460 likes | 633 Views
Use of Siesta in VIRGO commissioning. Lisa Barsotti University of Pisa – INFN Pisa For the Virgo collaboration. Caltech, December 19th 2003. Introduction to SIESTA SIESTA as locking tool: Commissioning of the central interferometer (CITF)
E N D
Use ofSiesta in VIRGO commissioning Lisa Barsotti University of Pisa – INFN Pisa For the Virgo collaboration Caltech, December 19th 2003
Introduction to SIESTA • SIESTA as locking tool: • Commissioning of the central interferometer (CITF) • Commissioning of the first Virgo 3-km cavity • Recombined mode • Lock of the full Virgo • Towards a complete simulation: • Optics Modal simulation • Mechanics Superattenuator tuning Inertial damping Local controls Hierarchical control Outlines
The SIESTA code SIESTA: time domain simulation of Virgo • Objects defined as C structure • Sub-routines written for each sub-system • Signal structure used to relate the different elements of the simulation • Simulation parameters defined in ascii configuration files (SIESTA cards)
m+n An example of configuration card • LASER clock l laser waist P IOlaser laser 0 NULL 1.064e-6 0.14 NULL freq_noise.out 0. 2.15264e-2 .50 NO 2 • PHASE MODULATOR USignal carrier 0.96 USignal sb1 0.05USignal sb2 -0.05 OPmod mod 0 laser.oBeam 3 0.6.264080e6 -6.264080e6 carrierNULL sb1 NULL sb2 NULL • OPTICAL CONFIGURATION OPcavity itf 0 mod.oBeam MiSuNIb MiSuNEf YES NULL Dynamical simulation Mirrors surface • CAVITY MIRRORS MIrror MirNI 0 SuNI.dxyzt misNI.out NULL MiSuNIb 6.3807 0. 0. 1. 0. 0 MIsurf MiSuNIb 0. .1 0. 0. 0. 0.8819765 7.75e-6 losses R
Histogram 1-D FFT Time Plot Histogram 2-D TF FFT Time Output frames: data fast visualization • Plots savable also as .C, .root, .ascii for deeper analysis (ROOT, VEGA, MATLAB)
Algorithms running in the global control Photodiodes signals Control signals SIESTA link to real time control SIESTA
Algorithms running in the global control Photodiodes signals Control signals SIESTA link to real time control VIRGO
West and recycling mirrors controlled Commissioning of the Virgo CITF - I • Study of the CITF lock acquisition • Gains and triggers computed by the simulation • Strategy directly transfered in the Virgo global control system
Commissioning of the Virgo CITF - II Recycling cavity power Lock event Main trigger Correction WI Correction PR
Commissioning of the north cavity • Feedback characterization: • optical gain • open loop transfer function • Analysis of the lock algorithm efficiency • linearized error signal • no linearized error signal • Comparison with real data (C1 run) • Real actuators, real photodiodes, computational delays included in the simulation
T=8% T=12% 6 W B7 T=50 ppm B5 B1 Commissioning of the north cavity - I • Opticalscheme
PR NI NE BS B7 B1p |Gain| Hz frequency Commissioning of the north cavity - II • Lock acquisition control scheme • 1 pole at 0.01 Hz • 2 zeros at 10 Hz • 2 poles at 800 Hz • 1 pole at 1000 Hz
Commissioning of the north cavity - II Switch to B1 with the OMC locked • Linearized error signal: • Asymmetric trigger on the trasmitted power Trigger opening: 50 % Trigger closing: 1 %
Optical Gain: • Measured • Simulated
zCorr zErr M noise G Unity Gain @ 50 Hz zGc Transfer Function Open Loop –Measured • Measured injecting white noise • Gain margin: 3 • Phase margin: 30°
zCorr zErr M noise Unity gain @ 55 Hz G zLock Transfer Function Open Loop – Simulated • Measured injecting white noise • Gain margin: 3.3 • Phase margin: 35°
Transfer Function Open Loop – Measured & Simulated simulated Gain measured Phase
Lock Algorithm Efficiency – I • with the linearized error signal • 24 locking events collected locking and delocking the cavity for 20 minutes (GPS 752873880 – 752875080) • 23 lock acquisition at the first attempt, only 1 failed locking attempt A typical locking event
Lock Algorithm Efficiency – I • Relative velocity between the mirrors computed for each locking attempt 2.5mm/s: mean value of the velocity • 8mm/s: maximum velocity for the lock acquisition success • 12.5 mm/s: velocity of the failed event Failed locking attempt v ~ 12.5 8
Lock Algorithm Efficiency – I • Constraints on the velocity according to the theory: a ~ 10 • Gain due to the linearization:
gain limited by the noise m Linearized error signal No Linearized error signal a ~ 10
