000 14885nam a2201201 i 4500
001 EBC1911737
003 MiAaPQ
005 20240123070852.0
006 m o d |
007 cr cnu||||||||
008 150124s2015 nyua foab 001 0 eng d
020 _z9781606501702
_qprint
020 _a9781606501719
_q(electronic bk.)
024 7 _z10.5643/9781606501719
_2doi
035 _a(MiAaPQ)EBC1911737
035 _a(Au-PeEL)EBL1911737
035 _a(CaPaEBR)ebr11007943
035 _a(CaONFJC)MIL688128
035 _a(OCoLC)899728211
040 _aMiAaPQ
_beng
_erda
_epn
_cMiAaPQ
_dMiAaPQ
050 4 _aTS156.8
_b.M357 2015
082 0 _a629.83
_223
100 1 _aMcMillan, Gregory K.,
_d1946-,
_eauthor.
245 1 0 _aTuning and control loop performance /
_cGregory K. McMillan.
250 _aFourth edition.
264 1 _aNew York, [New York] (222 East 46th Street, New York, NY 10017) :
_bMomentum Press,
_c2015.
300 _a1 online resource (xxxiv, 546 pages) :
_billustrations.
336 _atext
_2rdacontent
337 _acomputer
_2rdamedia
338 _aonline resource
_2rdacarrier
490 1 _aManufacturing and engineering collection
504 _aIncludes bibliographical references (pages 523-527) and index.
505 0 _a1. Fundamentals -- 1.1 Introduction -- 1.1.1 Perspective -- 1.1.2 Overview -- 1.1.3 Recommendations -- 1.2 PID controller -- 1.2.1 Proportional mode -- 1.2.2 Integral mode -- 1.2.3 Derivative mode -- 1.2.4 ARW and output limits -- 1.2.5 Control action and valve action -- 1.2.6 Operating modes -- 1.3 Loop dynamics -- 1.3.1 Types of process responses -- 1.3.2 Dead times and time constants -- 1.3.3 Open loop self-regulating and integrating process gains -- 1.3.4 Deadband, resolution, and threshold sensitivity -- 1.4 Typical mode settings -- 1.5 Typical tuning methods -- 1.5.1 Lambda tuning for self-regulating processes -- 1.5.2 Lambda tuning for integrating processes -- 1.5.3 IMC tuning for self-regulating processes -- 1.5.4 IMC tuning for integrating processes -- 1.5.5 Skogestad internal model control tuning for self-regulating processes -- 1.5.6 SIMC tuning for integrating processes -- 1.5.7 Traditional open loop tuning -- 1.5.8 Modified Ziegler-Nichols reaction curve tuning -- 1.5.9 Modified Ziegler-Nichols ultimate oscillation tuning -- 1.5.10 Quarter amplitude oscillation tuning -- 1.5.11 SCM tuning for self-regulating processes -- 1.5.12 SCM tuning for integrating processes -- 1.5.13 SCM tuning for runaway processes -- 1.5.14 Maximizing absorption of variability tuning for surge tank level -- 1.6 Test results -- 1.6.1 Performance of tuning settings on dead time dominant processes -- 1.6.2 Performance of tuning settings on near-integrating processes -- 1.6.3 Performance of tuning settings on true integrating processes -- 1.6.4 Performance of tuning settings on runaway processes -- 1.6.5 Slow oscillations from low PID gain in integrating and runaway processes -- 1.6.6 Performance of tuning methods on various processes -- Key points --
505 8 _a2. Unified methodology -- 2.1 Introduction -- 2.1.1 Perspective -- 2.1.2 Overview -- 2.1.3 Recommendations -- 2.2 PID features -- 2.2.1 PID form -- 2.2.2 External reset feedback -- 2.2.3 PID structure -- 2.2.4 Split range -- 2.2.5 Signal characterization -- 2.2.6 Feedforward -- 2.2.7 Decoupling -- 2.2.8 Output tracking and remote output -- 2.2.9 Setpoint filter, lead-lag, and rate limits -- 2.2.10 Enhanced PID for wireless and analyzers -- 2.3 Automation system difficulties -- 2.3.1 Open loop gain problems -- 2.3.2 Time constant problems -- 2.3.3 Dead time problems -- 2.3.4 Limit cycle problems -- 2.3.5 Noise problems -- 2.3.6 Accuracy and precision problems -- 2.4 Process objectives -- 2.4.1 Maximize turndown -- 2.4.2 Maximize safety and environmental protection -- 2.4.3 Minimize product variability -- 2.4.4 Maximize process efficiency and capacity -- 2.5 Step-by-step solutions -- 2.6 Test results -- Key points --
