5. Advanced Control Strategies for DWC

  1. Anton Alexandru Kiss

Published Online: 2 APR 2013

DOI: 10.1002/9781118543702.ch5

Advanced Distillation Technologies: Design, Control and Applications

Advanced Distillation Technologies: Design, Control and Applications

How to Cite

Kiss, A. A. (2013) Advanced Control Strategies for DWC, in Advanced Distillation Technologies: Design, Control and Applications, John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9781118543702.ch5

Publication History

  1. Published Online: 2 APR 2013
  2. Published Print: 12 MAR 2013

ISBN Information

Print ISBN: 9781119993612

Online ISBN: 9781118543702



  • dynamic simulations;
  • generic model control (GMC);
  • loop shaping design procedure (LSDP);
  • LQG/LQR control;
  • mathematical model;
  • model predictive control (MPC);
  • multi-variable controller μ-synthesis;
  • PID control


Distillation processes presents many challenging control problems, such as nonlinear dynamic behavior, uncertain and time varying parameters, and unmeasured disturbances. This chapter addresses advanced control strategies for DWC, which can make the nonlinear process control much more practical. A dynamic model of a DWC is presented and used on an industrial case study (BTX separation) to illustrate the performance of various advanced control strategies, such as linear quadratic Gaussian (LQG), generic model control (GMC), H loop shaping design procedure (LSDP), multivariable controller μ-synthesis (DK iteration procedure), and model predictive control (MPC). While PI control structures are also able to control the DWC, significantly shorter settling times and lower overshooting can be achieved using MIMO controllers. A very practical scheme based on combination of MPC and PID controllers is also proposed to overcome the disadvantages of individual structures.