With velocity lower than 10 mm/s lock at the first attempt • With velocity higher than 10 mm/s lock at the second attempt Lock Algorithm Efficiency - I Simulation • Sweep at 12 mm/s : Lock event Lock failed
Lock Algorithm Efficiency – II • with the no linearized error signal • 26 locking events collected locking and delocking the cavity for 20 minutes (GPS 752873880 – 752876280) • 14 lock acquisition at the first attempt, 12 after some failed attempts Locking always acquired in few seconds
Failed locking attempts 3.3 3.3 Lock Algorithm Efficiency – II • Maximum velocity measured for a locking event: 3.5 • Constraints on the velocity according to the theory:
Lock Algorithm Efficiency - IISimulation • Maximum velocity measured for a locking event: • With higher velocity, lock acquired after some attempts, in few seconds 2 • Sweep at 2.5
Recombined Optical Scheme B8 T=8% B7 B5 B2 B1
B8 • west cavity and michelson controlled at the sime time • north cavity controlled with B5 B7 B2 B5 B1 Reconbined Control Scheme
N_tras_power W_tras_power B1_power Recombined: preliminary simulation • to be tuned Lock of W cavity and michelson at the same time Lock of the N cavity
Lock acquisition of the full Virgo - I • Multi–states approach (LIGO scheme) • Dynamical inversion of the optical matrix
Lock acquisition of the full Virgo - I • simulation in progress Algorithm in a subroutine C++ in the global control use the same algorithm for the SIESTA simulation
Introduction to SIESTA • SIESTA as locking tool: • Commissioning of the central interferometer (CITF) • Commissioning of the the first Virgo 3-km cavity • Recombined mode • Lock of the full Virgo • Towards a complete simulation: • Optics Modal simulation • Mechanics Superattenuator tuning Inertial damping Local controls Hierarchical control Outlines
0.113 Modal simulation • High order modes (n + m ≤ 5 ) • compromise with the computational time 1 sec @ 20 kHz ⇒ 45 sec • misalignment of 2 mrad in qy of the curve mirror • Check with other codes in progress
Suspensions complete simulation: the SA • Siesta file with the SA description • Inertial damping • Simulation tuning Transfer function betweeen force on steering filter and YAW mode of the mirror RED simulation BLACK measurement
marionetta reference mass y z test mass x z The Last Stage of the SA
Local controls system • Sensing: angular readout ( qx e qy ) of marionetta and mirror, position readout of the mirror along the optical axis; • Filtering: filtering of the signals achieved in the sensing phase; • Driving: control of the angular position of mirror and marionetta by feedback on the marionetta; control of the mirror position along the optical axis (z) by feedback to the reference mass.
MARIONETTA: qx and qyangular readout • MIRROR: readout of qx e qy and of the z position • measurement of the z position Sensing Simulation in progress
marionetta mirror z reference mass Filtering & Driving marionetta loop z Damping marionetta mirror mirror loop
qy qx Marionetta loop action time Unity gain @ 5 Hz Unity gain @ 5 Hz
0.6 Hz excitation by white noise injection z Damping Unity gain @ 2 Hz • 0.6 Hz resonance compensation action time
Optimization of the z damping loop – I • measured zCorr zMirror mm • Damping time ~ 10 sec t~10 sec Open loop transfer function Unity gain @ 0.65 Hz Hz
Optimization of the z damping loop – II • simulated zCorr zMirror V m t~2 sec Open loop transfer function Critical damping @ 1.45 Hz Hz
zCorr zMirror V mm t~ 2 sec Guadagno open loop Hz Optimization of the z damping loop – III • measured after the optimization Critical damping @ 1.45 Hz
marionetta Transfer function betweeen force on steering filter and z movement of the mirror Control from the marionetta z reference mass mirror Control from the reference mass Hierarchical control • simulation work in progress
North cavity complete simulation • Modal and dynamical optical simulation • Laser frequency noise • noise taken from the real data • Real actuators and real photodiodes • Computational delays • Asymmetry in the coils • 6 dof superattenuators, with: • angular controls • longitudinal damping • inertial damping
Conclusions • Time domain simulation: mainly tool for locking studies • Frames output, link with real time control system • Now work on suspensions control and high order modes simulation: • improve the plane-wave lock acquisition algorithm • WFS • hierarchical control (marionetta) • Noise analysis