505 8 _a3. Performance criteria -- 3.1 Introduction -- 3.1.1 Perspective -- 3.1.2 Overview -- 3.1.3 Recommendations -- 3.2 Disturbance response metrics -- 3.2.1 Accumulated error -- 3.2.2 Peak error -- 3.2.3 Disturbance lag -- 3.3 Setpoint response metrics -- 3.3.1 Rise time -- 3.3.2 Overshoot and undershoot -- Key points --
505 8 _a4. Effect of process dynamics -- 4.1 Introduction -- 4.1.1 Perspective -- 4.1.2 Overview -- 4.1.3 Recommendations -- 4.2 Effect of mechanical design -- 4.2.1 Equipment and piping dynamics -- 4.2.2 Common equipment and piping design mistakes -- 4.3 Estimation of total dead time -- 4.4 Estimation of open loop gain -- 4.5 Major types of process responses -- 4.5.1 Self-regulating processes -- 4.5.2 Integrating processes -- 4.5.3 Runaway processes -- 4.6 Examples -- 4.6.1 Waste treatment pH loops (self-regulating process) -- 4.6.2 Boiler feedwater flow loop (self-regulating process) -- 4.6.3 Boiler drum level loop (integrating process) -- 4.6.4 Furnace pressure loop (near-integrating process) -- 4.6.5 Exothermic reactor cascade temperature loop (runaway process) -- 4.6.6 Biological reactor biomass concentration loop (runaway process) -- Key points --
505 8 _a5. Effect of controller dynamics -- 5.1 Introduction -- 5.1.1 Perspective -- 5.1.2 Overview -- 5.1.3 Recommendations -- 5.2 Execution rate and filter time -- 5.2.1 First effect via equation for integrated error -- 5.2.2 Second effect via equations for implied dead time -- 5.3 Smart reset action -- 5.4 Diagnosis of tuning problems -- 5.5 Furnace pressure loop example (near-integrating) -- 5.6 Test results -- Key points --
505 8 _a6. Effect of measurement dynamics -- 6.1 Introduction -- 6.1.1 Perspective -- 6.1.2 Overview -- 6.1.3 Recommendations -- 6.2 Wireless update rate and transmitter damping -- 6.2.1 First effect via equation for integrated error -- 6.2.2 Second effect via equations for implied dead time -- 6.3 Analyzers -- 6.4 Sensor lags and delays -- 6.5 Noise and repeatability -- 6.6 Threshold sensitivity and resolution limits -- 6.7 Rangeability (turndown) -- 6.8 Runaway processes -- 6.9 Accuracy, precision, and drift -- 6.10 Attenuation and deception -- 6.11 Examples -- 6.11.1 Waste treatment pH loop (self-regulating process) -- 6.11.2 Boiler feedwater flow loop (self-regulating process) -- 6.11.3 Boiler drum level loop (integrating process) -- 6.11.4 Furnace pressure loop (near-integrating process) -- 6.11.5 Exothermic reactor cascade temperature loop (runaway process) -- 6.11.6 Biological reactor biomass concentration loop (runaway process) -- 6.12 Test results -- Key points --
505 8 _a7. Effect of valve and variable frequency drive dynamics -- 7.1 Introduction -- 7.1.1 Perspective -- 7.1.2 Overview -- 7.1.3 Recommendations -- 7.2 Valve positioners and accessories -- 7.2.1 Pneumatic positioners -- 7.2.2 Digital positioners -- 7.2.3 Current to pneumatic (I/P) transducers -- 7.2.4 Solenoid valves -- 7.2.5 Volume boosters -- 7.3 Actuators, shafts, and stems -- 7.3.1 Diaphragm actuators -- 7.3.2 Piston actuators -- 7.3.3 Linkages and connections -- 7.4 VFD system design -- 7.4.1 Pulse width modulation -- 7.4.2 Cable problems -- 7.4.3 Bearing problems -- 7.4.4 Speed slip -- 7.4.5 Motor requirements -- 7.4.6 Drive controls -- 7.5 Dynamic response -- 7.5.1 Control valve response -- 7.5.2 VFD response -- 7.5.3 Dead time approximation -- 7.5.4 Deadband and resolution -- 7.5.5 When is a valve or VFD too slow? -- 7.5.6 Limit cycles -- 7.6 Installed flow characteristics and rangeability -- 7.6.1 Valve flow characteristics -- 7.6.2 Valve rangeability -- 7.6.3 VFD flow characteristics -- 7.6.4 VFD rangeability -- 7.7 Best practices -- 7.7.1 Control valve design specifications -- 7.7.2 VFD design specifications -- 7.8 Test results -- Key points --
