7 Identification of Dynamic Systems & Selection of Suitable Model Mohsin Jamil, Dr. Suleiman M Sharkh and Babar Hussain School of Engineering Sciences, University of Southampton England 1. Introduction Process Industry is growing very rapidly. To tackle this fast growth, current control methods need to be replaced to produce product with compatible quality & price. Normally the systems are described by suitable mathematical models. These models are replaced by actual process later on. Actually controllers are designed on behalf of suitable models to control the process effectively. So suitable models are very crucial. Different purposes demand for different types of models where the objective could be: (Bjorn Sohlberg, 2005) • Construction of controllers to control the process. • Simulation of control system to analyze the effect of changing reference • Simulate the behaviour of system during different production situations. • Supervise different parts of process which properties change due subjected to wear or changing product quality. The exact model of any system will reflect detailed description. A simple feedback controller demands a simple process description than a process description which is going to be used for supervision of wear. Often a more advanced application, demand for a more complex model. The relation between the purpose of the model and its complexity is shown below. Feedback Feedforward Process Process Control Control Simulation Supervision Model Complexity Fig. 1. Model Complexity The development of information technology has opened new prospective in modelling and simulation of processes used in different scientific applications. There are different types of models which will be discussed in next section. In this chapter we will discuss different types of models, Identification techniques using matlab identification toolbox & different examples. Several aspects on experimental design for identification purposes will be also discussed. In a nutshell this chapter will be useful especially for those who want to do linear black box identification. For any given system/process modelling & identification techniques would be useful to apply after proper understanding of this chapter.