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Article type: Research Article
Authors: Maji, Pallab* | Patra, Sarat Kumar | Mahapatra, Kamalakanta
Affiliations: Department of Electronics and Communication Engineering, National Institute of Technology, Rourkela, Odisha, India.
Correspondence: [*] Corresponding author. Pallab Maji, Department of Electronics and Communication Engineering, National Institute of Technology, Rourkela, Odisha - 769008, India. Tel.: +91 661 2464463; Fax: +91 661 2462459; E-mail: [email protected].
Abstract: This paper presents a generic hardware architecture based type-I Mamdani fuzzy logic controller (FLC) implemented on a programmable device, which can be remotely configured in real-time over Ethernet. This feature of reconfigurability enables a user to change fuzzy parameters in real-time, eliminating repeated hardware programming. Realization of these systems is generally difficult as the computational requirement is exponentially related to the number of inputs. This is achieved by significantly reducing the Rulebase to make inference time perceivable for real-time applications. An algorithm for Rulebase reduction is proposed and implemented which reduces effective rules without compromising system accuracy leading to improved cycle time in terms of fuzzy logic operations per second (FzLOPS). A hardware software co-design architecture for the proposed generic FLC is developed on TI C6748 DSP with Sys/BIOS RTOS and seamlessly integrated with a web based user interface (WebUI) for reconfigurability. The WebUI acquires the fuzzy parameters from users and a server application is dedicated to data communication between the hardware and the server. Analysis of this design is carried out by using hardware-in-loop (HIL) test to control various plant models in Simulink/Matlab environment. Performance of the proposed system is compared to Fuzzy Toolbox of Matlab and PID controllers.
Keywords: Digital signal processors, fuzzy systems, intelligent control, mamdani inference, programmable control, reconfigurable architectures, Sys/BIOS, web and internet services
DOI: 10.3233/IFS-151912
Journal: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 4, pp. 1973-1986, 2016
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