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SIESTA for Virgo locking experience

This detailed simulation workshop outline delves into the commissioning of the first 3-km cavity at Virgo, focusing on the North Cavity Optical Scheme and Control System. It covers feedback characterization, lock acquisition strategies, and algorithm efficiencies in the context of real data comparisons and simulations. The text explores the linearized error signals, lock algorithm efficiencies, and control schemes utilized, shedding light on the complex process of locking the cavity successfully. It showcases the iterative optimization steps taken to achieve critical damping and remove spikes, highlighting the intricate modal simulations and control strategies deployed for a comprehensive locking experience at Virgo.

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SIESTA for Virgo locking experience

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  1. SIESTA for Virgo locking experience L. Barsotti University of Pisa – INFN Pisa on behalf of the Virgo Locking Group Simulation Workshop Cascina, March 16th 2004

  2. Outlines • Commissioning of the first 3–km cavity • Recombined mode • Full Virgo • Other activities in parallel

  3. North Cavity Optical Scheme PR, WI, WE mirrors misaligned WE WI T=8% NI NE 6 W BS B7 T=12% T=50 ppm PR B5 B1p

  4. 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, C2 runs) • Real suspensions, real actuators, real photodiodes, computational delays included in the simulation

  5. PR NI NE BS B7 B1p T=8% |Gain| Hz frequency North Cavity Control Scheme Lock Acquisition • Linearized error signal:

  6. Optical Gain: • Measured • Simulated

  7. zCorr zErr M noise G Transfer Function Open Loop Gain simulated measured Phase

  8. Lock Algorithm Efficiency C1 run data : Several lock events collected locking and delocking the cavity linearized error signal • Lock almost always acquired at the first trial

  9. Constraints on the velocity according to the theory: 8mm/s: maximum velocity for the lock acquisition success Failed locking attempt v ~ 12.5mm/s • Gain due to the linearization: a ~ 10 Lock Algorithm Efficiency

  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 • Sweep at 12 mm/s : Lock event Lock failed

  11. Failed locking attempts Lock Algorithm Efficiency not linearized error signal C1 data Simulation

  12. Algorithms running in the global control Photodiodes signals Control signals SIESTA link to real time control SIESTA

  13. Algorithms running in the global control Photodiodes signals Control signals SIESTA link to real time control VIRGO

  14. B8 WE WI PR NI NE BS B7 T=8% B5 B2 B1 Recombined Optical Scheme PR mirror misaligned

  15. Recombined mode • 2 Steps locking strategy: • sensing matrix • procedure to find experimentally the algorithm parameters from simple optical systems • 3 Steps locking strategy • sensitivity curve • comparison with real data • Linear locking

  16. B8 • west cavity and michelson controlled at the sime time • north cavity controlled with B5 B7 B2 B5 B1 Reconbined 2 Steps Control Scheme

  17. Michelson and West cavity controlled with the symmetric (B2_quad) and the antysimmetric signal (B1p_quad) • Sensing matrix • Theorical optical matrix: • Optical matrix measured by Siesta:

  18. Locking simulation – North cavity Locking

  19. Locking simulation – Mich & West Powers Lengths Triggers Corrections

  20. B8_demod West arm North arm B7_demod B5 B2 B1p_demod Recombined 3Steps Control Scheme • switch from B1p to B1 after the lock acquisition

  21. Lock acquisition -simulation “Simple” simulation: real suspensions and actuators

  22. Lock acquisition -simulation

  23. First lock acquisition 27th February Locking event At 3.25 am

  24. Sensitivity - simulation Improvement: real photodiodes(electronic noise, shot noise)

  25. Sensitivity Simulated Measured

  26. d2_quad d2_phase d1p_quad MICH CARM DARM Switch to the linear locking state • Optical matrix: • Inverse optical matrix:

  27. West arm North arm B2_quad B1p_quad ⊗ B2_phase Linear Locking Control Scheme

  28. Linear lock of the recombined Simulation

  29. Full Virgo Optical Scheme B8 WE WI PR NI NE BS B7 B5 B2 B1

  30. Lock acquisition of full Virgo • Multi–states approach (LIGO scheme) • Dynamical inversion of the optical matrix

  31. Lock acquisition of full Virgo

  32. Something more… • Modal simulation • Longitudinal local control optimization • Spikes removal

  33. 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

  34. Something more… • Modal simulation • Longitudinal local control optimization • Spikes removal

  35. 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

  36. 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

  37. 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

  38. Something more… • Modal simulation • Longitudinal local control optimization • Spikes removal

  39. Spikes removal

  40. Spikes removal Rearrange the algo: Error signal  derivative  window  integrator window

  41. 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 Other activity:Hierarchical control • preliminary results wwwcascina.virgo.infn.it/collmeetings/presentations/Mar2004/Fiori_11Mar04_MarioLockSim.ppt

  42. Conclusions • Siesta: fundamental tool for locking studies • Link to the real time control system • Work in parallel with other groups to improve the simulation (suspensions, alignment) • Noise analysis

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