214

2.14 Model-Based Predictive Control Patents

D. MORGAN (2005)

Patent Offices: Canadian Patents Database (patents1.ic.gc.ca/intro-e.html)European Patent Office (EPO) (www.european-patent-office.org/espacenet/info/

access.htm)German Patent Office (http://www.dpma.de/index.htm)Japan Patent Office (www.jpo.go.jp)United States Patent Office (USPTO) (www.uspto.gov)World Intellectual Property Organization (WIPO) (www.wipo.org/about-wipo/en/

index.html)

Research Tools: DPMApatentblatt (www.patentblatt.de/eng)INAS Patent Analysis Software (www.mayallj.freeserve.co.uk/inas.htm)IP Menu (www.ipmenu.com)Mospatent (www.mospatent.ru/en/links.htm)Thomson Derwant (www.ipr-village.com/index_ipr.html)Thomson Delphion (www.delphion.com)

Engineering Library: Linda Hall Library (www.lhl.lib.mo.us)

INTRODUCTION

From optics to distillation to financial derivatives trading tonavigation, the applications of model-based predictive controlseem practically endless. Likewise, mathematical techniquesvary from Model Algorithmic Control to Dynamic Matrix Con-trol to Inferential Control to Internal Model Control. Diverseapplications or functions, and techniques or forms, make model-based predictive control popular in the patent literature.

Patent Basics

For a patent to be granted, one has to tell all, or as put forthby the U.S. Code of Federal Regulations:

(a) The [Patent] specification must include a writtendescription of the invention or discovery and of the man-ner and process of making and using the same, and isrequired to be in such full, clear, concise, and exact termsas to enable any person skilled in the art or science towhich the invention or discovery appertains, or with whichit is most nearly connected, to make and use the same.

(b) The specification must set forth the precise inven-tion for which a patent is solicited, in such manner as todistinguish it from other inventions and from what is old.It must describe completely a specific embodiment of theprocess, machine, manufacture, composition of matter, or

improvement invented, and must explain the mode ofoperation or principle whenever applicable. The bestmode contemplated by the inventor of carrying out hisinvention must be set forth.

Thus, the freely available patent databases of the worldare a natural place to play out ones interest in any technicalfield. Whether one is interested in a particular application orthe fundamental basics of the calculations involved, amplematerial exists to satisfy that interest.

The U.S. Patent Office (USPTO) describes a patent as agrant of property right to exclude others from making, using,offering for sale, selling, or importing the invention. Once apatent is issued, the patentee must enforce the patent on his orher own. Any person who invents or discovers any new anduseful process, machine, manufacture, or composition of matter,or any new and useful improvement thereof, may obtain apatent, subject to the conditions and requirements of the law.The word process is defined by law as a process, act, ormethod, and primarily includes industrial or technical pro-cesses. Three general types of patents exist worldwide. In theU.S., they are described as follows:

Utility patents may be granted to anyone who inventsor discovers any new and useful process, machine,article of manufacture, or compositions of matters,or any new useful improvement thereof.

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2.14 Model-Based Predictive Control Patents 215

Design patents may be granted to anyone who inventsa new, original, and ornamental design for an articleof manufacture.

Plant patents may be granted to anyone who inventsor discovers and asexually reproduces any distinctand new variety of plants.

All of the patents discussed here fall under the Utility patentclassification.

Basic Patent History

Recent events on the global stage have made the patent pro-cess anything but basic. Thus, a brief recap of the historyof industrial intellectual property rights and a summary ofrecent developments is in order.

The United Kingdom claims to have the longest traditionof granting patents, beginning in 1449 with a Letters Patentissued by Henry VI to the manufacturer of stained-glasswindows at Eton College. Elizabeth I granted around 50open-ended term patents between 1561 and 1590 for themanufacture and sale of commodities such as soap, saltpeter,alum, leather, salt, glass, knives, sailcloth, starch, iron, andpaper. She rejected the application for a water closet patent,however.

By 1610, concerns about the effect of monopolies ledJames I to revoke all patents. In 1624, the doctrine of the publicinterest was incorporated into the Statute of Monopolies. Thisstatute banned monopolies except those for the term of 14years or under hereafter to be made of the sole working ormaking of any manner of new manufactures within this Realmto the true and first inventor. Such monopolies should not becontrary to the law nor mischievous to the State by raisingprices of commodities at home or hurt of trade.

