Soft Computing Applications on SR-30 Turbojet Engine

More documents

Recommendations

Info

AIAA 2004-6444Integral Part1PD Part32Engine ModelFigure 10: Fuzzy Logic Simulation VI (wiring diagram)1.0N MN Z MP P1.0N MN Z MP P0.50.50.00.0-11.0 -5.5 0.0 5.5 11.0a b c d e f gA) INPUTSB) OUTPUTSFigure 11: Fuzzy Sets Associated with Thrust Error and Thrust Error Rate Inputs and FuzzySets associated with Valve Position and Valve Position Error Outputsbenefit from the capabilities of the fuzzy logiccontroller. Since the aim of the present study was todevelop a test-bed and demonstrate the hardware-inthe-loopanalysis, a relatively simple fuzzy logic designwas used. Table 2 explains the meanings of the symbolsto express each linguistic term. Table 3 shows a pair ofthe rule bases used in the design process.Among the defuzzification methods such as theCenter-of-Maximum, the Center-of-Gravity, and theMean-of-Maximum that are available in the FuzzyLogic Toolkit, the Center-of-Maximum method wasused in the design. The Center-of-Maximum methodresults in a lesser computation time and it also results ina linear variation of the output variable once fullyoverlapping linguistic terms were used.IV-C. FUZZY LOGIC CONTROLLER TESTUSING SIMULATED ENGINEThe LabVIEW-fuzzy logic controller design wasfirst tested in a LabVIEW simulation model using theplant transfer function identified in the PID controllerdesign process. It was assumed that the fuzzy logiccontrol algorithm would be applicable to this enginecontrol application because the architecture of thealgorithm is capable of handling non-linearity. In thedesign of the fuzzy logic algorithm, several differentuniverse of discourse ranges were tested for the6American Institute of Aeronautics and Astronautics
AIAA 2004-6444Thrust [lbs]andValve Position [deg]antecedence and the consequence ranges. The bestranges were identified which gave the least rise timewithout an overshoot.Step Input Test: Figure 12 shows a unit step responsefrom the simulation model, which includes the plantmodel and the fuzzy logic controller. The valve positionvery quickly rises to 3.6 degrees within 0.33 seconds.The simulated time delay is visible with about 0.2seconds. The thrust output from the plant modelincreases without an overshoot to the desired thrustvalue within 3.0 seconds. The number below thehorizontal axis in Figure 12 represents the number ofloops executed and the rate of the loop execution was25 time/sec.ThrustThrust DesiredValve PositionFigure 12: Step Response from Simulation Model.Twenty-five steps correspond to 1 second.stepsSystem Response with Limits on the Valve position:The fuzzy controller design was also tested to observethe effects on the system responses if valve positionlimits were set. The valve position limits were requiredbecause the controller tries to move the linkage out ofthe possible range of the motion. The reason of thenecessity for the limits is shown in Figure 13. Once thedesired thrust is obtained and subsequently decreasedback to a lower value, the valve position needs to bereduced below zero degrees, which is not achievabledue to the physical constraints of the fuel-flow valvesystem. Additionally, changing the valve position tobelow a certain angle would result in the engine to shutdown. Although the effect of the minimum angle limitset results in a much slower response of the engine, it isrequired to avoid any damage to the engine. In order toeliminate such control scenarios occurring, limits on theintegral controller was placed. The integrated controlangle and the control angle sent to the engine were resetto zero once the controller required an angle belowzero. The number below the horizontal axis in Figure13 also represents the number of loops executed and therate of the loop execution was 25 /sec.IV-D. FUZZY LOGIC CONTROLLER TESTWITH SR-30 TURBOJET ENGINEThe Fuzzy Logic Controller LabVIEW-Virtual-Instrument was next tested to control the SR-30 engine.In order to compare the response of the simulated andthe actual SR-30 engine responses, the same type of astep input test was attempted. The results are shown inFigure 14 (Case 1), Figure 15 (Case 2). Different rangesof the linguistic variable for the valve position outputwere used for each case while the same ranges of thelinguistic variables for the inputs were used with theones in the simulation. Refer to Figure 11 and Table 1for the numbers used for each case.A step command of 4.5 pounds was issued fromthe idling operation status for each case. Figure 14shows the result from the first attempt and the samefuzzy inference system used in the test simulation wasused for this case. There was an oscillation in the valveposition trying to achieve the desired thrust numbersince the thrust was not getting a steady state. In FigureThrust [lbs] and Valve Position [deg]5.0desired thrust4.54.03.5thrust3.02.5valve position2.01.51.0145 147 149 151 153 155 157 159Time [sec]Figure 14: Step Response from SR-30 Engine Case 17American Institute of Aeronautics and Astronautics
Page 2 and 3: AIAA 2004-6444II. SR-30 TURBOJET EN
Page 4 and 5: AIAA 2004-6444Figure 4, shows that
Page 8 and 9: AIAA 2004-644415, the result from t
Page 10 and 11: AIAA 2004-6444Table 1: Linguistic V

Soft Computing Applications on SR-30 Turbojet Engine

Create successful ePaper yourself

Delete template?

Save as template?