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4992c032 控晶四甲 葉仁富

PID Control System Analysis, Design,and Technolog. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, VOL. 13, NO. 4, JULY 2005. 4992c032 控晶四甲 葉仁富. REFERENCES. [1] ABB, Instruction Manual of MICRO-DC 53SL6000, 2001. [2] , Specification DataFile of Commander 355, 2001.

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4992c032 控晶四甲 葉仁富

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  1. PID Control System Analysis, Design,andTechnolog IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, VOL. 13, NO. 4, JULY 2005 4992c032 控晶四甲 葉仁富

  2. REFERENCES • [1] ABB, Instruction Manual of MICRO-DC 53SL6000, 2001. • [2] , Specification DataFile of Commander 355, 2001. • [3] K. J.Åström, T.Hägglund, C. C. Hang, andW. K. Ho, “Automatic tuningand adaptation for PID controllers—a survey,”Control Eng. Pract., vol.1, no. 4, pp. 699–714, 1993. • [4] K. J. Åström and T. Hägglund, PID Controllers: Theory, Design, andTuning. Research Triangle Park, NC: Instrument Soc. Amer., 1995. • [5] , “PID Control,” in The Control Handbook, W. S. Levine,Ed. Piscataway, NJ: IEEE Press, 1996, pp. 198–209. • [6] , Benchmark Systems for PID Control, pp. 165–166, 2000. • [7] , “The future of PID control,” Control Eng. Pract., vol. 9, no. 11,pp. 1163–1175, 2001. • [8] C. Bohn and D. P. Atherton, “An analysis package comparing PID antiwindupstrategies,” IEEE Control Syst. Mag., vol. 15, no. 2, pp. 34–40,Apr. 1995. • [9] R. Cao and T. McAvoy, “Evaluation of a pattern recognition adaptivePID controller,” Automatica, vol. 26, no. 4, pp. 797–801, Jul. 1990. • [10] G. Chong and Y. Li, “Trajectory controller network and its designautomation through evolutionary computing,” in Proc. EvoWorkshops2000: Real-World Applications of Evolutionary Computing, Edinburgh,U.K., Apr., pp. 139–146. • [11] (1998, May) Control Engineering—Single-Loop Controllers DominateMarketplace. [Online] http://www.manufacturing.net/ctl/article/CA189 397 • [12] (2004, Jun.) B1—esp@cenet—Your Gateway to Patents. [Online]http://gb.espacenet.com

  3. [13] W. Feng and Y. Li, “Performance indexes in evolutionary CACSD automationwith application to batch PID generation,” in Proc. 10th IEEEInt. Symp. Computer Aided Control System, Hawaii, Aug. 1999, pp.486–491. • [14] Foxboro, Product Specifications of I/A Series 716C 1/16 DIN TemperatureController, 1996. • [15] , Technical Information of EXACT TuningWith 762, 760, and 740 Series Controllers, Aug. 1995. • [16] J. P. Gerry, “A comparison of PID control algorithms,” Control Eng.,vol. 34, no. 3, pp. 102–105, Mar. 1987. • [17] J. P. Gerry and F. G. Shinskey. (2004, May) PID Controller Specification(White Paper). [Online] http://www.expertune.com/PIDspec.htm • [18] R. Gorez, “A survey of PID auto-tuning methods,” J. A, vol. 38, no. 1,pp. 3–10, 1997 • [19] T. Hägglund and K. J. Åström, “Industrial adaptive controllers based onfrequency response techniques,” Automatica, vol. 27, no. 4, pp. 599–609, • Jul. 1991. • [20] C. C. Hang and K. K. Sin, “A comparative performance study of PIDauto-tuners,” IEEE Control Syst. Mag., vol. 11, no. 5, pp. 41–47, Aug.1991. • [21] “Getting the best out of PID in machine control,” in Proc. Dig. Inst.Elect. Eng. PG16 Colloquium (96/287), London, U.K., Oct. 24, 1996. • [22] A. Kaya and T. J. Scheib, “Tuning of PID controls of different structures,”Control Eng., vol. 35, no. 7, pp. 62–65, Jul. 1988. • [23] Y. Li,W. Feng, K. C. Tan, X. K. Zhu, X. Guan, and K. H. Ang, “PIDeasyand automated generation of optimal PID controllers,” in Proc. 3rd Asia-Pacific Conf. Control and Measurement, Dunhuang, P.R. China, 1998,pp. 29–33. • [24] P. Marsh, “Turn on, tune in,” New Electron., vol. 31, no. 4, pp. 31–32,1998. • [25] B. J. Minter and D. G. Fisher, “A comparison of adaptive controllers:academicvs industrial,” in Proc. Amer. Control Conf., Atlanta, GA,1988, pp. 1653–1658.

