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Fuzzy Logic Controller Realization Using Microcontrollers_Presentation
- 2. Introduction • Fuzzy Logic (FL) controlling system is based on a set of rules established by an expert. • These rules are translated into mathematical steps used to realize a physical controller. • FL controllers can be physically realized in different forms. • We adopt look up tables and function realizations • Microcontrollers to use are one from the MSP430 family (Texas Instruments) and one from the Kinetis series (NXP)
- 5. Objectives • To develop a method to introduce fuzzy controllers schemes derived from applications for use in microcontrollers • Present focus: Texas Instruments MSP430 and NXP Kinetis series microcontrollers • To develop two microcontroller based fuzzy controller methods using • Look up tables, and • Function development inside the micro • To prove the controller with a specific application • A stabilizer for a quadcopter
- 6. Problem & Hypothesis • Methods proposed to implement the FL function: • A) Compute the outputs using Matlab and build a look-up table within the microcontroller. • Advantage: useful for small controllers • Disadvantage: memory consumption • B) To implement the membership functions, rules and defuzzification rule in the microcontroller.
- 7. Methodology • Study, analyze, and comprehend the design process of a Fuzzy Logic Controller • Understand and master the use of microcontroller to establish the system to be designed • Implement, program, and experiment with the system designed in it’s both forms using two different microcontrollers
- 8. Results
- 10. Rules in Matlab
- 13. Triangular Subroutines Functions Triangular: mov R6,R14; cmp R7,R14; jhe MPos2; add #0,R12; jmp Continue2; MPos2: cmp R8,R14; jhe MNeg2; sub R7,R14; sub R7,R8; mov #0,R11; Div3: sub R8,R14; inc R11; cmp R8,R14; jhe Div1; add R11,R12; jmp Continue2; MNeg2: cmp R10,R14; jhe Zero2; mov R10,R15; sub R14,R15; sub R9,R10; mov #0,R11; Div4: sub R10,R15; inc R11; cmp R10,R15; jhe Div2; add R11,R12; jmp Continue2; Zero2: add #0,R12; Continue2: ret;
- 14. Trapezoid Subroutines Functions Trapezoide: mov R6,R14; cmp R7,R14; jhe MPos; add #0,R12; jmp Continue; MPos: cmp R8,R14; jhe MZero; sub R7,R14; sub R7,R8; mov #0,R11; Div1: sub R8,R14; inc R11; cmp R8,R14; jhe Div1; add R11,R12; jmp Continue; MZero: cmp R9,R14; jhe MNeg; add #1,R12; MNeg: cmp R10,R14; jhe Zero; mov R10,R15; sub R14,R15; sub R9,R10; mov #0,R11; Div2: sub R10,R15; inc R11; cmp R10,R15; jhe Div2; add R11,R12; jmp Continue; Zero: add #0,R12; Continue: ret
- 15. Look-Up Table Input Angle Output Portion of Voltage 0.46875 0.25 1.40625 0.25 2.34375 0.25 3.28125 0.25 4.6875 0.25 … … 10.3125 0.2534965 14.0625 0.2996183 20.15625 0.3957399 24.84375 0.496114 … … Input Angle Output Portion of Voltage 25.3125 0.5031513 28.59375 0.5397465 30.46875 0.5640244 35.625 0.6482558 39.84375 0.7456897 … … 40.78125 0.75 45.9375 0.75 50.625 0.75 54.375 0.75 59.53125 0.75
- 16. Function Developed For the Defuzzification process we use the Weighted Average Function to calculate the output number according with the simulation on Matlab. 𝑂𝑢𝑡𝑝𝑢𝑡 = Σ 𝜇 𝑥 ∗ 𝑥+, Σ 𝜇 𝑥 𝜇 𝑥 𝑔𝑟𝑎𝑑𝑒 𝑜𝑓 𝑤𝑒𝑖𝑔ℎ𝑡 𝑜𝑛 𝑡ℎ𝑒 𝑚𝑒𝑚𝑏𝑒𝑟𝑠ℎ𝑖𝑝 𝑥+, weighted average input
- 17. Future Work
- 18. • Set up the one input system as a proof of concept. We are in the process of building the hardware set up. • Based on the first system, make a selection of the microcontroller models appropriate for a two and three input system • Build the controller with two axes, hence, two inputs or three inputs, depending on the rules.
- 20. Questions?