System-on-Chip Design of a Fuzzy Logic Controller Based on Dynamically Reconfigurable Hardware

Fuzzy Logic is, nowadays, a control technique widely extended in nonlinear system applications. This work adds a new point-of-view to the continuous efforts in search of an optimized hardware-software co-design of a dual-input single-output fuzzy logic controller (FLC). Our approach breaks up with the classical three-stage implementation process fuzzification, rule inference and defuzzification cores to focus it on directly synthesizing the resultant control surface. An innovative design methodology is defined by firstly splitting the total area in rectangular sectors to, afterwards, model each of them by second-order polynomial functions. The algorithm is finally embedded in a MCUFPGA platform to achieve a balanced cost-performance solution inspired by such efficient concepts in terms of runtime and silicon-area as parallel processing and dynamic partial reconfiguration, respectively. The result is a universal FLC where the control surface is parameterized and handled through a simple data file appended to the design bitstream in the way of initialized SRAM memory. This HW/SW architecture therefore provides a general-purpose solution able to customize whichever fuzzy application by only updating the data that model the particular control surface segmented in rectangular sectors.