Generalized Predictive Control And Bioengineering

M Mahfouf, D. A. Linkens

• Publisher: CRC Press
• Year: 2024
• eBook ISBN: 9781040290088
• Topic: Technology & Engineering
• Subtopic: Biotechnology in Medicine
• Index: Technology & Engineering

Predictive control is a powerful tool in dealing with those processes with large time delays. Generalized Predictive Control GPC is the most popular approach to the subject, and this text discusses the application of GPC starting with the concept of long-range predictive control and its need in medicine particularly automated drug deliveries.; The concept of adaptation is also emphasized with respect to patient-to-patient parameter variations. Subsequent chapters discuss interactions, comparisons and various aspects of GPC. The book concludes by putting into perspective the generic nature of the architecture built around GPC and which provides model-based fault diagnosis with control.

Table of contents

• Cover
• Half Title
• Also in the Systems and Control Series
• Title Page
• Copyright Page
• Table of Contents
• Series Introduction
• Acknowledgements
• 1 Introduction
• 1.1 Fundamental definitions
• 1.2 Automatic control in biomedicine
• 2 SISO Generalised Predictive Control (GPC) in Muscle Relaxation Therapy
• 2.1 Introduction
• 2.2 Physiological background pertaining to the muscle relaxation process
• 2.3 Atracurium mathematical model
• 2.4 Development of the adaptive GPC algorithm
• 2.5 Simulation studies
• 2.6 Performance of GPC in the operating theatre
• 2.7 Conclusions
• 3 Propofol Induced Anaesthesia: a Comparative Control Study Using a Derived Nonlinear Model
• 3.1 Introduction
• 3.2 Pharmacokinetic model for propofol
• 3.3 Automatic infusion of propofol based on pharmacokinetics and its problems
• 3.4 Pharmacodynamics associated with propofol
• 3.5 A comparative control study using the propofol nonlinear model
• 3.6 Conclusions
• 4 Multivariable Generalised Predictive Control in the Operating Theatre
• 4.1 Introduction
• 4.2 Identification of the nonlinear anaesthesia model
• 4.3 Development of the multivariable GPC algorithm for anaesthesia
• 4.4 Simulation results
• 4.5 Clinical evaluation of the multivariable anaesthesia control system
• 4.6 Conclusions
• 5 Constrained Multivariable Generalised Predictive Control for Anaesthesia: the Quadratic Programming Approach (QP)
• 5.1 Introduction
• 5.2 Theory of the constrained multivariable generalised predictive control
• 5.3 Simulation results
• 5.4 Conclusions
• 6 Generalised Predictive Control with Feedforward (GPCF) for Multivariable Anaesthesia
• 6.1 Introduction
• 6.2 Multivariable GPC with feedforward
• 6.3 Simulation results
• 6.4 Conclusions
• 7 Generalised Predictive Control with Long Range Predictive Identification (LRPI) for Multivariable Anaesthesia
• 7.1 Introduction
• 7.2 Development of long range predictive identification (LRPI) algorithm and its implementation through filtering
• 7.3 Simulation results
• 7.4 Conclusions
• 8 A Comparative Study between Multivariable Generalised Predictive Control and Intelligent Self-organising Fuzzy Logic Control (SOFLC) for Multivariable Anaesthesia
• 8.1 Introduction
• 8.2 Review of multivariable self-organising control using fuzzy logic
• 8.3 Simulation studies
• 8.4 Discussions and conclusions
• 9 Generalised Predictive Control with Pre-specified Set-points in Clinical Anaesthesia
• 9.1 Introduction
• 9.2 SISO GPC and the set-point pre-specification concept
• 9.3 Simulation results
• 9.4 MIMO GPC and the set-point pre-specification concept
• 9.5 Conclusions
• 10 Supervisory Generalised Predictive Control and Fault Detection for Multivariable Anaesthesia
• 10.1 Introduction
• 10.2 A review of faults associated with the multivariable control system
• 10.3 The hierarchical supervisory level: structure and algorithm
• 10.4 Simulation results
• 10.5 Conclusions
• 11 Nonlinear Generalised Predictive Control (NLGPC) for Muscle Relaxant Anaesthesia
• 11.1 Introduction
• 11.2 Theory of the proposed nonlinear GPC algorithm (NLGPC)
• 11.3 Simulation results
• 11.4 Objective comparison between linear GPC and the new nonlinear controller
• 11.5 Conclusions
• 12 Conclusions and Further Work
• 12.1 Summary of the book’s main contributions
• 12.2 Future work
• Appendix I Modelling of Multivariable System Dynamics
• Appendix II Recursive Least-squares Algorithm: the Multivariable Case
• Appendix III Converting the LSI Problem to the LDP Problem: the Constrained Solution
• References
• Index