The first U.S. patent law was enacted in 1790. The firstU.S. utility patent was issued in 1836 to the inventor of aspecial type of wheel. Whether this is the source of the phrasereinventing the wheel is uncertain. As of this writing, thereare over 6.6 million U.S. utility patents.

The first attempt to globalize industrial intellectual propertyrights was the 1883 Paris Convention. Further efforts led to thecreation of the World Intellectual Property Office (WIPO) in1967. WIPO is a specialized agency of the United Nationssystem of organizations with 179 member states. It administers16 industrial property rights and 6 copyright treaties. Global-ization efforts culminated with the Patent Cooperation Treaty(PCT). The PCT was concluded in 1970, amended in 1979, andmodified in 1984 and 2001. There are well over 100 PCTcontracting states at this time.

The PCT consolidates and streamlines the internationalpatent application process for inventors. Although the patentoffices of the individual states are still ultimately responsiblefor granting patents and collecting grant fees, inventors whouse international applications under PCT only have to applyonce.

They also pay a single application fee in the 1000 to 3000USD range with the fee variation largely depending on thesize of the application, the number of designated jurisdic-tions, whether they exercise a demand for preliminary exam-ination, and the choice of authority (USPTO or EPO forexample). In any event, the costs of multiple foreign filingsdwarf the PCT fees. Moreover, while buying time for furthercommercial assessments, the PCT filing fees are often lessthan the time value of money incurred with multiple domesticand foreign filings. The process allows an inventor to estab-lish global priority with one application.

WIPO promotes the value of the international patentsearch they sell. The results are set out in an internationalsearch report. This report is generally made available to theinventor by the fourth or fifth month after the internationalpatent application is filed. The international search report con-tains no comments on the value of an invention but lists priorart documents from the 30 million-plus universe of interna-tional patents (some of which are duplicates). Thus it com-ments on the possible relevance of the citations to the questionsof novelty and inventive step (nonobviousness). This enablesone to evaluate the chances of obtaining patents in the coun-tries designated.

The most immediate effect the patent researcher willnotice is the WO patent applicationsthe designation givento those applications filed under the PCT process. When apatent is finally granted by an individual state, the standardnumbering for that state will be employed, prefixed by thestates two-letter code.

Online Patent Databases

Currently, several online patent databases that anyone cansearch are available. The approaches taken vary greatly. Forexample, some databases have global reach while others arerestricted to the country that administers them. The USPTOis an example of the latter and the German database of theformer. Whichever database you choose to search, you canretrieve four basic types of records:

BibliographicalInformation such as Title, PatentNumber, Publication Date, Inventor(s), Applicant(s),Application Number, Priority Number(s), Classifi-cation, Literature References, and Prior PatentsCited. What you obtain depends on the country oforigin and the date, as newer patents tend to be filedunder the PCT.

AbstractsBrief descriptions of the invention, usuallyavailable in English. The Japanese patent office hasa just in time Japanese-to-English converter thatis quite accurate.

Full TextText-only form of a patent, usually in HTMLformat. Full text formats differ from country to coun-try. Some, such as the Canadian and the EuropeanPatent Offices, include drawings. There are some

2006 by Bla Liptk

216 Control Theory

drawbacks to full text. For example, the U.S. full textpatent database attempts to convey mathematical for-mulae using a plain English code page.

The USPTO provides full text records for patentsback to 1976. Full text records often provide hyper-links to other information, such as prior patents thatwere cited by the inventor. This is the type of infor-mation that allows for automated research.

Scanned Image Practically all patents are now avail-able or will be in the future in scanned form. PDFor TIFF file formats are usually employed. Whilenot convenient for automated research, one oftenwill ultimately need to obtain the original image inorder to obtain diagrams and mathematical formulaein their original form. Patents in this form are usuallyin the language preferred in the country of origin.Unfortunately, at todays bandwidth, one can onlydownload one page at a time.

