Abstract
This chapter gives a brief introduction to the objectives, principle, tasks, and challenges of control performance management (CPM). A basic procedure for CPM, assessment benchmarks, are given. The key dates of the development of CPM technology and a literature survey are described.
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References
Ahsan Q, Grosvenor RI, Prickett PW (2004) Distributed control loop performance monitoring architecture. In: Proc control 2004, University of Bath, UK, ID-054
Åkesson IN (2003) Plant loop auditing in practice. In: VDI-Berichte 1756, Proc GMA-Kongress: Automation und Information in Wirtschaft und Gesellschaft. Baden-Baden, Germany, pp 927–934
Åström KJ (1979) Introduction to stochastic control. Academic Press, San Diego
Åström KJ (1991) Assessment of achievable performance of simple feedback loops. Int J Adapt Control Signal Process 5:3–19
Bezergianni S, Georgakis C (2003) Evaluation of controller performance-use of models derived by subspace identification. Int J Adapt Control Signal Process 17:527–552
Bialkowski WL (1993) Dreams vs. reality: a view from both sides of the gap. Pulp & Paper Canada 94:19–27
Box GEP, Jenkins GM (1970) Time series analysis: forcasting and control. Holden-Day, Oakland
Brisk ML (2004) Process control: potential benefits and wasted opportunities. In: Proc Asian control confer, Melbourne, Australia, pp 10–16
Choudhury MAAS, Kariwala V, Shah SL, Douke H, Takada H, Thornhill NF (2005a) A simple test to confirm control valve stiction. In: Proc IFAC world congress, Praha
Choudhury MAAS, Thornhill NF, Shah SL, Shook DS (2006a) Automatic detection and quantification of stiction in control valves. Control Eng Pract 14:1395–1412
Choudhury MAAS, Shook D, Shah SL (2006b) Linear or nonlinear? A bicoherence based metric of nonlinearity measure. In: Proc IFAC symposium SAFEPROCESS, Beijing, China
Choudhury MAAS, Shah SL, Thornhill NF (2008) Diagnosis of process nonlinearities and valve stiction—data driven approaches. Springer, London
Desborough L, Harris T (1992) Performance assessment measures for univariate feedback control. Can J Chem Eng 70:1186–1197
Desborough L, Harris T (1993) Performance assessment measures for univariate feedforward/ feedback control. Can J Chem Eng 71:605–616
Desborough L, Miller R (2002) Increasing customer value of industrial control performance monitoring—Honeywell’s experience. AIChE Symp Ser 98(326):153–186
DeVries W, Wu S (1978) Evaluation of process control effectiveness and diagnosis of variation in paper basis weight via multivariate time-series analysis. IEEE Trans Autom Control 23:702–708
Dittmar R, Bebar M, Reinig G (2003) Control Loop Performance Monitoring: Motivation, Methoden, Anwendungswünsche. Automtech Prax 45:94–103
Ender D (1993) Process control performance: not as good as you think. Control Eng 40:180–190
Eriksson P, Isaksson AJ (1994) Some aspects of control loop performance monitoring. In: Proc IEEE confer control applications, Glasgow, Scotland, pp 1029–1034
Ettaleb L (1999) Control loop performance assessment and oscillation detection. PhD thesis, University of British, Columbia, Canada
Farenzena M, Trierweiler JO (2006) Variability matrix: a new tool to improve the plant performance. In: Proc IFAC ADCHEM, Gramado, Brazil, pp 893–898
Forsman K, Stattin A (1999) A new criterion for detecting oscillations in control loops. In: Proc Europ control confer, Karlsruhe, Germany
Gao J, Patwardhan RS, Akamatsu K, Hashimoto Y, Emoto G, Shah SL, Huang B (2003) Performance evaluation of two industrial MPC controllers. Control Eng Pract 11:1371–1387
Grimble MJ (2002b) Restricted structure controller tuning and performance assessment. IEE Proc Part D, Control Theory Appl 149:8–16
