Kontrol Home

Kontrol (also pronounced “control”) is a python package for KAGRA control system related work. It is intented for both offline and real-time (via Ezca and maybe diaggui and nds2 later) usage. In principle, it should cover all control related topics ranging from sensor/actuator diagonalization to system identification and control filter design.

Features

  • Complementary filter synthesis using \(\mathcal{H}_\infty\) methods [1].
    • Synthesize optimal complementary filters in a 2-sensor configuration.
  • Curve fitting
    • Fit transfer functions, spectral densities, etc.
  • Frequency series modeling (Soon deprecating. See Curve fitting).
    • Model-based empirical fitting.
    • Model frequency series as zero-pole-gain and transfer function models.
  • Sensing/Actuation Matrices.
    • Sensing/Actuation Matrices diagonalization with given coupling matrix.
    • General optical lever, horizontal and vertical optical lever sensing matrices, using parameters defined in kagra-optical-lever.
  • Spectral analysis
    • Noise spectral density estimation using 2-channel method [2]
    • Noise spectral density estimation using 3-channel method [3]
    • Time series simulation of a given spectral density.
  • Foton utilities.
    • Convert Python transfer function objects to Foton expressions
    • Support for translating transfer functions with higher than 20 order (the Foton limit).
  • Easy Channel Access (EZCA) utilities (wrapper)
    • Read and write matrices to EPICS record.
  • Transfer Function
    • Export transfer functions to foton expressions.
    • Save TransferFunction objects to pickle files.
  • Controller design
    • Auto-design of PID controller for oscillatory systems (like pendulum suspensions)
    • Auto-design of post-filters such as notch filters and low-pass filters.

Don’t hesitate to check out the tutorials!

Contents:

Indices and tables

[1]T. T. L. Tsang, T. G. F. Li, T. Dehaeze, C. Collette. Optimal Sensor Fusion Method for Active Vibration Isolation Systems in Ground-Based Gravitational-Wave Detectors. https://arxiv.org/pdf/2111.14355.pdf
[2]Aaron Barzilai, Tom VanZandt, and Tom Kenny. Technique for measurement of the noise of a sensor in the presence of large background signals. Review of Scientific Instruments, 69:2767–2772, 07 1998.
[3]R. Sleeman, A. Wettum, and J. Trampert. Three-channel correlation analysis: A new technique to measure instrumental noise of digitizers and seismic sensors. Bulletin of the Seismological Society of America, 96:258–271, 2006.