Process Control & Model Predictive Control

EEEN60441 Process Control & Model Predictive Control 15 Semester 1 Postgraduate Taught Level 6 Ognjen Marjanovic Unit coordinator Alexandru Stancu Unit coordinator 1 FHEQ level (Framework for Higher Education Qualifications) ' Masters/Integrated Masters P4 ' European Credit Transfer & Accumulation System Rating : 7.5 BRIEF DESCRIPTION OF THE UNIT:<div style="margin-left:18.0pt;"> Part A: Process Control</div><div style="margin-left:54.0pt;"> <ul> <li> PID controller structure: ideal/parallel/series, position/velocity implementation of digital PID.</li> <li> PID controller tuning: Ziegler-Nichols and Cohen-Coon, Internal Model Control with lambda-tuning.</li> <li> Enhanced control: cascade control, feedforward control, multi-loop control utilising de-couplers, Smith Predictor.</li> <li> Multi-loop interaction analysis using Relative Gain Array.</li> <li> Real-time process optimisation using Linear Programming technique.</li> </ul></div><div>  </div><div style="margin-left:18.0pt;"> Part B: Model Predictive Control (MPC)</div><div style="margin-left:54.0pt;"> <ul> <li> MPC control formulation: simple unconstrained optimal control formulation, general characteristics of MPC formulation, translation of MPC problem into quadratic programming optimisation problem, constant output disturbance observer model, infeasibility and softening of the constraints.</li> <li> Practical MPC implementation considerations: empirical model development, usage of design/tuning parameters, implementation/commissioning of MPC.</li> <li> Design of MPC control for typical CSTR chemical reactor as well as distillation column.</li> </ul></div>  BRIEF DESCRIPTION OF THE UNIT:<div style="margin-left:18.0pt;"> Part A: Process Control</div><div style="margin-left:54.0pt;"> <ul> <li> PID controller structure: ideal/parallel/series, position/velocity implementation of digital PID.</li> <li> PID controller tuning: Ziegler-Nichols and Cohen-Coon, Internal Model Control with lambda-tuning.</li> <li> Enhanced control: cascade control, feedforward control, multi-loop control utilising de-couplers, Smith Predictor.</li> <li> Multi-loop interaction analysis using Relative Gain Array.</li> <li> Real-time process optimisation using Linear Programming technique.</li> </ul></div><div>  </div><div style="margin-left:18.0pt;"> Part B: Model Predictive Control (MPC)</div><div style="margin-left:54.0pt;"> <ul> <li> MPC control formulation: simple unconstrained optimal control formulation, general characteristics of MPC formulation, translation of MPC problem into quadratic programming optimisation problem, constant output disturbance observer model, infeasibility and softening of the constraints.</li> <li> Practical MPC implementation considerations: empirical model development, usage of design/tuning parameters, implementation/commissioning of MPC.</li> <li> Design of MPC control for typical CSTR chemical reactor as well as distillation column.</li> </ul></div>  This course unit detail provides the framework for delivery in the current academic year and may be subject to change due to any additional Covid-19 impact.  Please see Blackboard / course unit related emails for any further updates.The course unit aims to:<div>1. Introduce students to the fundamental concepts of applied industrial process control, including cascade and feedforward control structures as well as the use of de-couplers.2. Introduce students to the formulation and the main implementation details regarding Model Predictive Control (MPC) as well as the real-time process optimisation.</div>  <table border="1" cellpadding="0" cellspacing="0" width="0"> <tbody> <tr> <td colspan="2" style="width:496px;"> All intended learning outcomes below are Developed and Assessed. On the successful completion of the course, students will be able to: </td> </tr> <tr> <td style="width:64px;"> ILO 1</td> <td style="width:432px;"> Design PID controller using Ziegler-Nichols, Cohen-Coon and Internal Model Control principle.</td> </tr> <tr> <td style="width:64px;"> ILO 2</td> <td style="width:432px;"> Design feedforward and cascade controllers as well as de-coupler-based multi-loop control systems for process control applications.</td> </tr> <tr> <td style="width:64px;"> ILO 3</td> <td style="width:432px;"> Solve real-time process optimisation problem using linear programming method.</td> </tr> <tr> <td style="width:64px;"> ILO 4</td> <td style="width:432px;"> Describe Model Predictive Control problem formulation using state-space system model format.</td> </tr> <tr> <td style="width:64px;"> ILO 5</td> <td style="width:432px;"> Convert optimisation-based control problem formulation into general mathematical programming formulation.</td> </tr> <tr> <td style="width:64px;"> ILO 6</td> <td style="width:432px;"> Derive and analyse unconstrained optimal control law for simple low-order single-input, single-output systems.</td> </tr> <tr> <td style="width:64px;"> ILO 7</td> <td style="width:432px;"> Design Model Predictive Control by selecting appropriate weights in the corresponding cost function.</td> </tr> <tr> <td style="width:64px;"> ILO 8</td> <td style="width:432px;"> Summarize the key steps of implementing Model Predictive Control, including development of empirical prediction model and the procedure of controller commissioning.</td> </tr> </tbody></table>  <div> This unit is taught during 6-week period during which several 3-hour lectures take place every week and two 3-hour lab sessions are scheduled to take place during the 6-week period.</div>  0 Other 20% 1 Written exam 80% <table border="1" cellpadding="0" cellspacing="0" width="0"> <tbody> <tr> <td style="width:291px;"> Coursework Assessment task</td> <td style="width:151px;"> How and when feedback is provided</td> <td style="width:95px;"> Weighting within unit (if relevant) </td> </tr> <tr> <td style="width:291px;">  Motor Speed and Position Control Lab</td> <td style="width:151px;"> Online submission in Blackboard, individual performance feedback is provided two weeks after students submit their answers.</td> <td style="width:95px;">  10%</td> </tr> <tr> <td style="width:291px;"> MPC Control of Simulated Distillation Column</td> <td style="width:151px;"> Online submission in Blackboard, individual performance feedback is provided two weeks after students submit their answers.</td> <td style="width:95px;"> 10%</td> </tr> </tbody></table>  . EEEN64401 Pre-Requisite Compulsory EEEN60109 Pre-Requisite Compulsory N “Process Dynamics and Control”, Seborg, Edgar, Mellichamp.“Predictive Control with Constraints”, Maciejowski.  Lectures 24 Practical classes & workshops 6 0 120