Abstract
Interval Type2 Fuzzy Logic Control (IT2FLC) has been applied to a number of industrial, medical, home and military applications. Hardware implementation of IT2FLC can be achieved in a number of ways. One of these ways is the use of a Field Programmable Gate Array (FPGA). In this paper, the design and implementation of an IT2FLC using FPGA has been presented. The proposed controller is of Mamdani type. It works in different structures (P/PI/PD/PID like IT2FLC) depending on two control lines, different number of triangular shape memberships (2-7) depending on three control lines, six tunable gains and within a range of sampling time of (0.01-1024) seconds. Three type reduction algorithms are used and it is found that the Enhanced Iterative Algorithm with Stop Condition (EIASC) produced the minimum reduction in FPGA size. Thus less execution time. The reduction size is about 75% than Karnick Mendel (KM) and is about 3% than Enhanced KM (EKM). Linear and nonlinear models are used to test the designed Controller. Gains are tuned manually to reach minimum overshoot, settling time and steady state error. Simulation and Implementation results showed that the proposed controller works in an efficient way under no-load, load and uncertainty in the nonlinear model parameters.
Highlights
Type2iFLC containifootprintiof uncertaintyi(FOUi) that is able toihandle the numerical uncertainties, nonlinearities and linguisticmassociatedi with the inputs and outputs
It is allowingieachllinput toihave two membershipllgrade values related with it; an Upper Membership Functions (MFs) (UMF) and Lower MF (LMF)
The unit step response of this model using P like Interval Type2 Fuzzy Logic Control (IT2FLC) as shown in Figure (11), PD like IT2FLC as shown in Figure (12), PI like IT2FLC as shown in Figure (13) and PID like IT2FLC is shown in Figure (14)
Summary
Type2iFLC containifootprintiof uncertaintyi(FOUi) that is able toihandle the numerical uncertainties, nonlinearities and linguisticmassociatedi with the inputs and outputs. Memberships of system variables are represented using interval value fuzzy sets Thelleffectiveness of this controller has been investigated through simulation studies. An IT2FLC can work with different number of memberships and several type reduction algorithms with highllresolution data. It describes the connections between these devices with PC using hardware in the loop approach.
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