fault-recovery procedures and associated r&d frédéric bouly (ipno/cnrs) - isaías martín...

Fault-recovery procedures and associated R&D

Frédéric Bouly (IPNO/CNRS) - Isaías Martín (ADEX)

MYRRHA accelerator 1st International Design reviewWP3 - Task 3.2WP1 - Task 1.2

Bruxelles, Belgium Tuesday, 13th November 2012

Accuracy requirements

2INTRODUCTION

Bouly F. & Martín I. MYRRHA accelerator 1st International Design review, Bruxelles 13th November 2012

■ Requirement on Energy accuracy : 600 MeV ± 1 MeV at the linac ouput . Control systems to ensure stability of the accelerating field and the synchronous phase

■ Superconducting cavities gets a Q0 (1010 at 2K) with a 106 < QL < 106 100 Hz High sensitivity to mechanical perturbations ( Lorentz force, microphonics )

Accuracy requirements

Complete board withanalogue

mezzanine

Objectives

3INTRODUCTION

Bouly F. & Martín I. MYRRHA accelerator 1st International Design review, Bruxelles

■ LLRF Digital system for the control of Eacc & ϕs Signal processing : In phase / Out of phase (I/Q) formalism

■ Cavity frequency tuned to maintain RF power margins (CW) Fast cold tuning system + controller & feedback loop

PXI V2 board: 5 ADC (14 bits @ 80 MHz ), 3 DAC ( 14 bits @ 80 MHz )FPGA handles: IQ demodulation, FIR and PID filtering, online monitoring via SDRAM, embedded NIOS II softcore processor for slow control operations ( collaboration LPNE/IPNO – IN2P3/CNRS Labs)

Down converter system (19’’rack)

■ Study the feasibility of retuning procedures (< 3 sec.) for the individually controlled cavities with a limited margin of CW RF power.

Worked based on the β 0.47 linac section Model : cavity + tuning system + feedback/control loops Use of Matlab SimulinkTM for time simulation Define the best control strategy for the tuning system - R&D on an adaptive & predictive controller (ADEX).

13th November 2012

4

Introduction

Cavity model & global control strategy -

Dynamic study of a fast fault-recovery procedure-

Tuning system controller R&D-

Conclusion & Prospects


5

Introduction






RF cavity model

6

■ Band pass resonator RLC parallel circuit.

■ RF amplifier & beam seen as current generator for the cavity.■ One can link the cavity parameters ((r/Q), Q0 ,QL ) to RL (or R), L et C.

Cavity model & global control strategy


Stationary Transient

13th November 2012

7 Cavity model & global control strategy


Control strategy (1/3) Complex plane representation : Cavity not frequency tuned

Re

Im

Ib O

Vb

ψψ

Ig

VgVb

ϕs

Vg (at ω0 = ω)

Vinc

Vrefφg

Vcav

■ Accelerating Field :Vacc = Vcav cos(ϕs) = VcI

■ ψ depends on the cavity frequency tuning :

Vb(at ω0 = ω)

φg

13th November 2012



Control strategy (2/3)

Optimal tuning is achieved to minimise the reflected power at the cavity input.

Re

Im

Ib O

Ig

ϕs

Vinc

Vref

VcavVb(at ω0 = ω)

Ig VincVref

Optimal frequency (de)tuning :

We want to reach the optimal cavity frequency

13th November 2012



Control strategy (3/3)

Re

Im

Ib

O ϕsVcav

Vb(at ω0 = ω) Ig

Vg (at ω0 = ω)

φg

Vg

Vb

Vb

ψψ

φg

VincVref

Optimal frequency detuning :

When the optimal detuning is achieved : φg= ϕs 13th November 2012



Control scheme for superconducting Cavity

Amp.

CAVITY

Cold Tuning System

Amp.

Perturbations : Lorentz detuningMicrophonicsHe bath pressure …

VcIset-p

,VcQset-p

VcI VcQ

_+

-+

++

ΔfSAF

ΔfL, ΔfmicLLRF Loop

CTS Loop

Beam

Low Level RF

Controller

ΔfHe

ϕSset-p

φg

φg

=0

13th November 2012

11

Introduction






12 Study of a fault-recovery procedure


Fault tolerance for the MYRRHA linac

■ Fault tolerant : less than 10 unintended beam trips longer than 3 seconds - per 3 mounts operation cycle.

■ Main beam trips origins in a linac : Injectors (source, RFQ, re-buncher) → 2 injection lines for MYRRHA (1 spare line) RF amplifier→ Main problem for the individually controlled cavities

■ Local compensation with “limited” RF CW power:

Cavities are independantly powered 1 failed cavity (or 1 Cryomodule) is compensated by 2 cavities (or 2 Cryomodules) placed upstream & 2 cavities (or 2 Cryomodules) placed downstream. One has to be able to detect the failed element and to retune the cavities in less than 3 seconds.

