JPH04148672A - Control of fermentation tank - Google Patents
Control of fermentation tankInfo
- Publication number
- JPH04148672A JPH04148672A JP26937990A JP26937990A JPH04148672A JP H04148672 A JPH04148672 A JP H04148672A JP 26937990 A JP26937990 A JP 26937990A JP 26937990 A JP26937990 A JP 26937990A JP H04148672 A JPH04148672 A JP H04148672A
- Authority
- JP
- Japan
- Prior art keywords
- culture
- phase
- control
- control method
- fuzzy
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000855 fermentation Methods 0.000 title abstract description 13
- 230000004151 fermentation Effects 0.000 title abstract description 13
- 238000000034 method Methods 0.000 claims abstract description 35
- 238000004519 manufacturing process Methods 0.000 claims abstract description 19
- 238000012258 culturing Methods 0.000 claims description 3
- 230000008569 process Effects 0.000 claims description 2
- WQZGKKKJIJFFOK-GASJEMHNSA-N Glucose Natural products OC[C@H]1OC(O)[C@H](O)[C@@H](O)[C@@H]1O WQZGKKKJIJFFOK-GASJEMHNSA-N 0.000 description 23
- 239000008103 glucose Substances 0.000 description 23
- QGZKDVFQNNGYKY-UHFFFAOYSA-N Ammonia Chemical compound N QGZKDVFQNNGYKY-UHFFFAOYSA-N 0.000 description 12
- WHUUTDBJXJRKMK-UHFFFAOYSA-N Glutamic acid Natural products OC(=O)C(N)CCC(O)=O WHUUTDBJXJRKMK-UHFFFAOYSA-N 0.000 description 12
- 235000013922 glutamic acid Nutrition 0.000 description 12
- 239000004220 glutamic acid Substances 0.000 description 12
- 239000001963 growth medium Substances 0.000 description 9
- 235000015097 nutrients Nutrition 0.000 description 8
- 239000002609 medium Substances 0.000 description 7
- 238000005259 measurement Methods 0.000 description 6
- 230000006698 induction Effects 0.000 description 5
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 description 4
- 230000035755 proliferation Effects 0.000 description 4
- 230000007704 transition Effects 0.000 description 4
- VHUUQVKOLVNVRT-UHFFFAOYSA-N Ammonium hydroxide Chemical compound [NH4+].[OH-] VHUUQVKOLVNVRT-UHFFFAOYSA-N 0.000 description 3
- 235000011114 ammonium hydroxide Nutrition 0.000 description 3
- 229910000069 nitrogen hydride Inorganic materials 0.000 description 3
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 2
- 229910021529 ammonia Inorganic materials 0.000 description 2
- 229910052799 carbon Inorganic materials 0.000 description 2
- 230000000052 comparative effect Effects 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 229910052757 nitrogen Inorganic materials 0.000 description 2
- 238000003756 stirring Methods 0.000 description 2
- 241000186361 Actinobacteria <class> Species 0.000 description 1
- 244000063299 Bacillus subtilis Species 0.000 description 1
- 235000014469 Bacillus subtilis Nutrition 0.000 description 1
- 241000894006 Bacteria Species 0.000 description 1
- 102000004190 Enzymes Human genes 0.000 description 1
- 108090000790 Enzymes Proteins 0.000 description 1
- 230000002159 abnormal effect Effects 0.000 description 1
- 239000013543 active substance Substances 0.000 description 1
- 239000000654 additive Substances 0.000 description 1
- 230000000996 additive effect Effects 0.000 description 1
- 238000005273 aeration Methods 0.000 description 1
- 230000003698 anagen phase Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 210000004102 animal cell Anatomy 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000003115 biocidal effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000004113 cell culture Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000012010 growth Effects 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 239000004570 mortar (masonry) Substances 0.000 description 1
- 238000011017 operating method Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 239000000758 substrate Substances 0.000 description 1
Landscapes
- Feedback Control In General (AREA)
- Apparatus Associated With Microorganisms And Enzymes (AREA)
- Micro-Organisms Or Cultivation Processes Thereof (AREA)
Abstract
Description
【発明の詳細な説明】
〔産業上の利用分野〕
本発明は発酵槽の制御方法、さらに詳しくは経時的ある
いは培養状態に応じて異なる制御を行う、培養系におけ
る計算機を利用したファジープロダクションルールによ
る培養フェーズの推定とその培養フェーズに対応した制
御方法を行わせる方法とからなる発酵槽の制御方法に関
する。[Detailed Description of the Invention] [Field of Industrial Application] The present invention relates to a method for controlling a fermenter, and more specifically, a method for controlling a fermenter, and more specifically, a method for controlling a fermenter using a fuzzy production rule using a computer in a culture system, which performs different control over time or depending on the culture state. The present invention relates to a method for controlling a fermenter, which includes estimating a culture phase and performing a control method corresponding to the culture phase.
従来、発酵槽の自動制御においては、ｐＨ。 Conventionally, in automatic control of fermenters, pH.
ＤＯ１温度等の各項目について定値制御、あるいは予め
プログラムされた制御を実行するプログラム制御が行わ
れていた。また、発酵槽の培養状態を考慮して制御方法
を決定する必要がある場合には、運転員が現場で計測分
析結果等に基づき培養状態を判定し、適宜制御を行って
いた。For each item such as DO1 temperature, fixed value control or program control that executes preprogrammed control has been performed. In addition, when it is necessary to determine a control method in consideration of the culture state of the fermenter, an operator determines the culture state based on measurement and analysis results on site and performs appropriate control.