Several countries and private organizations provideonline patent databases that anyone can search. Some, suchas Germanys DEPATISNet and the European Patent Officesesp@cenet, cover multiple foreign databases with theirsearch engines. Others, such as the United Kingdom, rely onthird parties, the European Patent Office (EPO), to providesuch services. Currently the EPOs esp@cenet has the fol-lowing coverage:

1. Abstracts, bibliographic data and full text: EPO, France, Germany, Switzerland, United

Kingdom, United States, and WIPO2. Abstracts and bibliographic data:

China and Japan3. Bibliographic data only:

Argentina, ARIPO, Australia, Austria, Belgium,Brazil, Bulgaria, Canada, Croatia, Cuba, Cyprus,Czechoslovakia, Czech Republic, Denmark,Egypt, Ellas, Eurasian Patent Office, Finland,GDR, Hong Kong, India, Ireland, Israel, Italy,Kenya, Korea, Latvia, Lithuania, Luxembourg,Malawi, Mexico, Moldova, Monaco, Mongolia,The Netherlands, New Zealand, Norway, OAPI,Philippines, Poland, Portugal, Romania, Russia,Slovakia, Slovenia, South Africa, Soviet Union,Spain, Turkey, Vietnam, Yugoslavia, Zambia,Zimbabwe

Most online databases are accessible via an epacenet.comlink that is a combination of the countrys two-letter abbre-viation and espacenet.com. Whenever a county also main-tains its own freely searchable database, the link for thatdatabase is given. In the case of Germany, the German databaseitself is linked to other databasesmuch like espacenetbutin German.

Patent Contents

Besides the basic types of information noted above, patentscontain a wealth of useful information for a researcher. Atthe beginning of U.S. patents in full text form, one first seesan abstract. This is followed by the bibliographic information.Next come links to patents cited by the inventor as prior art.Both patents that are useful to the present invention and thosethat will be improved upon by it are cited. Often what followsis a list of references to other, nonpatent resources that eitheraid in the understanding of the current patent, are to beincorporated by reference, or further describe the prior art tobe improved upon.

Following the bibliographical and claims informationusually comes a brief summary followed by a description ofthe prior art. Prior art descriptions often contain referencesto previous patents and the like, making it easy for one toquickly grasp an understanding of the field of invention andto understand what is to be improved upon. Next, the inventorwill typically give a brief description of how the prior art isto be improved upon followed by a description of any draw-ings accompanying the patent. What then follows is a detaileddescription of the invention, its preferred embodiments, andany examples. Examples often include sample data and evensource code in order to facilitate duplication of the work byanyone skilled in the art.

GUIDE

Patent literature concerning model-based control is rich inboth form and function. Form represents the various coretechnologies that may or may not have developed into spe-cific functions. Function represents specific implementationsthat may or may not have developed from established forms.The following attempt to produce a guide that characterizespatents according to their perceived form and/or function isbased on a survey of over 280 U.S. patents pertaining directlyto either the form and/or function of model-based control.These patents in turn cite over 1000 other patents and over750 other references.

Such supporting citations either deal directly with theform of model-based control or some superseding technolog-ical function. The U.S. patent database Web site provides avery convenient means of surfing to both the patents that agiven patent cites as well as those patents that cite a givenpatent. It also makes its own attempt at classification. Otherreferences can be obtained online from sources such as theLinda Hall Library in Kansas City, Missouri, or in some otherfashion via your own local university library system.

Forms

Prediction and adaptation are the business of Model-BasedPredictive Control (MBPC). To those ends, a wide variety ofapproaches exist that fit fairly well into two major classes.

2006 by Bla Liptk

2.14 Model-Based Predictive Control Patents 217

The first class involves predictors based on rigorous mathe-matical models of specific processes.

Generic controllers that can be used on any process formthe other major class of MBPC patents. Early implementa-tions focused on making controllers adaptive. Over timeand with the decrease in memory costs, multivariable predic-tive controllers gained in importance. One subclass of suchcontrollers is known as extended horizon predictive and pre-dictive adaptive controllers. This subclass is further dividedaccording to the method used to supply the extra inputsthat extend beyond the process horizon or delay time.

These controllers include the Extended Horizon AdaptiveController (EHC), the Receding Horizon Adaptive Controller(RHC), the Control Advance Moving Average Controller(CAMAC), the Extended Prediction Self-Adaptive Control-ler (EPSAC), the Generalized Predictive Controller (GPC),the Model Predictive Heuristic Controller (MPHC), and theDynamic Matrix Controller (DMC).

Neural net-based predictors, often called model-free pre-dictors because very little understanding of the process isrequired, are also popular members of this class. Monte Carlo

simulation, Kalman filters, hill climbing, constraint control,least squares, linear programming, quadratic programming,fuzzy logic, and partial differential equation-based approachesround out the generic predictor universe. Many of these knownmethods are represented in the U.S. patent literature.