Grimble MJ (2003) Restricted structure control loop performance assessment for PID controllers and state-space systems. Asian J Control 5:39–57
Grimble MJ, Uduehi D (2001) Process control loop benchmarking and revenue optimization. In: Proc Amer control confer, Arlington, USA
Hägglund T (1995) A control-loop performance monitor. Control Eng Pract 3:1543–1551
Harris TJ (1989) Assessment of closed loop performance. Can J Chem Eng 67:856–861
Harris T, Seppala CT (2001) Recent developments in performance monitoring and assessment techniques. In: Proc chemical process control confer, Tuscon, USA
Harris T, Seppala CT, Desborough LD (1999) A review of performance monitoring and assessment techniques for univariate and multivariate control systems. J Process Control 9:1–17
Harris T, Boudreau F, MacGregor JF (1996a) Performance assessment using of multivariable feedback controllers. Automatica 32:1505–1518
Harris T, Seppala CT, Jofriet PJ, Surgenor BW (1996b) Plant-wide feedback control performance assessment using an expert-system framework. Control Eng Pract 4:1297–1303
He QP, Wang J, Pottmannn M, Qin SJ (2007) A curve fitting method for detecting valve stiction in oscillating control loops. Ind Eng Chem Res 46:4549–4560
Horch A (1999) A simple method for detection of stiction in control valves. Control Eng Pract 7:1221–1231
Horch A (2000) Condition monitoring of control loops. PhD thesis, Royal Institute of Technology, Stockholm, Sweden
Horch A, Isaksson AJ (1999) A modified index for control performance assessment. J Process Control 9:475–483
Horton EC, Foley MW, Kwok KE (2003) Performance assessment of level controllers. Int J Adapt Control Signal Process 17:663–684
Huang B (2002) Minimum variance control and performance assessment of time variant processes. J Process Control 12:707–719
Huang B (2003) A pragmatic approach towards assessment of control loop performance. Int J Adapt Control Signal Process 17:489–608
Huang B, Shah SL (1998) Practical issues in multivariable feedback control performance assessment. J Process Control 8:421–430
Huang B, Shah SL, Kwok EK (1997a) Good, bad or optimal? Performance assessment of multivariable processes. Automatica 33:1175–1183
Huang B, Shah SL, Kwok EK, Zurcher J (1997b) Performance assessment of multivariate control loops on a paper-machine headbox. Can J Chem Eng 75:134–142
Huang B, Shah SL, Fujii H (1997c) The unitary interactor matrix and its estimation from closed-loop data. J Process Control 7:195–207
Huang B, Shah SL, Badmus L, Vishnubhotla A (1999) Control performance assessment: an enterprise asset management solution. www.matrikon.com/download/products/lit/processdoctor_pa_eam.pdf
Huang B, Shah SL, Miller R (2000) Feedforward plus feedback controller performance assessment of MIMO systems. IEEE Trans Control Syst Technol 8:580–587
Huang B, Ding SX, Qin J (2005a) Closed-loop subspace identification: an orthogonal projection approach. J Process Control 15:53–66
Huang B, Ding SX, Thornhill N (2005b) Practical solutions to multivariable feedback control performance assessment problem: reduced a priori knowledge of interactor matrices. J Process Control 15:573–583
Hugo AJ (1999) Process controller performance monitoring and assessment. www.controlartsinc.com/Support/Articles/PerformanceAssessment.PDF
Jelali M (2006c) An overview of control performance assessment technology and industrial applications. Control Eng Pract 14:441–466
Jelali M (2008) Estimation of valve stiction in control loops using separable least-squares and global search algorithms. J Process Control 18:632–642
Jelali M, Huang B (eds) (2010) Detection and diagnosis of stiction in control loops: state of the art and advanced methods. Springer, Berlin
Jofriet P, Seppala C, Harvey M, Surgenor B, Harris T (1995) An expert system for control loop performance analysis. In: Proc annual meeting, technical section, Canadian pulp and paper association, pp B41–B49
