University of Illinois Urbana-Champaign

Automation of power adaptation for electrosurgery

Prakash, Praveen

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https://hdl.handle.net/2142/124683

Description

Title
Automation of power adaptation for electrosurgery
Author(s)
Prakash, Praveen
Issue Date
2024-05-01
Director of Research (if dissertation) or Advisor (if thesis)
Bentsman, Joseph
Department of Study
Mechanical Sci & Engineering
Discipline
Mechanical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
  • Electrosurgery
  • Power Adaptation
  • Power Tracking
  • Control
  • Cutting
  • Coagulation
  • FPGA
  • GPC
  • Generalized Predictive Control
Abstract
Well-selected power with accurate delivery is of importance in electrosurgery to generate proper temperature at the cutting site, and thus, reduce undesired collateral tissue damages. The power reference setpoint is determined either based on temperature or impedance. Bao et al. [1] present PI controller for power adaptation using commercially low-cost industrial-scale digital signal processor (DSP). In this thesis different control algorithms for cutting and coagulation modes for power tracking are explored. The plant models are based on data obtained from electrosurgery experiments on live pigs. The controllers explored are: Linear Quadratic Regulator (LQR), General Predictive Control (GPC), and Direct methods. In LQR and GPC the reference current is updated in real-time to ensure power tracking using linear models. Moreover, the moving window approach is used to achieve faster adaptation. Further to assess the non-linearity in the plant model, wavelet based Non-linear Autoregressive model with Exogenous inputs are derived. To sample and precisely reconstruct signals of hundreds of kilohertz it is proposed to use Xilinx field-programmable gate array (FPGA). The implementation steps and results from these analyses are presented.
Graduation Semester
2024-05
Type of Resource
Thesis
Copyright and License Information
Copyright 2024 Praveen Prakash

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