Feedback Control of SPS E-Cloud/TMCI Instabilities C. H. Rivetta 1 LARP Ecloud Contributors: A. Bullitt 1, J. D. Fox 1, T. Mastorides 1, G. Ndabashimiye 1, M. Pivi 1, O. Turgut 1, W. Hofle 2, B. Savant 2, M. Furman 3,R. Secondo 3, J.-L. Vay 3 1 Accelerator Research Department, SLAC 2 BE-RF Group CERN 3 LBNL This work is supported by the US-LARP program and DOE contract #DE-AC2-76SF515 C. H. Rivetta ECLOUDS1- Cornell University October 1, 21 1
1 Introduction 2 Feedback Systems - Generalities 3 R & D Plan - Progress Hardware Non-Linear Simulations Reduced Models - Feedback Design MD plans 4 Conclusions C. H. Rivetta ECLOUDS1- Cornell University October 1, 21 2
Electron Cloud / TMCI Project - DOE LARP / CERN Motivation: - Control E-cloud and TMCI effects in SPS and LHC via GHz bandwidth feedback Complementary to E-cloud coatings, grooves, etc. Also TMCI Anticipated instabilities at operating currents Intrabunch Instability: Requires bandwidth sufficient to sense the vertical position and apply correction fields to multiple sections of a nanosecond-scale bunch. US LHC Accelerator Research Program (LARP) has supported a collaboration between US labs (SLAC, LBNL) and CERN Large R & D effort coordinated on: Non-linear Simulation codes (LBNL - CERN - SLAC) Dynamics models/feedback models (SLAC - Stanford STAR lab) Machine measurements- SPS MD (CERN - SLAC - LBNL) Hardware technology development (SLAC) C. H. Rivetta ECLOUDS1- Cornell University October 1, 21 3
Simple Observations from SPS Studies SPS MDs: 2 in 28, 1 in 29, recently in 21 June 29, SPS injection 26GeV, Charge: 1E11p/bunch, separation 25 nsec., Time domain Vertical pick-up signals: SUM and DIFF - Extracted Vertical displacement (Data sampled 2 ps/point) 5 4 Vertical displacement of bunch 47 1 SUM DIFF.8 5 4 Vertical displacement of bunch 119 1 SUM DIFF.8 3.6 3.6 SUM / DIFF signals (a.u) 2 1 1 Vertical displacement (a.u).4.2.2.4 SUM / DIFF signals (a.u) 2 1 1 Vertical displacement (a.u).4.2.2.4 2.6 2.6 3.8 3.8 4 5 1 slice 1 5 1 slice 4 5 1 slice 1 5 1 slice Two batches: First 72 bunches stable, (e.g. bunch 47), second set of 72 bunches E-cloud instabilities, (e.g. bunch 119). Time span: 2.6 nsec. movie Vert. Displacement C. H. Rivetta ECLOUDS1- Cornell University October 1, 21 4
Simple Observations from SPS Studies Tune shift Different time evolution of the vertical displacement for different sections of the bunch. Tune shifts within the bunch due to E-cloud, (Tune =.185) 4 3 2 Tail, 24.15 cm Center, 1.15cm Front, 21.85cm 4 35 3 Bunch Tail V y off [a.u.] 1 1 25 2 15 2 1 3 5 4 5 1 15 2 25 3 35 4 45 5 Turn.15.16.17.18.19.2.21.22.23.24.25 Tune movie rms tune C. H. Rivetta ECLOUDS1- Cornell University October 1, 21 5
Feedback System Basics Feedback control is required when the original system is unstable or when performance cannot be achieved due to uncertainties in the the system characteristics Feedback control changes the dynamics of the original system - stabilize - improve performance Receiver + Proc. Channel Vc Amplifier + Kicker Vb Beam Vert. Displ. Vert.Disp. Multiple samples of the vertical position along the bunch Vc Control signal Vb Momentum Kick Requirement for Feedback Control: Provide stability and satisfactory performance in the face of disturbances, system variations, and uncertainties. C. H. Rivetta ECLOUDS1- Cornell University October 1, 21 6
Feedback Systems Requirements Original system unstable- Minimum gain for stability Delay in control action - Maximum gain limit Bunch Dynamics Nonlinear - tunes/growth rates change intrinsically Beam Dynamics change with the machine operation noise-perturbations rejected or minimized Vertical displacement signals has to separated from longitudinal/horizontal signals Control up-date time = T revolution C. H. Rivetta ECLOUDS1- Cornell University October 1, 21 7
Plan - Progress R & D lines Goal is to have a minimum prototype to fully understand the limitations of feedback techniques to mitigate E-cloud TMCI effects in SPS. High Level Simulation Reduced Model Control Design System Design - Implementation Measurements Validation Tests Commissioning R & D areas Study and Development of Hardware Prototypes Non-Linear Simulation Codes - Real Feedback Models - Multibunch behavior Development and Identification of Mathematical Reduced Dynamics Models for the bunch - Control Algorithms MD Coordination - Analysis of MD data - Data Correlation between MD data / Multiparticle results C. H. Rivetta ECLOUDS1- Cornell University October 1, 21 8
