Page 15 - Control Theory in Biomedical Engineering

4 Control theory in biomedical engineering

can be categorized into several classes: linear and nonlinear models, con-
tinuous or discrete models, deterministic or stochastic models, parametric
or nonparametric models, and lumped or distributed parameter models.
The human body contains a natural and autonomous control process that
can maintain human life (Cherruault, 2012; Banks, 2013; Hacısalihzade,
2013). However, in many cases, certain failures in the body process require
external control laws in order to regulate its natural behavior (Morari and
Gentilini, 2001; Iii et al., 2011). The external controllers can be based on
different control algorithms such as predictive, adaptive and optimal control
laws principles (Swan, 1981; Hajizadeh et al., 2018; Turksoy and Cinar,
2014). These different types of controllers can be also applied in commercial
artificial organs and assistive technologies in order to simulate natural human
functions (Turksoy and Cinar, 2014; Smith et al., 2018).
This chapter provides comprehensive information on mathematical
modeling and control-based modeling in physiology in order to explain
the complexity of the human body process. In addition, the chapter exam-
ines challenges in this wealth domain.
The chapter is structured as follows. Section 2 presents a comprehensive
review of mathematical modeling in physiology. Section 3 investigates
various control principles by pointing out their applications in physiology.
Finally, Section 4 provides the possible challenges for modeling and control-
ling systems in medicine. It also describes commercial artificial organs and
assistive technologies that guarantee easier life for patients.

2 Mathematical modeling in physiology

A physiological model is a mathematical representation that approximates
the behavior of an actual physiological system. Physiological models can
serve mainly for the following purposes: (1) to understand the physiological
system, (2) to predict its dynamics, and (3) to control the system under desirable
conditions. However, the main problem in physiological systems is to find
the appropriate mathematical models to describe real problems, especially
disease dynamics. In fact, mathematical modeling represents a valuable tool
for understanding the human body processes.

2.1 Modeling methodology

Fig. 1 describes the modeling process generally adopted for designing math-
ematical models for physiological systems (Kuttler, 2009). There are various
modeling approaches and their number is still increasing. Some modeling