Advanced Control Strategies Applied to Bioprocesses: An Overview

Abstract

In the last decades, biology, agriculture, food science, and medicine technologies have been gathered in a new science field recognized as biotechnology. Of course, human beings have always been dependent on chemical and biochemical processes to meet their needs. But health care has taken such an important place in everyone's life that the economic potentialities of the biotechnology market have pushed the industry, e.g., food and biopharmaceuticals, to engage in a race at peak performance requiring more than the heuristics. Optimization of bioprocesses through monitoring and control is now the spearhead of many big industries for the next decades. Mechanistic models are widely used in bioprocess modeling mainly because of their lower degree of complexity (in comparison with microscopic models) allowing an easier control design which must be chosen, taking the plant particularities into account: – What is the plant optimum? – Which state variables should be controlled? – Are the controlled variables measurable? – If not, is there a way to correctly estimate or observe them? – Is a suboptimal solution more practical? – Should the controller have a certain complexity degree? Is the complexity degree a source of limitation? An overview of advanced control design techniques applied to different fields of biotechnology is presented.