U.S. Patents 4,349,869 and 4,616,308 and PCT patentWO03060614 all deal with the well-known Dynamic MatrixControl, or DMC, form of Model-Based Predictive Control(MBPC). The PCT version, published July 24, 2003, providesstep-by-step guidance through an actual distillation unit exam-ple (Figure 2.14a), with actual input and output data. TheU.S. patent versions, also highly detailed with respect to thecalculation procedures, suggest methods for coupling DMCwith an offline economic optimizer applied to a typical FCC.

U.S. Patent 4,358,822, Adaptive-Predictive Control Sys-tem, also provides detailed calculation procedures, two exam-ples, and source code. The first example is a binary distillationunit. The second is for a single-inputsingle-output (SISO)process. The well-documented source code is for an adaptivecontrol program capable of controlling SISO processes withtime delays.

FIG. 2.14aThe Dynamic Matrix Control (DMC) form of Model-Based Predictive Control (MBPC), provides step-by-step guidance through an actualdistillation unit example with actual input and output data.

7

TC

8

TC

LC

LC

FC

AI

5

FI

Feed

FuelGas

6

9

11

TIC-2002, SPTIC-2002, PV

TIC-2001, SPTIC-2001, PV

TIC-2001, OP

TIC-2002, OPFIC-2004, OP

FIC-2004, SPFIC-2004, PV

LIC-2007, SPLIC-2007, PV

LIC-2007, OP

AI-2022, PV

Topproduct

Midproduct

Btmproduct

FI-2005, PV

2006 by Bla Liptk

218 Control Theory

Functions

As mentioned above, the applications for model-based controlare practically limitless. As one would suspect, over time therange of applications has grown exponentially. While we tendto equate model-based predictive control with advanced digitalcontrol systems, inventors were applying analog systems wellbefore the dawn of the digital age. The prime advantage thatdigital computing holds over analog systems is not that it issomehow easier for the inventor to perfect. Rather, it has moreto do with the way in which computers facilitate disseminationof the art to those who actually apply it.

Auto-piloting aircraft were an early impetus for the art,and automation of advanced military craft remains a significantdriving force. Recently, interest in automotive applications hasgrown. The art is actually applied in order to facilitate itsapplication via computers. The literature on the use of MBPCin disk-drive tracking is extensive, for example. That the artitself is useful in bettering itself is rather unique.

Patents that are specific in form usually target a singleprocess. However, those intended for generic use will oftenprovide details, references, and examples of their use in specificprocesses. What follows is a guide to patents that are eitherspecifically intended for a given field or those that cite a givenfield as an example.

Aircraft Aircraft experience large variations in the gainsand time constants of the external disturbances they encoun-ter, making them strong candidates for the application ofmodel-based control. As time is compressed more and more

for fighter pilots, model-based control is finding a niche intarget identification and weapons targeting. One can even findpatents related to missile flight path control. Todays stealthaircraft, such as the F-117A Wobblin Gobblin, in whichfunction is often sacrificed for form, would not be flyablesave for MBPC.1,2

Computing MBPC finds application in two specific areasof computingwafer fab and disk-drive positioning. In waferfab, the goal is the reduction in run-by-run variability of theCVD, spin coating, and etching processes. CVD temperaturecontrol garners particular attention. Disk-drive accuracy andhence speed can be enhanced via MBPC, just as with anyother servo process.3,4

Utility Power MBPC patents relating to power generationand distribution attack problems at both the system and equip-ment levels. For example, there are MBPC patents for bettercontrol of boiler chemicals as well as patents for optimal dis-patching of multi-unit cogeneration facilities.

More and more plants designed for base load service arebeing used to meet peaking power demand. Steam turbinesdesigned to operate in a continuous range of steady-state con-ditions are being cycled to meet peaking load. This can inducelarge thermal stresses in both the turbine and the boiler as aresult of steep steam-to-metal temperature gradients thatdevelop during rapid loading or unloading of the turbine. Thus,much attention is given to predicting loads based on extendedload profiles. Figure 2.14b gives an example of a MBPC design

FIG. 2.14bPatent for MBPC design used in peak-shedding applications to predict loads based on extended load profiles.

200 100Boiler

pressurecontrol

Steam supplyvalve

control Valveactuator

180

170Steamplant

Turbine inletsteam temp.

