Process Simulation and Control

Continuous chemical processes are inherently dynamic systems – process inputs and outputs change in time. To accommodate this, modern plants require some form of automatic control. This subject equips students with the skills to understand how and why key process variables change in time, and to then design and implement effective control strategies to accommodate this. Students are introduced to the concept of feedback control, with examples of control schemes for common unit operations. The development of dynamic process models is introduced, along with analytical and numerical techniques for process simulation. Process simulation is performed using linear ordinary differential equation models, Laplace transforms, transfer functions, and numerical methods. The response of complex process plants to common dynamic inputs is investigated. Students are introduced to frequency response analysis and Bode plots. The process control component of the subject introduces the concept of closed loop transfer functions and the PID controller. Dynamic process simulation is performed using analytical techniques and with the numerical simulation capabilities of software packages including MATLAB Simulink. The stability of closed loop systems is analysed using techniques such as Routh stability analysis, the Bode stability criterion, and gain and phase margins. The effect of controller tuning constants on control system response is investigated, along with various controller tuning methods. Advanced control strategies including cascade control, time-delay compensation, and feedforward control are developed, as well as techniques to simultaneously control multiple process variables in multiloop systems.