  4. [26] A. O’Dwyer, Handbook of PI and PID Controller TuningRules. London, U.K.: Imperial College Press, 2003. • [27] OPC Foundation. (2002, June) The OPC Foundation—Dedicated to Interoperabilityin Automation. [Online] http://www.opcfoundation.org • [28] “Digital control: past, present and future of PID control,” in Proc. IFACWorkshop, J. Quevedo and T. Escobet, Eds., Terrassa, Spain, Apr. 5–7,2000. • [29] F. G. Shinskey, Feedback Controllers for the Process Industries. NewYork: McGraw-Hill, 1994. • [30] (2004, Jun.) Patents—Patent Full-Text and Full-Page Image Databases.[Online] http://ww.uspto.gov/patft • [31] H. J. Versteeg, H. J. Jansma, and K. Turner, “Evaluation of commerciallyavailable adaptive controllers,” J. A, vol. 27, no. 3, pp. 120–126, 1986. • [32] L. Wang, T. J. D. Barnes, and W. R. Cluett, “New frequency-domaindesign method for PID controllers,” Proc. Inst. Elect. Eng. D—ControlTheory Appl., vol. 142, no. 4, pp. 265–271, 1995. • [33] C. Wilson and C. Callen. (2004, Jan.) Close Process Control TranslatesTo Quality Heat Treated Parts. [Online] http://www.industrialheating.com/CDA/ArticleInformation/coverstory/BNPCoverStoryItem/ • 0,2830,116383,00.html • [34] J. G. Ziegler and N. B. Nichols, “Optimum settings for automatic controllers,” • Trans. ASME, vol. 64, pp. 759–768, 1942.

  5. INTRODUCTION • WITH its three-term functionality covering treatment to both transient and steady-state responses, proportional- integral-derivative (PID) control offers the simplest and yet most efficient solution to many real-world control problems. Sinceinvention of PID control in 1910 (largely owning toElmer Sperry’s ship autopilot), and the Ziegler–Nichols’ (Z-N)straightforward tuning methods in 1942 [34], the popularityof PID control has grown tremendously. With advances indigital technology, the science of automatic control now offersa wide spectrum of choices for control schemes. However,more than 90% of industrial controllers are still implementedbased around PID algorithms, particularly at lowest levels [5],as no other controllers match the simplicity, clear functionality,applicability, and ease of use offered by the PID controller[32]. Its wide application has stimulated and sustained thedevelopment of various PID tuning techniques, sophisticatedsoftware packages, and hardware modules.

  6. The success and longevity of PID controllers were characterized in a recent IFAC workshop, where over 90 papers dedicated to PID research were presented [28].With much of academic research in this area maturing and entering the region of “diminishing returns,” the trend in present research and development (R&D) of PID technology appears to be focused on the integrationof available methods in the form of software so as to get the best out of PID control [21]. A number of software-based techniques have also been realized in hardware modules to perform “on-demand tuning,” while the search still goes on to find the next key technology for PID tuning [24].