Generatorpower

Boilercontroller

Turbine inlet steam temp.

250

Loaderror Fuzzylogic

circuit230

210

206

Selected electrical-load proles

Generator power signalLoad demandprediction circuit

Operator interface

Weightedoperationalconstraints

Model predictivecontroller

2006 by Bla Liptk

2.14 Model-Based Predictive Control Patents 219

from U.S. Patent 5,517,424, which is intended to address thisissue. Table 2.14c provides a sample of steam utility patentsand their application forms.57

Nuclear Energy Although regulatory issues tend to dis-courage the application of MBPC to direct control of nuclearpower systems, MBPC still finds use in the industry. Forexample, motor operator valve (MOV) reliability is a subjectof great concern. Hundreds of MOV failures have been inves-tigated in different studies. In one study, electromechanicaltorque switches and limit switches were identified as the

components at the root of approximately 32% of the docu-mented MOV failures.

Mechanical failures (failure to operate, bent stems, dam-age to valve seats, gear binding and damage) accounted for22% of the MOV failures. U.S. Patent 4,694,390 seeks toaddress this problem by instrumenting MOVs with a valvestem position sensor, a stem load sensor, and motor loadsensor. Then, an MBPC-based monitor periodically tests thestatus of the motor-operated valve and turns off the power tothe valves motor if certain predefined criteria for the valvestem position and the valve load are not satisfied.

TABLE 2.14cSteam Utility Patents and Their Areas of Application

Steam Power Patents

Patent No. Title Year Application Approach

3,758,762 Decoupled feedforward-feedback control system 9/11/1973 STEAM TURBINE MODEL3,939,328 Control system with adaptive process controllers especially adapted for

electric power plant operation2/17/1976 TURBINE SELF ADAPTIVE

4,027,145 Advanced control system for power generation 5/31/1977 COGENERATION ROM4,110,825 Control method for optimizing the power demand of an industrial plant 8/29/1978 COGENERATION ROM4,258,424 System and method for operating a steam turbine and an electric power

generating plant3/24/1981 STEAM TURBINE ROM

4,297,848 Method of optimizing the efficiency of a steam turbine power plant 11/3/1981 STEAM TURBINE ROM

4,403,293 Control apparatus for use in multiple steam generator or multiple hot water generator installations

9/6/1983 COGENRATION LP

4,628,462 Multiplane optimization method and apparatus for cogeneration of steam and power

12/9/1986 COGENRATION MULTIPLANE

4,630,189 System for determining abnormal plant operation based on whiteness 12/16/1986 POWER PLANT AR WHITENESS

4,768,143 Apparatus and method using adaptive gain scheduling algorithm 8/30/1988 WATER HEATER LEAST SQUARES4,802,100 Advanced cogeneration control system 1/31/1989 COGENRATION ROM

4,805,114 Economical dispatching arrangement for a boiler system 2/14/1989 COGENRATION ROM4,922,412 Apparatus and method using adaptive gain scheduling 5/1/1990 WATER HEATER LEAST SQUARES4,969,408 System for optimizing total air flow in coal-fired boilers 11/13/1990 COAL FURNACE ROM

5,040,725 Adaptive controller for forced hot water heating systems 8/20/1991 WATER HEATING ADAPTIVE5,159,562 Optimization of a plurality of multiple-fuel fired boilers using iterated

linear programming10/27/1992 BOILER LP

5,268,835 Process controller for controlling a process to a target state 12/7/1993 STEAM GEN ROM5,305,230 Process control system and power plant process control system 4/19/1994 STEAM TURBINE NEURAL NET5,311,421 Process control method and system for performing control of a controlled

system by use of a neural network5/10/1994 STEAM TURBINE NEURAL NET

5,347,466 Method and apparatus for power plant simulation and optimization 9/13/1994 STEAM TURBINE ROM5,442,544 Single input single output rate optimal controller 8/15/1995 ELECTRIC UTILITY ROC5,517,424 Steam turbine fuzzy logic cyclic control method and apparatus therefore 5/14/1996 STEAM TURBINE FUZZY LOGIC5,619,433 Real-time analysis of power plant thermohydraulic phenomena 4/8/1997 POWER PLANT RELAP5/MOD35,696,696 Apparatus and method for automatically achieving and maintaining

congruent control in an industrial boiler12/9/1997 BOILER CHEMS MACC

5,923,571 Apparatus and method for automatic congruent control of multiple boilers sharing a common feedwater line and chemical feed point

