Evolutionary Computing: Opportunities for Control Engineers

Abstract

Control systems engineers regularly use optimisation in design and on-line applications. However, increasingly, due to the nature of the search space or because of the decision variable data types, for example, these problems cannot be solved satisfactorily using traditional approaches. Evolutionary computing (EC) offers certain advantages over traditional approaches for many of these problems, and those features that confer particular benefits for control applications are described here. As a result of these new opportunities, evolutionary algorithms have been applied to controller design and model identification, for both parameter and structural optimisation and for handling multiple competing performance objectives. Examples, including real-time and industrial uses of EC are described, together with other applications involving fault diagnosis, system analysis, robotics, sensor-actuator placement and optimisation for fuzzy and neural control. The rapid developments in computer technology will permit further realisation of the potential of EC and future perspectives are discussed.