Julien RH, Foley MW, Cluett WR (2004) Performance assessment using a model predictive control benchmark. J Process Control 14:441–456
Kano M, Maruta H, Kugemoto H, Shimizu K (2004) Practical model and detection algorithm for valve stiction. In: Proc IFAC symp DYCOPS, Boston, USA
Ko B-S, Edgar TF (1998) Assessment of achievable PI control performance for linear processes with dead time. In: Proc Amer control confer, Philadelphia, USA
Ko B-S, Edgar TF (2001a) Performance assessment of constrained model predictive control systems. AIChE J 47:1363–1371
Ko B-S, Edgar TF (2001b) Performance assessment of multivariable feedback control systems. Automatica 37:899–905
Ko B-S, Edgar TF (2004) PID control performance assessment: the single-loop case. AIChE J 50:1211–1218
Kozub DJ (2002) Controller performance monitoring and diagnosis. Industrial perspective. In: Proc IFAC world congress, Barcelona, Spain
Kozub DJ, Garcia C (1993) Monitoring and diagnosis of automated controllers in the chemical process industries. In: Proc AIChE, St Louis, USA
Lynch C, Dumont GA (1996) Control loop performance monitoring. IEEE Trans Control Syst Technol 18:151–192
Majecki P, Grimble MJ (2004a) Controller performance design and assessment using nonlinear generalized minimum variance benchmark: scalar case. In: Proc control 2004, University of Bath, UK, ID-232
Majecki P, Grimble MJ (2004b) GMV and restricted-structure GMV controller performance assessment—multivariable case. In: Proc Amer control confer, Boston, USA, vol 1, pp 697–702
McNabb CA, Qin SJ (2003) Projection based MIMO control performance monitoring: I—covariance monitoring in state space. J Process Control 13:739–757
Miao T, Seborg DE (1999) Automatic detection of excessively oscillatory feedback control loops. In: Proc IEEE confer control applications. Kohala Coast-Island, USA
Olaleye F, Huang B, Tamayo E (2004a) Performance assessment of control loops with time varying disturbance dynamics. J Process Control 14:867–877
Olaleye F, Huang B, Tamayo E (2004b) Feedforward and feedback controller performance assessment of linear time-variant processes. Ind Eng Chem Res 43:589–596
Ordys AW, Uduehi D, Johnson MA (eds) (2007) Process control performance assessment: from theory to implementation. Springer, Berlin
Patwardhan RS (1999) Studies in synthesis and analysis of model predictive controllers. PhD thesis, University of Alberta, Canada
Patwardhan RS, Shah S, Emoto G, Fujii H (1998) Performance analysis of model-based predictive controllers: an industrial study. In: Proc AIChE, Miami, USA
Paulonis MA, Cox JW (2003) A practical approach for large-scale controller performance assessment, diagnosis, and improvement. J Process Control 13:155–168
Qin SJ (1998) Control performance monitoring—a review and assessment. Comput Chem Eng 23:173–186
Rakar A, Zorzut S, Jovan V (2004) Assessment of production performance by means of KPI. In: Proc control 2004, University of Bath, UK, ID-073
Ruel M (2002) Learn how to assess and improve control loop performance. In: Proc ISA, Chicago, USA
Ruel M (2003) The conductor directs this orchestra. Intech, November:20–22
Schäfer J, Çinar A (2002) Multivariable MPC performance assessment, monitoring and diagnosis. In: Proc IFAC world congress, Barcelona, Spain
Seborg DE, Edgar TF, Mellichamp DA (2004) Process dynamics and control. Wiley, New York
Shah SL, Patwardhan R, Huang B (2001) Multivariate controller performance analysis: methods, applications and challenges. In: Proc chemical process control confer, Tucson, USA, pp 187–219
Shinskey FG (1990) How good are our controllers in absolute performance and robustness? Meas Control 23:114–121