7/13/1999 BOILER CHEMS ROM

2006 by Bla Liptk

220 Control Theory

Pressurized and boiling water reactor core monitoring is animportant area for MBPC. For example, U.S. Patent 4,770,843discloses a MBPC application for controlling the stability ofa boiling water reactor using a digital computer to calculateonline, from distributed steady-state values of only power, flow,enthalpy, and pressure; a stability index for selected fuel assem-blies taking into account nuclear feedback as well as detailedhydrodynamic effects. U.S. Patent 4,234,925 applies linearprogramming (LP) to the problem of generating the optimumexcitation waveform for excitation of the plasma in fusion reac-tors. U.S. Patent 4,982,320 discloses a self-adaptive controllerfor particle beam accelerator control.8,9

Motor Fuel Production Patents on processes ranging fromgas lift oil production to hydrogen fluoride (HF) alkylationtarget the motor fuel production industry, where small opti-mizations can mean large returns. Hydrocracking and FluidCatalytic Cracking (FCC) are especially well represented.U.S. Patent 4,349,869 provides a detailed example of theapplication of Dynamic Matrix Control coupled with offlineoptimization to FCC.10,11

Pulp and Paper MBPC patents target practically everyaspect of pulp and paper production. Digestion, delignifica-tion, additive control, and final webbing all gain attention.12,13

Distillation Distillation is difficult to optimize because ofits numerous degrees of freedom both controllable, such asreboiler and heat input, and uncontrollable, such as feedcomposition. Making matters worse are the strong couplingsbetween variables and the nonlinearity encountered in high-purity towers. For example, as stated in U.S. Patent5,343,407, a 10% increase in boilup rate will result in onlya moderate increase in the purity of the bottoms product,while a 10% decrease would cause a drastic decrease in thepurity of the bottoms product. In addition, a 10% increasein boilup by itself will cause a drastic reduction in the purityof the overhead product.

Despite the inherent difficulties, high-purity distillationis a very common process. As noted again in U.S. Patent5,343,407, ethylene, propylene and styrene monomers ofnearly 100% purity are required for their respective poly-merization processes in order to produce polymers with thedesired characteristics. Also, for the production of industrialgrade acetic acid, levels of less than 200 ppm propanoicacid impurity must be maintained. In addition, chemicalintermediate xylene products are typically produced as highpurity products. Ethylene oxide and propylene oxide are sep-arated industrially to produce products, each with about 200ppm impurities.

Distillations prominence coupled with its tricky naturemakes it an ideal candidate for MBPC solutions. Table 2.14d

TABLE 2.14dPatents Related to Distillation and Their Applications

Distillation-Related Patents

Patent No. Title Date Application Approach

3,976,179 Controlling the temperature of a depropanizer tower bychromatographic analysis of feed and bottoms

8/24/1976 DEPROPANIZER RIED VP MODEL

4,030,986 Control for maximizing capacity and optimizingproduct cost of distillation column

6/21/1977 DISTILLATION COST FACTOR MODEL

4,070,172 Pressure responsive fractionation control 1/24/1978 DEMETHANIZER ROM

4,252,614 Control of multiple feed fractional distillation column 2/24/1981 MULTI-FEED ROM4,230,534 Control of a fractional distillation column 10/28/1980 DISTILLATION ROM4,358,822 Adaptivepredictive control system 11/9/1982 DISTILLATION DMC4,367,121 Fractional distillation column control 1/4/1983 DISTILLATION INTERNAL REFLUX MODEL

4,526,657 Control of a fractional distillation process 7/2/1985 DISTILLATION ROM4,560,442 Fractional distillation process control 12/24/1985 DISTILLATION INTERNAL REFLUX MODEL4,889,600 Fractionating column control apparatus and methods 12/26/1989 DISTILLATION REID VP MODEL

5,132,918 Method for control of a distillation process 7/21/1992 DISTILLATION ROM5,260,865 Nonlinear model-based distillation control 11/9/1993 DISTILLATION ROM5,343,407 Nonlinear model-based distillation control 8/30/1994 DISTILLATION MCCABE THIELE MODEL5,396,416 Multivariable process control method and apparatus 3/7/1995 GAS FRACTIONATION SELF ADAPTIVE DMC5,477,449 Hierarchical model predictive control system based on

accurate manipulation variable prediction12/19/1995 DISTILLATION DMC VARIANT

5,522,224 Model predictive control method for an air-separation system

6/4/1996 AIR SPEARATION ROM

2006 by Bla Liptk

2.14 Model-Based Predictive Control Patents 221

provides a sample of distillation-related patents and theirforms.14,15

Robotics It is unfortunate that something once labeled anautonomwhich would imply independent actionhasbeen more recently labeled a robot, when that implies

something that performs the same task in the same way, overand over again. The patent literature alone would beg to differas it reflects a movement to make robots more adaptive andautonomous.