R & D areas Hardware - Complexity? Scale? Bunch Spectrum 12 Bunch # 45 Spectrum for turns 1 to 6 2 db 12 Bunch # 119 Spectrum for turns 1 to 6 2dB 1 1 1 1 8 8 Freq [MHz] 6 1 2 Freq [MHz] 6 1 2 4 3 4 3 2 4 2 4 5 1 15 2 25 3 35 4 45 5 55 6 Turns 5 5 1 15 2 25 3 35 4 45 5 55 6 Turns 5 stack 1-bunch 47 stack 2 - bunch 47 (bunch 119) Frequency spectrogram of bunch oscillations suggests for this case that a 4 Gsamples/sec (Nyquist limit) could be enough to measure the most unstable modes C. H. Rivetta ECLOUDS1- Cornell University October 1, 21 9
R & D areas Hardware - Complexity? Scale? Assuming 16 samples/bunch/turn, 72x6 bunches/turn, 16 Multiplications/Accumulate (MACs) operations per sample (Proc. Ch. 16 taps FIR). SPS = 6*72*6*16*43Khz = 5 GigaMACs/sec KEKB igp system = 8 GigaMACs/sec, (existent) Dynamic bandwidth to process 4 Gs/sec Amplifier - Kicker: bandwidth limit about 1-2GHz, Power-Gain?? Installed Kicker: Limited in bandwidth and power Study option for kicker Receiver - Pick-up Installed Pick-up: No major limitations - Propagation modes 1.7MHz Study receiver topology - noise / spurious perturbations floor C. H. Rivetta ECLOUDS1- Cornell University October 1, 21 1
4 MHz 2 GHz 43.347 khz (26GeV) Introduction Feedback Systems - Generalities R & D Plan - Progress Conclusions R & D areas Hardware - Processing Channel - Excitation Prototype SPS RF Clock Signals from SPS SPS Turn Clock SPS Injection Signal Prototype Processing Channel SPS ecloud/tcmi Feedback February 21 A. Bullitt, J.D. Fox SLAC 5x Harmonic Multiplier Quadrature Generator ADC 1 MAX19 Digital Bus Low Level Signal Power Signal Splitter FPGA DAC MAX19693 Amplifiers Reciever ADC 2 MAX19 Analog: 2x 2 GSps Interleaved 2.8 GHz Input Bandwidth Async FIFO In 5 MHz 7 LVDS Analog: 4 GSps 1.5 GHz min. Bandwidth Digital: 5 MHz Data: 4 channels 8 bits/channel LVDS ADC Control Out 2 LVDS Async FIFO Out 1 GHz 48 LVDS Digital: 1 GHz Data: 4 channels 1 bits/channel LVDS Status: 3 bits LVDS DAC Control In 1 LVDS Control: DATACLK: 1 bit LVDS Control RSTIN: 1 bit LVDS SPS Plant Pickup Beam Wideband Kicker(s) Can we build a small prototype style feedback channel? What fits in our limited LARP hardware budget? Develop for driving beam (identification) and closed-loop tests in SPS Idea - build 4 GS/sec. channel via evaluation boards and SLAC-developed Vertex 5 FPGA processor C. H. Rivetta ECLOUDS1- Cornell University October 1, 21 11
R & D areas Hardware - Kicker / Pick-up Amplifier - Kicker. Critical missing elements Test power amplifiers, set cable plant, loads for existent kicker. Drive the bunch with the actual hardware. Identify the Kicker technology as an accelerated research item, Study best kicker topology for prototype. Kicker design/fab requires joint CERN/US plans. Design kicker and vacuum components for SPS fabrication and installation C. H. Rivetta ECLOUDS1- Cornell University October 1, 21 12
Plan - Progress Non-Linear Simulations Multiparticle simulation codes have been a very useful test-bench for designing MD analysis algorithms and tools. Important for the development of mathematical reduced dynamics models of the bunch. Next step related to feedback control system: Add realistic models representing the receiver, processing channel, amplifier and kicker hardware. Test-bench to test feedback control system design.!!!!!"#$!%! Receiver + 9=! 4,5.+66)27! 9.! 9<! #&'()*+,!%! ADC V!$3822+(! V c1 V y1 V y8-16 c8-16 -)./+,! + Noise 9+,:;!")6'(;! y 1 y 64 12.3! Vb V b1 V b64 J-L Vay - R.Secondo talks C. H. Rivetta ECLOUDS1- Cornell University October 1, 21 13
Plan - Progress Mathematical Modeling and Feedback Design From previous analysis : Bunch Dynamics is unstable, non-linear. Delay in the control action. Noise and spurious perturbations. Limited Power. Parameters change. What is the best control strategy?? Unique robust control Scheduled robust control Adaptive controller Complexity: One control algorithm per sample or Multi-input/Multi-output algorithms. Control Design using Model-Based Design Mathematical reduced dynamics models of the bunch. Requires identification of the bunch dynamics (Measurement of the response to a given excitation) C. H. Rivetta ECLOUDS1- Cornell University October 1, 21 14
Plan - Progress Identification of Internal Bunch Dynamics: Reduced Model Characterize the bunch dynamics - same technique for simulations and SPS measurements Critical to design the feedback algorithms Ordered by complexity, the reduced models could be Linear models with uncertainty bounds (family of models to include the GR/tune variations) Linear with variable parameters (to include GR / tune variations - Synchrotron osc. - Different op. cond.) Non-linear models C. H. Rivetta ECLOUDS1- Cornell University October 1, 21 15