Shinskey FG (1996) Process-control systems: application, design, and tuning. McGraw Hill, New York
Shunta JP (1995) Achieving world class manufacturing through process control. Prentice Hall, New York
Singhal A, Salsbury TI (2005) A simple method for detecting valve stiction in oscillating control loops. J Process Control 15:371–382
Spencer MA, Elliot RM (1997/1998) Improving instrumentation and control systems performance. Pet Technol Q Winter:93–97
Stanfelj N, Marlin TE, MacGregor JF (1993) Monitoring and diagnosis of process control performance: the single-loop case. Ind Eng Chem Res 67:856–861
Swanda A, Seborg DE (1997) Evaluating the performance of PID-type feedback control loops using normalized settling time. In: Proc IFAC ADCHEM, Banff, Canada, pp 301–306
Swanda A, Seborg DE (1999) Controller performance assessment based on setpoint response data. In: Proc Amer control confer, San Diego, USA, pp 3863–3867
Thornhill NF, Hägglund T (1997) Detection and diagnosis of oscillation in control loops. Control Eng Pract 5:1343–1354
Thornhill NF, Horch A (2007) Advances and new directions in plant-wide disturbance detection and diagnosis. Control Eng Pract 15:1196–1206
Thornhill NF, Oettinger M, Fedenczuk MS (1999) Refinery-wide control loop performance assessment. J Process Control 9:109–124
Thornhill NF, Shah SL, Huang B (2001) Detection of distributed oscillations and root-cause diagnosis. In: Proc CHEMFAS, Chejudo Island, Korea, pp 167–172
Thornhill NF, Cox J, Paulonis M (2003a) Diagnosis of plant-wide oscillation through data-driven analysis and process understanding. Control Eng Pract 11:1481–1490
Thornhill NF, Huang B, Shah SL (2003b) Controller performance assessment in set point tracking and regulatory control. Int J Adapt Control Signal Process 17:709–727
Thornhill NF, Huang B, Zhang H (2003c) Detection of multiple oscillations in control loops. J Process Control 13:91–100
Torres BS, de Carvalho FB de Oliveira Fonseca M, Filho CS (2006) Performance assessment of control loops—cases studies. In: Proc IFAC ADCHEM, Gramado, Brasil
Tyler M, Morari M (1995) Performance assessment for unstable and nonminimum-phase systems. In: Preprints IFAC workshop on-line fault detection supervision chemical process industries, Newcastle upon Tyne, UK
Tyler M, Morari M (1996) Performance monitoring of control systems using likelihood methods. Automatica 32:1145–1162
Xia C, Howell J (2003) Loop status monitoring and fault localization. J Process Control 13:679–691
Xia H, Majecki P, Ordys A, Grimble MJ (2003) Controller benchmarking based on economic benefits. In: Proc Europ control confer, Cambridge, UK, pp 2393–2398
Xia H, Majecki P, Ordys A, Grimble MJ (2006) Performance assessment of MIMO systems based on I/O delay information. J Process Control 16:373–383
Xu F, Huang B, Tamayo EC (2006a) Assessment of economic performance of model predictive control through variance/constraint tuning. In: Proc IFAC ADCHEM, Gramado, Brazil, pp 899–904
Xu F, Lee K-H, Huang B (2006b) Monitoring control performance via structured closed-loop response subject to output variance/covariance upper bound. J Process Control 16:971–984
Yamashita Y (2006) An automatic method for detection of valve stiction in process control loops. Control Eng Pract 14:503–510
Zhang Y, Henson MA (1999) A performance measure for constrained model predictive controllers. In: Proc Europ control confer, Karlsruhe, Germany
Ziegler JG, Nichols NB (1943) Process lags in automatic control circuits. Trans Am Soc Mech Eng 65:433–444
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Jelali, M. (2013). Introduction. In: Control Performance Management in Industrial Automation. Advances in Industrial Control. Springer, London. https://doi.org/10.1007/978-1-4471-4546-2_1
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