Today, hybrid robotic control incorporates adaptive forceand position controllers based on highly rigorous models.

FIG. 2.14ePatent describing a control strategy for braking.

Start

Brakeapplied?

Determine vehiclemass

Determine roadload

Determine grade

Make fuzzylogic decision

Decisionto downshift ?

Signal shift

End

Braking load< max tractive

eorts?

Update road load withaerodynamic drag changes

Determine brake load

Determine brake temp

Predict braking load

Determine actualbraking load

Determine elevationchange

Determine driver intent

Determine other criteria

No

Yes

2006 by Bla Liptk

222 Control Theory

Automatic targeting systems can recognize moving targetsand predict where they will be once fired upon. Unmannedaerial vehicles are able to perform missions unattended.16,17

Optics, Photography, and Astronomy Many of the tech-nologies for the Keck telescope on the Mauna Kea volcanoin Hawaii are fairly well represented in the patent literature,including relatives of its MBPC-based adaptive optics. Look-ing back at Earth, U.S. Patent 4,748,448 discloses a MBPCapproach to gauging wind speed and direction from oceanicwave action observed from a satellite. Optimization andquality control of photographic emulsion products are alsorepresented.18,19

Automotive The automotive field is one of the latest towhich MBPC has been applied. Fuel-to-air ratio (lambda),braking, and cylinder disablement are some examples ofareas where both rigorous and generic models are just someof the applications where inventions have been disclosed.U.S. Patent 6,625,535 discloses a control scheme for braking,whose logic is shown in Figure 2.14e.20,21

Polymers The patent literature describes MBPC-basedinventions related to monomer production (for example, eth-ylene), polymerization reactions, and the production of poly-mer suspensions.

An area of particular interest is predicting polymer meltindex from process data rather than having to rely on samplestaken to the lab. As U.S. Patent 5,504,166 states,

The desired control of the polymerization process isextremely difficult to attain because of the holdup time ofpolymerization reactors and the time involved in obtainingpolymer samples and measuring the properties of thosesamples. Because of this time period, the polymerizationconditions employed in the reactor at the time at which aproperty of a polymer sample withdrawn from the reactoris measured are not necessarily the same as the polymer-ization conditions employed in the reactor at the time atwhich such polymer sample was produced in the reactorand/or withdrawn from the reactor.

This is especially the case when the attempted controlof the polymerization process is based on the measure-ment of the melt flow rate or in other words, the meltindex of the polymer product as determined accordingto the ASTM Test D-1238-62T. Although the melt flowrate or the melt index is a satisfactory control propertyfor most solid polymers prepared from alpha-olefins, thetime consumed in obtaining a polymer sample for mea-surement and in measuring the melt index of the samplecombines with the aforesaid holdup time of the reactor toseriously hamper accurate control of the polymerizationprocess.22,23

Financial Derivatives Trading Underlying the price of acommodity is a market process that can be modeled just likeany other process. A trader makes a series of inputs to a con-tinuous process based on analysis of feedback from a market.

Financial engineering was born in 1973 when a math-ematician, Fischer Black, and an economist, Myron Scholes,devised one of the first mathematically accepted approachesfor pricing options that can only be exercised at their expi-ration date (European options). Today there are well overa thousand systems trading applications on the market thatcan be used by anyone to control portfolios.

According to U.S. Patent 6,546,375: What has becomeknown as the BlackScholes option formula was describedfirst in The pricing of options and corporate liabilities, Jour-nal of Political Economy 81 (1973). The BlackScholes optionformula is presently of widespread use in financial markets allover the world. The price of such an option can be found bysolving the BlackScholes equation with the initial conditionat expiration (i.e., the payoff of the option). The BlackScholesequation is a reverse diffusion equation with parameters deter-mined by the statistical characteristics of involved stocks andcurrencies such as risk-free interest rate, holding cost orexpected dividends, and volatility.