505 8 _a8. Effect of disturbances -- 8.1 Introduction -- 8.1.1 Perspective -- 8.1.2 Overview -- 8.1.3 Recommendations -- 8.2 Disturbance dynamics -- 8.2.1 Load time constants -- 8.2.2 Load rate limit -- 8.2.3 Disturbance dead time -- 8.2.4 Disturbance oscillations -- 8.3 Disturbance location -- 8.4 Disturbance troubleshooting -- 8.4.1 Sources of fast oscillations -- 8.4.2 Sources of slow oscillations -- 8.5 Disturbance mitigation -- 8.6 Test results -- Key points --
505 8 _a9. Effect of nonlinearities -- 9.1 Introduction -- 9.1.1 Perspective -- 9.1.2 Overview -- 9.1.3 Recommendations -- 9.2 Variable gain -- 9.2.1 Cascade control -- 9.2.2 Reversals of process sign -- 9.2.3 Signal characterization -- 9.2.4 Gain scheduling -- 9.2.5 Adaptive control -- 9.2.6 Gain margin -- 9.3 Variable dead time -- 9.4 Variable time constant -- 9.5 Inverse response -- 9.6 Test results -- Key points --
505 8 _a10. Effect of interactions -- 10.1 Introduction -- 10.1.1 Perspective -- 10.1.2 Overview -- 10.1.3 Recommendations -- 10.2 Pairing -- 10.2.1 Relative gain array -- 10.2.2 Distillation column example -- 10.2.3 Static mixer example -- 10.2.4 Hidden control loops -- 10.2.5 Relative gains less than zero -- 10.2.6 Relative gains from zero to one -- 10.2.7 Relative gains greater than one -- 10.2.8 Model predictive control -- 10.3 Decoupling -- 10.4 Directional move suppression -- 10.5 Tuning -- 10.6 Test results -- Key points --
505 8 _a11. Cascade control -- 11.1 Introduction -- 11.1.1 Perspective -- 11.1.2 Overview -- 11.1.3 Recommendations -- 11.2 Configuration and tuning -- 11.3 Process control benefits -- 11.4 Process knowledge benefits -- 11.5 Watch-outs -- 11.6 Test results -- Key points --
505 8 _a12. Advanced regulatory control -- 12.1 Introduction -- 12.1.1 Perspective -- 12.1.2 Overview -- 12.1.3 Recommendations -- 12.2 Feedforward control -- 12.2.1 Opportunities -- 12.2.2 Watch-outs -- 12.3 Intelligent output action -- 12.3.1 Opportunities -- 12.3.2 Watch-outs -- 12.4 Intelligent integral action -- 12.4.1 Opportunities -- 12.4.2 Watch-outs -- 12.5 Dead time compensation -- 12.5.1 Opportunities -- 12.5.2 Watch-outs -- 12.6 Valve position control -- 12.6.1 Opportunities -- 12.6.2 Watch-outs -- 12.7 Override control -- 12.7.1 Opportunities -- 12.7.2 Watch-outs -- 12.8 Test results -- Key points --
505 8 _a13. Process control improvement -- 13.1 Introduction -- 13.1.1 Perspective -- 13.1.2 Overview -- 13.1.3 Recommendations -- 13.2 Unit operation metrics -- 13.3 Opportunities -- 13.3.1 Variability -- 13.3.2 Increasing capacity and efficiency -- 13.3.3 Effective use of models -- 13.3.4 Sizing and assessment -- 13.4 Key questions -- Key points --
505 8 _a14. Auto tuners and adaptive control -- 14.1 Introduction -- 14.1.1 Perspective -- 14.1.2 Overview -- 14.1.3 Recommendations -- 14.2 Methodology -- Key points --
505 8 _a15. Batch optimization -- 15.1 Introduction -- 15.1.1 Perspective -- 15.1.2 Overview -- 15.1.3 Recommendations -- 15.2 Cycle time -- 15.3 Profile -- 15.4 End point -- Key points --
