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6.4 FrequencyWeighting 51 Ifweweight this process transfer function byW(s)=1/(s+1), then the new system becomesWG=10/(s+10). Now, the gain declines with increasing fre- quency, fromamaximumofoneat zero frequency toaminimumofzeroat infinite frequency. Byweighting the original system,G, by theweighting function,W, we cause theH2 normof the combined system,WG, to be relativelymore sensitive to low- frequency disturbances.Whenwedesign a controller byminimizing theH2 norm associatedwithWG,wewill typicallyfinda system that is better at rejecting low- frequency loaddisturbances thanadesignminimizing theH2 normassociatedwith G. For the weighted system, optimization will avoid controllers that reject high- frequencyloaddisturbances,becausetheweightedsystemalreadyrejectsthosehigh- frequency inputs. Roughly speaking, a weighting function instructs the optimization method to reducethegainandsensitivityforcertainfrequenciesandtoignorethegainforother frequencies.Theweighting functionsdonot alter the actual system.Theweighting functionsareonlyusedtoalter thecost functionandoptimizationmethodthatdeter- mine theoptimal controller. Figure6.4 shows the regulation feedback system of Fig.6.1 with additional weightingsforthedisturbanceandnoiseinputs.Theweightingsmodifythefoursys- tem transfer functions andassociated sensitivities inEq. 6.2 tobeWdGud,WdGηd, WnGun, andWnGηn.Thecost function inEq.6.5becomes J =μ2||WdT||22+μ2ρ2||WdPS||22 +||WnCS||22+ρ2||WnT||22. (6.9) Consider an example in which we begin with the process, P, in Eq. 6.8. To emphasize low-frequency loaddisturbances, setWd =1/(s+0.1) tobea low-pass filter.Thatweightingfiltersoutdisturbances that are significantlygreater thanω= 0.1.Toemphasizehigh-frequencysensornoise,setWn = s/(s+10).Thatweighting filters out noise that is significantly less thanω=10. By using these two filters, the optimization method puts very low weight on any disturbances in midrange frequenciesofω= (0.1,10). n P d C u y n Wd d ~ Wn ~ Fig.6.4 Basic regulationfeedback loop inFig.6.1withadditionalweightings fordisturbanceand noise inputs. Theweightings alter the cost function to emphasize particular frequency bands for disturbanceandnoise,yieldingamodifiedoptimal controller
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Control Theory Tutorial Basic Concepts Illustrated by Software Examples
Title
Control Theory Tutorial
Subtitle
Basic Concepts Illustrated by Software Examples
Author
Steven A. Frank
Publisher
Springer Open
Location
Irvine
Date
2018
Language
English
License
CC BY 4.0
ISBN
978-3-319-91706-1
Size
15.5 x 23.5 cm
Pages
114
Keywords
Control Theory --- Engineering Design Tradeoffs, Robust Control, Feedback Control Systems, Wolfram
Category
Informatik
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