchical control of large-scale systems

Emamzadeh, M. M ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1016/j.fss.2017.05.018
  3. Abstract:
  4. This paper presents a fuzzy-based interaction prediction approach (F-IPA) for two-level optimal control of large-scale systems. The design procedure uses a decomposition/coordination framework of hierarchical structures. At the first level, the system is decomposed into subsystems for which subproblems are formed. At the second level, a fuzzy coordinator is used to predict the coordination parameters needed to coordinate the solutions of the first level subproblems. The fuzzy coordinator uses a critic vector to evaluate its performance and learn its parameters by minimizing an energy function. The proposed control scheme is implemented on a two-degrees-of-freedom (2DOF) model of robot manipulator with parallel links and two inverted pendulums on cars. Simulation results are obtained and compared with the gradient-based interaction prediction approach (G-IPA) and a centralized optimization. © 2017 Elsevier B.V
  5. Keywords:
  6. 2DOF robot manipulators ; Fuzzy interaction prediction approach ; Two inverted pendulums on cars ; Two-level optimal control ; Degrees of freedom (mechanics) ; Flexible manipulators ; Forecasting ; Hierarchical systems ; Industrial robots ; Manipulators ; Modular robots ; Pendulums ; Robot applications ; Fuzzy coordination ; Interaction prediction ; Inverted pendulum ; Optimal controls ; Robot manipulator ; Large scale systems
  7. Source: Fuzzy Sets and Systems ; Volume 329 , 2017 , Pages 127-152 ; 01650114 (ISSN)
  8. URL: https://www.sciencedirect.com/science/article/pii/S0165011417302270