A simulation-based comparative analysis of PID and LQG control for closed-loop anesthesia delivery

被引:2
作者
Chakravarty, Sourish [1 ,2 ]
Waite, Ayan S. [1 ,2 ]
Abel, John H. [1 ,2 ]
Brown, Emery N. [1 ,2 ,3 ]
机构
[1] MIT, Picower Inst Learning & Memory, 77 Massachusetts Ave, Cambridge, MA 02139 USA
[2] Massachusetts Gen Hosp, Dept Anesthesia Crit Care & Pain Med, Boston, MA 02114 USA
[3] MIT, Inst Med Engn & Sci, 77 Massachusetts Ave, Cambridge, MA 02139 USA
关键词
Closed-loop control; physiological systems; LQG; PID; integral action; anti-windup; compartmental models; sigmoid-Emax; quantitative systems pharmacology; COMPUTER-CONTROLLED INFUSION; PROPOFOL;
D O I
10.1016/j.ifacol.2020.12.369
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Closed loop anesthesia delivery (CLAD) systems can help anesthesiologists efficiently achieve and maintain desired anesthetic depth over an extended period of time. A typical CLAD system would use an anesthetic marker, calculated from physiological signals, as real-time feedback to adjust anesthetic dosage towards achieving a desired set-point of the marker. Since control strategies for CLAD vary across the systems reported in recent literature, a comparative analysis of common control strategies can be useful. For a nonlinear plant model based on well-established models of compartmental pharmacokinetics and sigmoid-Emax pharmacodynamics, we numerically analyze the set-point tracking performance of three output-feedback linear control strategies: proportional-integral-derivative (PID) control, linear quadratic Gaussian (LQG) control, and an LQG with integral action (ILQG). Specifically, we numerically simulate multiple CLAD sessions for the scenario where the plant model parameters are unavailable for a patient and the controller is designed based on a nominal model and controller gains are held constant throughout a session. Based on the numerical analyses performed here, conditioned on our choice of model and controllers, we infer that in terms of accuracy and bias PID control performs better than ILQG which in turn performs better than LQG. In the case of noisy observations, ILQG can be tuned to provide a smoother infusion rate while achieving comparable steady state response with respect to PID. The numerical analysis framework and findings reported here can help CLAD developers in their choice of control strategies. This paper may also serve as a tutorial paper for teaching control theory for CLAD. Copyright (C) 2020 The Authors.
引用
收藏
页码:15898 / 15903
页数:6
相关论文
共 24 条
[1]   Closed Loop Anesthesia: Are We Getting Close to Finding the Holy Grail? [J].
Absalom, Anthony R. ;
De Keyser, Robin ;
Struys, Michel M. R. F. .
ANESTHESIA AND ANALGESIA, 2011, 112 (03) :516-518
[2]   Closed-loop control of anesthesia using bispectral index - Performance assessment in patients undergoing major orthopedic surgey under combined general and regional anesthesia [J].
Absalom, AR ;
Sutcliffe, N ;
Kenny, GN .
ANESTHESIOLOGY, 2002, 96 (01) :67-73
[3]  
Astrom K. J., 2021, FEEDBACK SYSTEMS INT, V2nd
[5]   AUTOMATIC ELECTROENCEPHALOGRAPHIC CONTROL OF GENERAL ANESTHESIA [J].
BICKFORD, RG .
ELECTROENCEPHALOGRAPHY AND CLINICAL NEUROPHYSIOLOGY, 1950, 2 (01) :93-96
[6]   Mechanisms of Disease: General Anesthesia, Sleep, and Coma. [J].
Brown, Emery N. ;
Lydic, Ralph ;
Schiff, Nicholas D. .
NEW ENGLAND JOURNAL OF MEDICINE, 2010, 363 (27) :2638-2650
[7]  
Crassidis J. L., 2011, OPTIMAL ESTIMATION D
[8]   GUARANTEED MARGINS FOR LQG REGULATORS [J].
DOYLE, JC .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1978, 23 (04) :756-757
[9]   Closed-Loop Control of Anesthesia: A Primer for Anesthesiologists [J].
Dumont, Guy A. ;
Ansermino, J. Mark .
ANESTHESIA AND ANALGESIA, 2013, 117 (05) :1130-1138
[10]   Robust control of depth of anesthesia [J].
Dumont, Guy A. ;
Martinez, Arturo ;
Ansermino, J. Mark .
INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, 2009, 23 (05) :435-454