Determining the forward pricing of American options,which can be exercised before expiration, is difficultbecause it leads to an infinite-dimensional free boundaryproblem that cannot be solved explicitly nor finitely. Inorder to approximate a solution, U.S. Patent 6,546,375employs a discretized partial differential linear comple-mentary problem (PDLCP)-based system. An optimiza-tion problem in the form of a mathematical program withequilibrium constraints (MPEC) is also used to deriveimplied volatilities of the assets underlying the subjectderivatives.

Other patents integrate the MBPC side of the overallprocess with the requisite feedback information systems,much as a DCS workstation works with an operator and aprocess. Orders can be placed, real-time data can be ana-lyzed, margins can be calculated, and buy and sell signalscan be generated automatically via ones Internet-readyPC.24,25

References

1. U.S. Patent 4,258,545, Optimal Control for a Gas Turbine Engine.2. U.S. Patent 4,812,990, System and Method for Optimizing Aircraft

Flight Path.3. U.S. Patent 5,646,870, Method of Setting and Adjusting Process

Parameters to Maintain Acceptable Critical Dimensions Across EachDie of Mass-Produced Semiconductor Wafers.

4. U.S. Patent 6,625,513, Run-to-Run Control over Semiconductor Pro-cessing Tool Based Upon Mirror Image Target.

5. U.S. Patent 4,628,462, Multi-Plane Optimization Method and Appa-ratus for Cogeneration of Steam and Power.

6. U.S. Patent 5,696,696, Apparatus and Method for AutomaticallyAchieving and Maintaining Congruent Control in an IndustrialBoiler.

7. U.S. Patent 5,923,571, Apparatus and Method for Automatic Con-gruent Control of Multiple Boilers Sharing a Common FeedwaterLine and Chemical Feed Point.

8. U.S. Patent 5,392,320, Core Automated Monitoring System.

2006 by Bla Liptk

2.14 Model-Based Predictive Control Patents 223

9. U.S. Patent 4,694,390, Microprocessor-Based Control and Diagnos-tic System for Motor-Operated Valves.

10. U.S. Patent 4,437,977, Control of a Catalytic Cracking Unit.11. U.S. Patent 6,595,294, Method and Device for Gas-Lifted Wells.12. U.S. Patent 5,301,102, Multivariable Control of a Kamyr Digester.13. U.S. Patent 6,328,851, Method and Equipment for Controlling Prop-

erties of Paper.14. U.S. Patent 4,560,442, Fractional Distillation Process Control.15. U.S. Patent 5,522,224, Model Predictive Control Method for an Air-

Separation System.16. U.S. Patent 4,621,332, Method and Apparatus for Controlling a

Robot Utilizing Force, Position, Velocity, Spring Constant, MassCoefficient, and Viscosity Coefficient.

17. U.S. Patent 4,725,942, Controller for Multi-Degree of Freedom Non-linear Mechanical System.

18. U.S. Patent 5,265,034, Feedback Controlled Optics with Wave-FrontCompensation.

19. U.S. Patent 5,067,067, Method for Evaluating and DesigningLenses.

20. U.S. Patent 6,594,573, Method for Regulating a Clutch or a Brakein a Transmission.

21. U.S. Patent 6,625,535, Adaptive Power-Train Braking Control withGrade, Mass, and Brake Temperature.

22. U.S. Patent 4,668,473, Control System for Ethylene PolymerizationReactor.

23. U.S. Patent 6,106,785, Polymerization Process Controller.24. U.S. Patent 6,061,662, Simulation Method and System for the Val-

uation of Derivative Financial Instruments.25. U.S. Patent 6,546,375, Apparatus and Method of Pricing Financial

Derivatives.

2006 by Bla Liptk

TABLE OF CONTENTSChapter 2.14: Model-Based Predictive Control PatentsINTRODUCTIONPatent BasicsBasic Patent HistoryOnline Patent DatabasesPatent Contents

GUIDEFormsFunctions

ReferencesA.1 International System of UnitsA.2 Engineering Conversion FactorsA.3 Chemical Resistance of MaterialsA.4 Composition of Metallic and Other MaterialsA.5 Steam and Water TablesA.6 Friction Loss in PipesA.7 Tank VolumesA.8 Partial List of SuppliersA.9 Directory of Lost CompaniesA.10 ISA Standards