2-1 Introduction

The dynamics of a process response can be modeled by three types of parameters: dead time, time constant, and process gain. The dynamics are identified from the plant's operation, and they determine both the process's ultimate performance and the actual performance of the control system. The process dynamics are used to compute PID controller settings. They could also be employed directly to predict the trajectory of process outputs from past process inputs in future applications of model predictive control (MPC) for bioreactors. Although MPC technology has been used almost exclusively on continuous processes, recent batch applications are promising, and it is anticipated that bioreactor applications are possible.

Section 2-2 of this chapter discusses the largest sources of dead time in the automation and process systems, the impact of total dead time on the controller's capability and tuning, and the procedure for estimating the performance based on the tuning settings. Section 2-3 details the characteristics of a self-regulating process response, the way small time constants effectively become dead time, and the reasons why the location of the largest time constant affects control. Section 2-4 delves into the integrating process response of the more important process variables as well as the implications of this response for process testing and controller tuning,