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Improving the Hardware Complexity by Exploiting the Reduced Dynamics-Based Fractional Order Systems
Author(s) -
Nasim Ullah,
Anees Ullah,
Asier Ibeas,
Jorge Herrera
Publication year - 2017
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2017.2700439
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Fractional calculus is finding increased usage in the modeling and control of nonlinear systems with the enhanced robustness. However, from the implementation perspectives, the simultaneous modeling of the systems and the design of controllers with fractional-order operators can bring additional advantages. In this paper, a fractional order model of a nonlinear system along with its controller design and its implementation on a field programmable gate array (FPGA) is undertaken as a case study. Overall, three variants of the controllers are designed, including classical sliding mode controller, fractional controller for an integer model of the plant, and a fractional controller for a fractional model of the plant (FCFP). A high-level synthesis approach is used to map all the variants of the controllers on FPGA. The integro-differential fractional operators are realized with infinite impulse response filters architecturally implemented as cascaded second-order sections to withstand quantization effects introduced by fixed-point computations necessary for FPGA implementations. The experimental results demonstrate that the fractional order sliding mode controller-based on fractional order plant (FCFP) exhibits reduced dynamics in sense of fractional integration and differentials. It is further verified that the FCFP is as robust as the classical sliding mode with comparable performance and computational resources.

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