FeedForward Prof. Ing. Michele MICCIO Dip. Ingegneria Industriale (Università di Salerno) Prodal Scarl (Fisciano)  adapted from Romagnoli & Palazoglu’s Chapter 16: Model-Based Control  see also Stephanopoulos,1984 Chapter 21  §21.1-4 rev. 3.1 of May 11, 2017

Romagnoli & Palazoglu, “Introduction to Process Control “ Definition of Model-Based Control Detailed Process Understanding Intelligent Use of Modern Control Systems Improved Profitability $ The combination of detailed process understanding with the intelligent use of modern control systems (hardware, software and technology) to achieve improved profitability. Romagnoli & Palazoglu, “Introduction to Process Control “

Romagnoli & Palazoglu, “Introduction to Process Control “ Model-Based Control In this course we consider the following control design techniques that explicitly use the process model: Delay Compensation (Smith Predictor) Inverse Response Compensation Feedforward control Model Predictive Control (MPC) Romagnoli & Palazoglu, “Introduction to Process Control “

Romagnoli & Palazoglu, “Introduction to Process Control “ Feedforward Control Feedback control can never achieve perfect control of a chemical process. It reacts to the changes in the controlled variable after a deviation is detected in the output. Manipulated variable Controlled variable Controller Process Disturbance Set-point Sensor Romagnoli & Palazoglu, “Introduction to Process Control “

Romagnoli & Palazoglu, “Introduction to Process Control “ Feedforward Control A feedforward controller measures the disturbance directly and takes control action to compensate for its eventual impact on the output variable. Feedforward controllers have the theoretical potential for perfect control. Romagnoli & Palazoglu, “Introduction to Process Control “

Feedforward Control Consider the following feedforward flow of information about disturbance … Process Manipulated variable Controlled variable Controller Disturbance Set point Feedforward Controller output Final control element  the feedforward controller predicts the effect of disturbances. Romagnoli & Palazoglu, “Introduction to Process Control “

Romagnoli & Palazoglu, “Introduction to Process Control “ Feedforward Control Design We want to achieve the following control objective: y(t) = ysp(t) Therefore, in the Laplace domain: m(s) y(s) d(s) gp(s) gd(s) We shall require: 1 Romagnoli & Palazoglu, “Introduction to Process Control “

Romagnoli & Palazoglu, “Introduction to Process Control “ Feedforward Control Design We introduce a suitable structure for the feedforward controller. Then, we further determine m(s) from the block algebra: 2 p g f 2 ff md 1 y sp + gd d − disturbance measurement final control element m 3 process vs. disturbance actual feedforward controller o process Romagnoli & Palazoglu, “Introduction to Process Control “

Romagnoli & Palazoglu, “Introduction to Process Control “ Feedforward Control The feedforward control elements are not conventional controllers (P, PI or PID) The feedforward controller: needs the gff1 block in order to make the set point comparable to the measured disturbance depends on the knowledge of process and disturbance models can be developed for more than one disturbance and for multiple controlled variables Romagnoli & Palazoglu, “Introduction to Process Control “

Feedforward vs Feedback  Feedforward - Advantages Acts before disturbances affect the process Cannot cause instability Good for slow process dynamics  Feedforward - Disadvantages Must identify and measure ALL disturbances Fails for unmeasured disturbances Needs to have a reliable process dynamic model Fails for changes within the process No indication of control quality Romagnoli & Palazoglu, “Introduction to Process Control “

Romagnoli & Palazoglu, “Introduction to Process Control “ Feedforward vs Feedback  Feedback - Advantages No disturbance measurements needed Limited or even no process model needed Can cope with changes within process  Feedback - Disadvantages Will always be some error Poor for slow process dynamics, interaction, etc. Instability is possible Romagnoli & Palazoglu, “Introduction to Process Control “

Use a combination of Feedforward and Feedback control Feedforward-Feedback Control Use a combination of Feedforward and Feedback control We expect that a combined feedforward-feedback control system will retain, The superior performance of a feedforward controller, and The insensitivity of the feedback controller to uncertainties and inaccuracies. Romagnoli & Palazoglu, “Introduction to Process Control “

Example 1: Process with dead time Consider the following process TFs: gmd and gf purely algebraic Design a Feedforward Controller Compare with PI feedback design Romagnoli & Palazoglu, “Introduction to Process Control “

Example 1: process with dead time (disturbance rejection) FF Controller Feedback with a PI controller No modelling error +20% error in gd gain (Kd = 1.2) NB: Output signal = controlled variable Romagnoli & Palazoglu, “Introduction to Process Control “

Romagnoli & Palazoglu, “Introduction to Process Control “ Example 2: Heat Exchanger Manipulated variable Feedforward Controller Tout,sp Tout Steam Controlled variable TT FT Disturbances Design a FF controller to compensate for variations in the feed flow rate and temperature. Romagnoli & Palazoglu, “Introduction to Process Control “

Romagnoli & Palazoglu, “Introduction to Process Control “ Example 3 Distillation Column FF Controller Design a FF controller to compensate for variations in feed composition and flow rate. Manipulated variable Disturbances Controlled variable CT FT Romagnoli & Palazoglu, “Introduction to Process Control “