  7. A. Three-Term Functionality and the Parallel Structure • A PID controller may be considered as an extreme form ofa phase lead-lag compensator with one pole at the origin andthe other at infinity. Similarly, its cousins, the PI and the PDcontrollers, can also be regarded as extreme forms of phase-lagand phase-lead compensators, respectively. A standard PIDcontroller is also known as the “three-term” controller, whosetransfer function is generally written in the “parallel form”given by (1) or the “ideal form” given by (2)

  8. B. Series Structure • A PID controller may also be realized in the “series form” if both zeros are real, i.e., if . In this case, (2) canbe implemented as a cascade of a PD and a PI controller in theform [23]

  9. C. Effect of the Integral Term on Stability Refer to (2) or (3) for and 0. It can be seen that,adding an integral term to a pure proportional term will increasethe gain by a factor of and will increase the phase-lag at the same time since • Hence, both stability gain margin (GM) and phase margin (PM)will be reduced, i.e., the closed-loop system will become moreoscillatory or potentially unstable.

  10. D. Integrator Windup and Remedies • If an actuator that realizes the control action has an effectiverange limit, then the integrator may saturate and future correctionwill be ignored until the saturation is offset. This causeslow-frequency oscillations and may lead to instability. A usualmeasure taken to counteract this effect is “anti-windup” [4], [8],[29]. This is realized by inner negative feedback of some excessamount of the integral action to the integrator such that

  11. E. Effect of the Derivative Term on Stability • Generally, derivative action is valuable as it provides usefulphase lead to offset phase lag caused by integration. It is alsoparticularly helpful in shortening the period of the loop andthereby hastening its recovery from disturbances. It can havea more dramatic effect on the behavior of second-order plantsthat have no significant dead-time than first-order plants [29]. • However, the derivative term is often misunderstood and misused.For example, it has been widely perceived in the controlommunity that adding a derivative term will improve stability.It will be shown here that this perception is not always valid.In general, adding a derivative term to a pure proportional termwill reduce phase lags by

  12. F. Remedies on Singular Derivative Action • A pure differentiator is not “casual.” It does not restricthigh-frequency gains, as shown in (9) and demonstrated inFig. 2. Hence, it will results in a theoretically infinite highcontrol signal when a step change of the reference or disturbanceoccurs. To combat this, most PID software packagesand hardware modules perform some forms of filtering on thedifferentiator.

  13. G. Tuning Objectives and Existing Methods • Preselection of a controller structure can pose a challenge inapplying PID control. As vendors often recommend their owndesigns of controller structures, their tuning rules for a specificcontroller structure does not necessarily perform well with otherstructures. One solution seen is to provide support for individualstructures in software. Readers may refer to [16] and [22] for detaileddiscussions on the use of various PID structures. Nonetheless,controller parameters are tuned such that the closed-loopcontrol system would be stable and would meet given objectivesassociated with the following:

  14. H. PIDeasy—A Software-Based Approach • During the past decade, the Intelligent Systems researchgroup at University of Glasgow has attempted to solve the PIDdesign problem systematically, using modern computationalintelligence technology. As a result, a design solution has beenobtained in the form of software, PIDeasy [23]. For simplicityand reliability in PID applications, effort is made to maintainthe controller structure in the “standard form,” while allowingoptimal augmentation with simple and effective differentiatorfiltering and integrator anti-windup. High-performance particularlythat of transient response is offered through setting thecontroller parameters optimally in a fraction of a millisecond,as soon as changes in process dynamics are detected. The optimalityis multiobjective and is achieved by addressing existingproblems at the roots using modern computational intelligencetechniques.

  15. PID PATENTS • A. Patents Filed • This section focused on the currently patented tuningmethods that are often adopted in industry for PID design toolsand hardware modules. A range of patents on PID tuning arebeing studied and analyzed, which are chronologically listed inTable III. There are 64 such patents filed in the United States(US), 11 in Japan (JP), 2 in Korea (KR) and 2 by the World Intellectual Property Organization (WO). Note that a Koreanpatent (KR 9 407 530) is not included in the following analysisas it is not available in English. Readers may refer to [12] and[30] for detailed information on each patent.

