© ABB Corporate Research Insert image here Control Performance Monitoring Alf Isaksson, Alexander Horch ABB Corporate Research PROST Seminar 22 January.

Slides:



Advertisements
Similar presentations
Model-based PID tuning methods Two degree of freedom controllers
Advertisements

ERT 210 Process Control & dynamics
PID Controllers and PID tuning
Copyright © Thomas Marlin 2013
Introductory Control Theory I400/B659: Intelligent robotics Kris Hauser.
Chapter 4: Basic Properties of Feedback
Ratio Control Chapter 15.
Plant-wide disturbance assessment with an application on a paper making process Zhang Di, M.Sc, Cheng Hui, M.Sc, Jämsä-Jounela Sirkka-Liisa, Professor.
Control performance assessment in the presence of valve stiction Wei Yu, David Wilson & Brent Young Industrial Information & Control Centre New Zealand.
A UTOMATING PID C ONTROLS IN M ATHCAD Neil Kuyvenhoven Engr 315 December 11,2002.
Introduction to Statistical Quality Control, 4th Edition Chapter 7 Process and Measurement System Capability Analysis.
P M V Subbarao Professor Mechanical Engineering Department
Collaboration FST-ULCO 1. Context and objective of the work  Water level : ECEF Localization of the water surface in order to get a referenced water.
CHE 185 – PROCESS CONTROL AND DYNAMICS
280 SYSTEM IDENTIFICATION The System Identification Problem is to estimate a model of a system based on input-output data. Basic Configuration continuous.
Practical Process Control Using Control Station
Feedback Controllers Chapter 8
A COMPUTER BASED TOOL FOR THE SIMULATION, INTEGRATED DESIGN, AND CONTROL OF WASTEWATER TREAMENT PROCESSES By P. Vega, F. Alawneh, L. González, M. Francisco,
Environmental Data Analysis with MatLab Lecture 24: Confidence Limits of Spectra; Bootstraps.
Econ 240C Lecture Part I. VAR Does the Federal Funds Rate Affect Capacity Utilization?
1 EE 616 Computer Aided Analysis of Electronic Networks Lecture 9 Instructor: Dr. J. A. Starzyk, Professor School of EECS Ohio University Athens, OH,
1 ECE 3336 Introduction to Circuits & Electronics MORE on Operational Amplifiers Spring 2015, TUE&TH 5:30-7:00 pm Dr. Wanda Wosik Set #14.
Enhancing Paper Mill Performance through Advanced Diagnostics Services Dr. BS Babji Process Automation Division ABB India Ltd, Bangalore IPPTA Zonal Seminar.
LECTURE#11 PID CONTROL AUTOMATION & ROBOTICS
بسم الله الرحمن الرحيم PID Controllers
Chapter 7 PID Control.
Calibration & Curve Fitting
Cascade, Ratio, and Feedforward Control
Proportional/Integral/Derivative Control
Component Reliability Analysis
Simple Linear Regression
Introduction to Statistical Quality Control, 4th Edition Chapter 7 Process and Measurement System Capability Analysis.
Chapter 6 Control Using Wireless Throttling Valves.
1 Chapter 2 We need to write differential equations representing the system or subsystem. Then write the Laplace transform of the system. Then we will.
Book Adaptive control -astrom and witten mark
Analysis of techniques for automatic detection and quantification of stiction in control loops Henrik Manum student, NTNU (spring 2006: CPC-Lab (Pisa))
Closed Loop Performance Monitoring: Automatic Diagnosis of Valve Stiction by means of a Technique based on Shape Analysis Formalism ( 1,2 ) H. Manum, (
PSE and PROCESS CONTROL
Chapter 8 Model Based Control Using Wireless Transmitter.
Automation & Control Any process consist of :- (1) Application (2) Control System The Process Application (Operative Part) Control System (Action Coordinator)
3. Sensor characteristics Static sensor characteristics
1 Chapter 5 Sinusoidal Input. 2 Chapter 5 Examples: 1.24 hour variations in cooling water temperature Hz electrical noise (in USA!) Processes are.
Model Reference Adaptive Control (MRAC). MRAS The Model-Reference Adaptive system (MRAS) was originally proposed to solve a problem in which the performance.
Chapter 16 Data Analysis: Testing for Associations.
PID CONTROLLERS By Harshal Inamdar.
ERT 210/4 Process Control Hairul Nazirah bt Abdul Halim Office: CHAPTER 8 Feedback.
Features of PID Controllers
Topic 4 Controller Actions And Tuning. Chemical Processes Self-regulating Process Dynamics SS Gain, Kp Deadtime, θ Lag, τ Integrating Process Dynamics.
Chapter - Continuous Control
Controllability Analysis for Process and Control System Design
Forecast 2 Linear trend Forecast error Seasonal demand.
MISS. RAHIMAH BINTI OTHMAN
 The differentiator or differentiating amplifier is as shown in figure.  This circuit will perform the mathematical operation of differentiation.
1 PID Feedback Controllers PID 反馈控制器 Dai Lian-kui Shen Guo-jiang Institute of Industrial Control, Zhejiang University.
2. Sensor characteristics Static sensor characteristics
EEN-E1040 Measurement and Control of Energy Systems Control I: Control, processes, PID controllers and PID tuning Nov 3rd 2016 If not marked otherwise,
Chapter 1: Overview of Control
Break and Noise Variance
Performance Supervision System
CHAPTER 29: Multiple Regression*
Process Control Engineering
Enhanced Single-Loop Control Strategies
Process and Measurement System Capability Analysis
بسم الله الرحمن الرحيم PID Controllers
Identification of Wiener models using support vector regression
A practical approach for process control optimization during start-up
Control Systems Prof Swanson MECH 3550.
PID Controller Design and
Outline Control structure design (plantwide control)
Control Systems Prof Swanson MECH 3550.
Presentation transcript:

© ABB Corporate Research Insert image here Control Performance Monitoring Alf Isaksson, Alexander Horch ABB Corporate Research PROST Seminar 22 January 2002

© ABB Coprorate Research Goal: detect and diagnose malfunctioning control loops

© ABB Coprorate Research Bad control manifests itself as oscillation or too high variance

© ABB Coprorate Research Methods needed to detect oscillations diagnose oscillations determine of variance is too large Since there are hundreds of loops methods should be automatic

© ABB Coprorate Research Oscillation detection Hägglund (1995). Consider areas between zero crossings (count if large enough). Stattin and Forsman (1998). Based on same idea, easier to use. Seborg and Miao (1999). Damping ratio of auto- correlation function.

© ABB Coprorate Research Stattin index: Compare areas between zero crossings

© ABB Coprorate Research Oscillation index Controller re-tuned 0 = no oscillation, 1 = perfect osc.

© ABB Coprorate Research Oscillation index trend plot days index Valve IP converter replaced

© ABB Coprorate Research Major advantage: correlation analysis oscillation loop 2 oscillation loop 1 Conclusion: The loops interact. One of them is likely to cause both oscillations

© ABB Coprorate Research Potential causes are... F FC static friction cycling load tight tuning

© ABB Coprorate Research If the cause is stiction... process output control signal cross-correlation

© ABB Coprorate Research If the cause is NOT stiction... process output control signal cross correlation

© ABB Coprorate Research Stiction diagnosis New method by Horch (1999) which utilizes that when stiction in valve, process variable and control signal have odd cross-correlation when ”not stiction” the signals are such that the cross-correlation is even (due to negative feedback)

© ABB Coprorate Research Example: two coupled loops F FC Q QC water pulp Stiction O.K.

© ABB Coprorate Research Example cont’d data concentration loopflow loop cross-corr. Diagnosis:stictionno stiction

© ABB Coprorate Research Important assumptions Cross- correlation method O.K. 4O4O Oscillation detectedSelf-regulating process Integral action No compressible media

© ABB Coprorate Research Example II: integrating plant no stiction two different level control loops no stiction stiction

© ABB Coprorate Research CCF-method useless for integrating plants! Integration destroys the specific correlation in the stiction case. CCF is even, no matter if stiction or not. Re-calculation (differentiation) does not solve the problem level control loop

© ABB Coprorate Research Idea! Look for discontinuities in the data!... ‘Second derivative is infinite’

© ABB Coprorate Research ) Differentiate the process output! stiction Y dy dt d2y dt2 no stiction

© ABB Coprorate Research a.) Histogram (ideally) no stiction d2y dt2 stiction d2y dt2

© ABB Coprorate Research b.) Histogram (noise & filter) no stiction d2y dt2 stiction d2y dt2

© ABB Coprorate Research Level control with stiction MSE: d2yd2y dt 2 y(t) stiction

© ABB Coprorate Research Level control without stiction MSE: y(t) d2yd2y dt 2 no stiction

© ABB Coprorate Research Use Camel method also for self-regulating processes! stictionno stiction Y dy dt d2y dt2 Y Y’

© ABB Coprorate Research Flow control with stiction MSE: y(t) dy dt stiction

© ABB Coprorate Research Flow control without stiction MSE: y(t) dy dt no stiction

© ABB Coprorate Research Detect too large variance (too large 2-sigma) Is this good or bad? Basic problem: 2σ2σ -2σ

© ABB Coprorate Research Performance index Possible to calculate denominator from normal operating data given knowledge of process time delay (deadtime). Proposed by Harris (1989). Modification presented in Horch and Isaksson (1999) Introduce a control performance measure: Current variance Theoretically opt variance Ip =

© ABB Coprorate Research Before: After: Modified Index:

© ABB Coprorate Research Commercial tools / suppliers... LoopMD KCL-CoPA ABB LoopAnalyst PROTUNER™

© ABB Coprorate Research LATTS – Loop Auditing and Tuning Tool Suite Process model identification PID controller tuning Loop auditing Part of ABB Industrial IT concept and uses the new Aspect Integrator Platform (AIP). Consists of three Aspects:

© ABB Coprorate Research Process Model Identification Aspect

© ABB Coprorate Research PID Controller Tuning Aspect

© ABB Coprorate Research Auditing Aspect Computes 21 different quantities/indices. For example: Control error standard deviation Oscillation index Stiction diagnosis (correlation) Stiction diagnosis (histogram) Modified Harris index

© ABB Coprorate Research Auditing Aspect cont’d Combines these indices to test a number of hypotheses, such as Acceptable performance Possible valve problem Sluggish tuning The result is summarized in a report, either as a text file or in Internet Explorer

© ABB Coprorate Research Auditing -- Index trend plots

© ABB Coprorate Research Auditing -- Report

© ABB Coprorate Research Conclusions New ABB Product LATTS under Beta testing right now. Product release approximately June Methods exist for non-invasive Oscillation detection Stiction diagnosis Minimum variance benchmark

© ABB Coprorate Research Future work (industrial as well as academic) detection and diagnosis of mill-wide oscillations distinction of linearly and non-linearly caused oscillations performance assessment based on full process model (event-triggered estimation) application of multivariable performance index performance monitoring of MPC loops

© ABB Coprorate Research abb