Using Fuzzy Relational Hybrid Models to Control Mixed-Valued Dynamic Systems with Discrete-Valued Inputs

Abstract

Abstract

This is the first attempt to bring the fuzzy relational hybrid models (FRHMs) from modeling to control. The main challenge is to configure both the plant model and the controller appropriately so that the overall system has good analytical and numerical properties. However, to close the control loop effectively by connecting the FRHM blocks, it is needed for its core mathematical operator to be associative. Therefore, in this paper: (1) It has been shown that the core mathematical operator that relates the connected g-normal FRHM blocks, i.e., the Yager-product fuzzy relational inner composition (FRIC), unlike most FRICs, is associative; (2) An intelligent adaptive control scheme has been developed for a class of plants in which the states of the system can be mixed-valued and all inputs are of discrete-valued type (either quantitative or qualitative). Benefiting from the associative property, the proposed control scheme uses the g-normal FRHM building blocks in the role of the controller as well as the plant model with no prior knowledge of the elements of the fuzzy relational matrices. Being applied to control a synchronous buck converter in both regulation and tracking scenarios, and under parameters uncertainties, the proposed scheme has been evaluated by computer simulation.

 

Keywords

fuzzy systems; fuzzy control; switching systems (control); adaptive control; voltage control

 

Cite this article

Aghili-Ashtiani, A.: Using fuzzy relational hybrid models to control mixed-valued dynamic systems with discrete-valued inputs. IET Control Theory Appl. 16, 192– 207 (2022). https://doi.org/10.1049/cth2.12216