505 8 _aAppendix A. Automation system performance top 10 concepts -- Appendix B. Basics of PID controllers -- Appendix C. Controller performance -- Appendix D. Discussion -- Appendix E. Enhanced PID for wireless and analyzer applications -- Appendix F. First principle process relationships -- Appendix G. Gas pressure dynamics -- Appendix H. Convective heat transfer coefficients -- Appendix I. Interactive to noninteractive time constant conversion -- Appendix. Jacket and coil temperature control -- Appendix K. PID forms and conversion of tuning settings -- Appendix L. Liquid mixing dynamics -- Appendix M. Measurement speed requirements for SIS -- References -- Bibliography -- About the author -- Index.
506 _aRestricted to libraries which purchase an unrestricted PDF download via an IP.
520 3 _aThe proportional-integral-derivative (PID) controller is the heart of every control system in the process industry. Given the proper setup and tuning, the PID has proven to have the capability and flexibility needed to meet nearly all of industry's basic control requirements. However, the information to support the best use of these features has fallen behind the progress of improved functionality. Additionally, there is considerable disagreement on the tuning rules that largely stems from a misunderstanding of how tuning rules have evolved and the lack of recognition of the effect of automation system dynamics and the incredible spectrum of process responses, disturbances, and performance objectives. This book provides the knowledge to eliminate the misunderstandings, realize the difference between theoretical and industrial application of PID control, address practical difficulties, improve field automation system design, use the latest PID features, and ultimately get the best tuning settings that enables the PID to achieve its full potential.
588 _aTitle from PDF title page (viewed on January 24, 2015).
590 _aElectronic reproduction. Ann Arbor, MI : ProQuest, 2015. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.
650 0 _aProcess control.
650 0 _aFeedback control systems.
653 _aadaptive control
653 _aadvanced regulatory control
653 _aanalyzer response
653 _aauto tuner
653 _aautomation system
653 _abatch optimization
653 _abioreactor control
653 _acascade control
653 _acompressor control
653 _acontrol loop performance
653 _acontrol valve response
653 _aexternal reset feedback
653 _afeedforward control
653 _ainverse response
653 _alambda tuning
653 _alevel control
653 _ameasurement response
653 _apH control
653 _aPID control
653 _aPID execution rate
653 _aPID filter
653 _aPID form
653 _aPID structure
653 _aPID tuning
653 _apressure control
653 _aprocess control
653 _aprocess disturbances
653 _aprocess dynamics
653 _aprocess interaction
653 _aprocess metrics
653 _aprocess nonlinearity
653 _aprocess performance
653 _aprocess response
653 _aproportional-integral-derivative controller
653 _areactor control
653 _arunaway reaction
653 _atemperature control
653 _avalve deadband
653 _avalve position control
653 _avalve resolution
653 _avariable frequency drive response
653 _awireless control
653 _awireless response
655 4 _aElectronic books.
776 0 8 _iPrint version:
_z9781606501702
797 2 _aProQuest (Firm)
830 0 _aManufacturing and engineering collection.
856 4 0 _uhttps://ebookcentral.proquest.com/lib/bacm-ebooks/detail.action?docID=1911737
_zClick to View
999 _c123438
_d123438