Plan - Progress Closed-Loop feedback around the Reduced Model.','%5'())*) 6(4,7)892::'$) ;,)!"#$%&'()*) ;<).'/,'/) ;'(=7)>%?#$7) +%,-'() 1'2")34/'$) Use the reduced model, with realistic feedback delays and design a simple FIR controller 1 Transfer function for a 5 TAP FIR Filter Each slice has an independent controller This example 5 tap filter has broad bandwidth - little separation of horizontal and vertical tunes But what would it do with the beam? How can we estimate performance? Coefficients Magnitude [db.] Phase [deg.].5.5 1 1 1.5 2 2.5 3 3.5 4 4.5 5 Taps 2 1 1 2.5.1.15.2.25.3.35.4.45.5 Normalized frequency 2 1 1 Nominal Tune =.19 2.5.1.15.2.25.3.35.4.45.5 Normalized frequency C. H. Rivetta ECLOUDS1- Cornell University October 1, 21 16
Plan - Progress Root Locus Study - Tune shifted from.185 to.21 We study the stability for a range of tunes This filter can control both systems- Maximum damping is similar in both cases Is this realistic case to design? We need more data from simulations and MD We need models for dynamics vs. beam energy, interaction with ramp 1 Root locus for fractional tune.185 and.21 (Detail) frac. tune =.21 (red) frac. tune =.185 (blue) 1.1 1.5 Root locus for fractional tune.185 and.21 (Detail) frac. tune =.21 (red) frac. tune =.185 (blue).8 1.6.4.95.2.9 Imag Imag.85.2.8.4.75.6.8.7 1.65 1.8.6.4.2.2.4.6.8 1 Real.6.1.15.2.25.3.35.4.45.5 Real C. H. Rivetta ECLOUDS1- Cornell University October 1, 21 17
Plan - Progress MD plans To validate multiparticle simulation codes, we are planing more MDs in SPS. It will help to have good test-bench multiparticle simulators to test feedback designs. In this MD we want to drive the bunch using the existent SPS kicker. Currents below E-cloud threshold (stable bunch). Important to test the power level and kicker gain for prototyping new kicker. Test of SLAC hardware - Back-end - Synchronization with SPS machine - Timing. If it is possible to drive different sections of the bunch, test identification algorithms. - Calculate reduced dynamic model of bunch. Perform bunch model identification at current levels near the instability threshold. Plan next MD to stabilize a few bunches C. H. Rivetta ECLOUDS1- Cornell University October 1, 21 18
Conclusions Summary - 21 LARP Ecloud/TMCI effort Lab effort -development 4 GS/sec. excitation system for SPS Modify existing system to synchronize with selected bunches - data for system identification tools Identify critical technology options, evaluate difficulty of technical implementation Explore 4 Gs/sec. small prototype feedback channel for 211 fab. and MD use Evaluate SPS Kicker options: CERN request, 212 shutdown window Understand E-cloud dynamics via simulations and machine measurements Participation in E-Cloud studies at the SPS (July 21) - Data under Analysis Analysis of SPS and LHC beam dynamics studies, comparisons with E-cloud models Modeling, estimation of E-Cloud effects Validation of Warp, Head-Tail and CMAD models, comparisons to MD results Integrate realistic models of feedback system hardware in Warp, Head-Tail and CMAD simulators. Comparisons with machine physics data (driven and free motion), Critical role of E-cloud simulations in estimating future conditions, dynamics Extraction of system dynamics, development of reduced coupled-oscillator model for feedback design estimation C. H. Rivetta ECLOUDS1- Cornell University October 1, 21 19
Conclusion Request for SPS Feedback System What can we do for the 212 SPS shutdown? CERN s interest - very high. Critical missing element - useful high-power kicker and power amplifier components in SPS Identify the Kicker technology as an accelerated research item, design prototype kicker and vacuum components for SPS fabrication and installation Kicker design/fab requires joint CERN/US plans. FY 211 - Accelerated research and design report on Kicker System Design report, suggested implementation, test low power lab models, RF simulation. FY212 - Detailed design and fab of prototype kicker, vacuum components FY213 - Installation in SPS with Amplifiers and Cable plant Vacuum components essential for shutdown Dovetails with parallel system estimation and development of quick prototype processor Model closed-loop dynamics, estimate feedback system specifications Evaluate possible control architectures, implementations, via technology demonstrations SPS Machine Physics studies, development of small prototype, closed loop studies stabilizing a few bunches. C. H. Rivetta ECLOUDS1- Cornell University October 1, 21 2
Thanks to the audience for your attention!!!,...questions? C. H. Rivetta ECLOUDS1- Cornell University October 1, 21 21