  16. B. Identification Methods for Tuning • Most of the tuning methods patented rely on an identificationof plant dynamics, using an excitation (E) or nonexcitation (NE)type of method. The excitation type can be broken down furtherinto time- or frequency-domain method. Excitation is often used during plant set-up and commissioningin order to set initial PID parameters. Time-domainexcitations are usually a step or pseudorandom binary sequence(PRBS) applied in an open-loop fashion. This is a classicaland the most widely practised method. It is often adopted formodel-based tuning methods. Frequency-domain excitationsusually use a relay-like method, where the plant will undergoa controlled self-oscillation. This type of identification doesnot normally require a parametric model in tuning a PID controller,which is the main advantage over time-domain basedidentification.

  17. C. Tuning Methods Patented • Most of the identification and tuning methods patented areprocess engineering oriented and appear rather ad hoc. Shownin Table III, patented tuning methods are mostly formula-based(F), rule-based (R), and optimization-based (O). Formula-basedmethods first identified the characteristics of the plant and thenperform a mapping (similar to the Z-N formula). These areoften used in on-demand tuning for responsiveness. Rule-basedmethods are often used in adaptive control, but can be quitecomplex and ad hoc. These can be expert systems, includingsimple heuristics and fuzzy logic rules. Optimization-basedmethods are often applied offline or on very slow processes,using a conventional (such as least mean squares) or an unconventional(such as genetic algorithms [13]) search method.

  18. PID SOFTWARE PACKAGES • A. Software Packages • Due to the lack of a simple and widely applicable tuningmethod, a need for the development of easy to use PID tuningsoftware has therefore arisen. This allows a practitioner withsome control knowledge or plant information to be able to tune aPID controller efficiently and optimally for various applications.It is hoped that such software tools will increase the practising

  19. B. Tuning Methods Adopted • Within the “Analytical Methods” group in Table IV, it isseen from the “Remarks” column that the IMC or lambdatuning method is the most widely adopted tuning method incommercial software packages. Almost all these packagesrequire a time-domain model before the controller can be set.The adopted model is the one given by (10). The pIDtunemethod by EngineSoft is the only one that uses an AX (AutoRegressive with eXternal input) model instead of the modelgiven by (10). On design, “Type C” (or I-PD) structure isstrongly recommended in BESTune [40]. Note that ExperTuneis embedded in RSTune and Tune-a-Fish. It is almost impossible to name a software package to be thebest as there is no generic method to set the PID controller optimallyto satisfy all design criteria and needs. However, mostof the software packages studied in Table IV provide a tuneableparameter set for the user to determine an overall performancethat is best suited to an ad hoc application.

  20. C. Operating Systems and Online Operation • Based on the information summarized in Table IV, MicrosoftWindows is currently the most supported platform. Meanwhile,MATLAB is a popular software environment used in offlineanalysis. • Quite a few software packages in Table IV do not supportonline operations, such as, real-time sampling of data, onlinetuning, etc. The common nonvendor specific interfaces supportedfor online operations are Microsoft Windows dynamicdata exchange (DDE) and OLE for process control (OPC)[27] based on Microsoft object linking and embedding (OLE),component object model (COM) and distributed componentobject model (DCOM) technologies

  21. D. Modern Features • Remedial features such as differentiator filtering and integratoranti-windup are now mostly accommodated in a PIDsoftware package. Now the trend is to provide some additionalfeatures, such as diagnostic analysis, which prove tobe very helpful in practice. An example is highlighted byExperTune, which includes a wide range of fault diagnosisfeatures, such as valve wear analysis, robustness analysis, automaticloop report generation, multivariable loop analysis,power spectral density plot, auto and cross correlations plot,and shrink-swell (inverse response) process optimization, etc.Other additional features seen in commercial PID packagesinclude user-friendly interfaces, support of a variety of controllerstructures and allowing more user-defined settings indetermining PID parameters when necessary.