13th November 2012



LLRF feedback loop model

■ Modelled in I/Q formalism - Transfer function in Laplace domain: Maximum RF power available 30 kW. Numerical system effects : Delay + ZOH + modulator. PI correctors adjusted to minimise beam loading effect.

13th November 2012



CTS control loop

■ Transfer function of the cold tuning system modelled from measurements

13th November 2012



Choice for the CTS controller■ Different option for the Tuning system controller have been studied :

A PI corrector - An adaptive and predictive system (from ADEX)

Example: Simple frequency control Example: strong microphonics perturbations

The Control is lost with PI controller

13th November 2012



A fault-recovery scenario

Recovery from the failure of a β 0.47

cryomodule

Cavity n°76One of the

compensation cavities

Cavity n°77One cavity of

the failed module

13th November 2012



Scenario description

compensation cavityCavity n°76

Failed cavityCavity n°77

13th November 2012



Compensation cavity (n°76)

13th November 2012

-45



Failed cavity (n°77)

Motor detuning action at 1 kHz/sec

Beam deceleration150 keV >> 22.25 keV (higher than acceptable limit from the 0.5 % error tolerance)

Motor must detune the cavity at a speed higher than 5 kHz/sec.

13th November 2012

20

Introduction






21 Tuning system controller R&D


The ADEX system■ The ADEX system use an adaptive and predictive control methodology

■ Predictive : instead of reacting to the error already produced, like PIDs, it predicts the process variable's evolution and thus anticipating to the predicted drifts from their set points.

■ Adaptive : it learns in real time from the changing process dynamics in order to have a permanent precise prediction. The adaptive mechanism informs the driver block about the current process status and of the process output deviation from the desired trajectory.

13th November 2012


Hardware definition

■ In view of carry out real scale “fault-recovery” experiment a control prototype board is developed. It may support the execution of both conventional PID and ADEX control■ Board development collaboration ADEX (A. Nevado) & IPNO (N. Gandolfo).■ The control period of the ADEX algorithm is 2 milliseconds.

PROCESS

B3

DelfinoBoard

B2 B2

FPGA Board

Cyclone III

Main MCU Board

dsPIC33FMAINBUS

MAINBUS

ADEX’s objective: Executing the controller

in less than 2 ms

DAC

ADC

PIEZO




ADEX controller’s execution & communication

C2000 32 bit 28x Delfino™ Floating-point Series.

ADEX controller’s algorithm executed in 977.92 μs.

Communication trials have been performed with two Delfinos facing each other. The times spent for reading, writing and handling the necessary data are the following:

Reading: 64.09 μs

Writing: 26.00 μs

Handling: 28.51 μs

Overall: 118.60 μs.

13th November 2012

24

Introduction


Dynamic study of a fault-recovery procedure-



Bouly F. & Martín I. MYRRHA accelerator 1st International Design review, Bruxelles November 13th 2012

25

Bouly F. & Martín I. MYRRHA accelerator 1st International Design review, Bruxelles November 13th 2012

Conclusion■ Based on existing systems a model of the cavity and its feedback loops have been developed : cavity + cold tuning systems + LLRF system + tuning system control loop.

■ Results from simulations showed that it is possible to retune the cavities in less than 3 seconds.

■ Still, procedure feasibility depends on the failure detection speed : here 30 ms are assumed .■ It is therefore highly recommended to dispose of a “fast” tuning system (response time : ~ 1 ms) :

Otherwise, in certain cases, the spare RF power margin may not be sufficient

■ The unused cavity can disturb the beam-conditions to fulfil : Beam deceleration must be lower than 0,5% Δwnominal (~ 20 keV ) In worst case, the minimum required detuning Δf ≈ 12 kHz (> 140 * bandpass) has to be

achieved in less than 3 seconds.

■ So we need a tuning system which : Acts on a broad frequency band a minimum of 20/30 kHz around f0,

is quite fast to detune the failed cavity Vmini ≈ 5 kHz/sec, is very fast and precise for Lorentz detuning and microphionics compensation.

■ On this basis a modular electronic board (prototype) is developed to implement an adaptive & predictive controller of the CTS. To be tested with experimental 700 MHz cryomodule.

26

THANK YOU !

Frédéric Bouly MAX 3rd General meeting, Madrid 13th November 2012

fault-recovery procedures and associated r&d frédéric bouly (ipno/cnrs) - isaías martín...

Documents

v ref v cav v b

rf cavity model

v ref gg v cav

bruxelles control strategy

cavity frequency tuning

failed cavity

cavity input

v cq setp v ci v cq