  22. PID HARDWARE MODULES • A. Hardware and Auto-Tuning • Many PID software features are now incorporated in hardwaremodules, particularly those used in process control. Arange of these are available from the four dominant vendors,namely, ABB, Foxboro, Honeywell and Yokogawa, as listedin Table V. Hardware brands from Elsag Bailey, Kent-TaylorInstruments, Hartmann & Braun and Alfa Laval have beenacquired by ABB. The following brands have been acquiredunder Emerson Process Management Group, namely, BrooksInstrument, Daniel, DeltaV, Fisher, Intellution, Micro Motion,PROVOX, Rosemount, RS3 and Westinghouse Process Control.Invensys Production Management Division consists ofAPV, Avantis, Esscor, Eurotherm, Foxboro, Pacific Simulation,Triconex, and Wonderware. Readers may refer to [3], [4], [9],[19], [20], [25], and [31] for more information on commercialPID controllers.

  23. B. ABB Controllers • ABB controllers offer two auto-tuning options, namely,quarter-wave and minimal overshoot. They also come with amanual fine-tuning option called control efficiency monitor(CEM). As shown in Fig. 8, six “key-performance” parameterslabeled are measured and displayed, allowing the user to varythe PID settings to match the process needs and to fine-tunemanually. • ABB also offers another tuning algorithm for its Micro-DCIseries, the Easy-Tune. The Easy-Tune algorithm approximatesa process by a first-order plus delay model, as shown in (10). Ituses a typical graphical method, where the step changes are appliedso as to measure the gain, delay and rise-time and, hence,the time-constant. These are then used to map the controller parametersthrough formulae shown in Table VI [1], which are optimizedfor the integral of time-weighted absolute error (ITAE)performance index.

  24. C. Foxboro Series • Foxboro 716C, 718, and 731C series use a proprietary selftuningalgorithm SMART. During start-up and control, SMARTcontinuously monitors the PV and automatically adjusts the PIDparameters according to the response of the PV, as shown inFig. 9. The advantage of SMART is its ability to operate withoutinjecting any artificial change into the system.

  25. D. Honeywell Tuners • Honeywell offers a “tuning on demand” controller, Autotune,which is not adaptive or continuous. They also offer an adaptivetuner, Accutune, which uses a combination of frequency andtime response analysis plus rule-based expert system techniquesto identify the process continually. An enhanced version of thisis, Accutune II, which incorporates a fuzzy logic overshootsuppression mechanism. It provides a “plug-and-play” tuningalgorithm, which will starts at the touch of a button or throughan input response data set identify and tune for any processesincluding integrating processes and those with a dead-time.This speeds up and simplifies the startup process and allowsretuning at any set-point in an “automatic mode.” The fuzzylogic overshoot suppression function operates independentlyfrom Accutune tuning as an add-on.

  26. E. Yokogawa Modules • Yokogawa first introduced its SUPER CONTROL moduleover a decade ago. Similar to Honeywell’s Accutune II, it alsouses a fuzzy logic based algorithm to eliminate overshoots,mimicking control expertise of an experienced operator. Itconsists of two main parts, namely, the set-point modifier andthe set-point selector. • The set-point modifier models the process and functions asan “expert operator” by first considering that a PID controlleris difficult to tune to deliver both a short rise-time and a lowovershoot. It thus seeks a knowledge base about the process, itsdynamics, and any nonlinearity of the process (including loadchanges). Then it leads the system into performing perfectly byfeeding artificial target set-points into the PID block through theset-point selector.

  27. F. Remarks • Many PID hardware vendors have made tremendous effortsto provide a built-in tuning facility. Owing to their vast experienceon PID control, most manufacturers have incorporatedtheir knowledge base into their algorithms. Current PID controlmodules provide “tuning on demand” with upset or “adaptivetuning” or both, depending on the model and user settings.Either technique has its advantages and disadvantages. For example,if using “tuning on demand” only, the controller needsto be retuned periodically and whenever changes occur in theprocess dynamics. This can be quite tedious and sometimesunder-performance can be too late to notice. Therefore, “tuningon demand” coupled with “gain-scheduling” could provide anadvantage.

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