しかし、上記定値制御やプログラム制御のみで運転する
ことは培養状態の変化に対する適切な判断方策の追加を
行うことかできず、常に運転員による補正を適時行う必
要があった。また、運転員によるそのような制御方策の
決定は運転員の経験又は実績に基づいて行われているた
め、自動制御系にそれらを反映し、自動制御化をするこ
とは非常に困難であった。さらに、詳しくは、一般に発
酵槽の運転において、まず計測データ、経過時間、外観
等から培養状態が異常か正常か、又は培１Ｎ経過全体の
中でどのような状態にあるかを判断し、その判断に基つ
き制御方法を決定していた。However, operating only with the above-mentioned fixed value control or program control does not allow addition of appropriate judgment measures for changes in culture conditions, and it is necessary to always make corrections by the operator in a timely manner. In addition, since decisions on such control measures by operators are based on the operator's experience or track record, it has been extremely difficult to reflect them in the automatic control system and implement automatic control. . Furthermore, in detail, in general, when operating a fermenter, it is first determined from measurement data, elapsed time, appearance, etc. whether the culture state is abnormal or normal, or what state it is in during the entire culture 1N process, and then The control method was determined based on judgment.
しかしながら、例えば訪導期、対数増殖期等のような人
間の思考方法に沿った情報は従来は制御系に取り込むこ
とが難しく、多くは無視されたため、発酵槽の自動制御
を困難なものにしていた。However, it has been difficult to incorporate information based on the human way of thinking, such as the visiting phase and logarithmic growth phase, into the control system and was often ignored, making automatic control of fermenters difficult. Ta.
（発明が解決しようとする課題）
本発明は上記事情に鑑みなされたもので、その目的とす
るところは発酵槽の自動制御を行うことにある。(Problems to be Solved by the Invention) The present invention was made in view of the above circumstances, and its purpose is to automatically control a fermenter.
本発明者らは、これらの間朗を解決するために種々検討
した結果、培養槽内の培養の状態を各種センサーにより
検出し、その測定結果を電子計算機に取り込み、前記測
定値を基にファジープロダクションルールを用いて培養
フェーズの推定を行い、推定されたフェーズに対応して
予め準備されている制御方法を実行することにより、直
接オンライン測定をできない項目を一定に保持すること
、あるいは目的生産物を最大にすることを可能にしたも
のである。As a result of various studies in order to solve these problems, the present inventors detected the state of the culture in the culture tank using various sensors, imported the measurement results into a computer, and based on the measurement values, fuzzy By estimating the cultivation phase using production rules and executing a control method prepared in advance corresponding to the estimated phase, items that cannot be directly measured online can be held constant, or the desired product can be This makes it possible to maximize the
即ち、本発明は発酵槽の培養経過を予め複数のフェーズ
に分割すると共に、分割した各フェーズに対応する制御
方法を定めておき、培養時において培養槽から取り込ん
だ培養槽の状態を示すデータに基づいてファジープロダ
クションルールにより培養中のフェーズを同定すると共
に、同定したフェーズに対応する予め定めた制御方法を
実行するものである。That is, in the present invention, the progress of culturing in a fermenter is divided into a plurality of phases in advance, a control method corresponding to each divided phase is determined, and data indicating the state of the fermenter taken from the fermenter at the time of culturing is used. Based on this, the phase during cultivation is identified using fuzzy production rules, and a predetermined control method corresponding to the identified phase is executed.
また、本発明は同定されたフェーズに対応した、詳しく
はその時点の各フェーズの重みに応じた加算的な、又は
個別併行的な制御方法を運転者により、又は好ましくは
電子計算機によりオンラインで行なうものである。Further, the present invention performs an additive or individual parallel control method corresponding to the identified phases, more specifically, according to the weight of each phase at that time, by the driver or preferably online by a computer. It is something.
以下、図面を参照して本発明をさらに詳細に説明する。Hereinafter, the present invention will be explained in more detail with reference to the drawings.
第１図は本発明の一実施！！線を示すフローシートであ
る。即ち、培養槽ｌにおいて通常の方法により培養を行
う場合につき例示すると、培養槽１内などのｐＨ，Ｄｏ
、温度等の測定値を培養槽１などに取り付けたセンサー
類９からインターフェース４を経由してモニター用計算
機３に取り込む。モニター用計算機３に取り込んだ測定
値はファジー制御用計算機２に送り込まれる。ファジー
制御用計算機２では、これらの測定値等の情報に基づい
てファジー推論を行い培養フェーズの推定を行う。次い
で、このようにして決定された、複数であることもある
培養フェーズに対応する、予め定めた制御方法の指令を
各制御機器に送出する。本例においては、制御の指令は
培地供給ポンプ６及び栄養源供給ポンプ８に送られ、そ
れぞれの供給量の制御が行われる。これにより、培地タ
ンク５及び栄養源タンク７中の培地及び栄養源が定めら
れた供給速度で培養槽１に供給される。ここでグルタミ
ン酸発酵の場合にはセンサー類９で測定する項目は温度
、ｐＨ，Ｄｏ、ＣＯ。Figure 1 shows one implementation of the present invention! ! This is a flow sheet showing lines. That is, to exemplify the case where culture is carried out by a normal method in the culture tank 1, the pH and Do
, temperature and other measured values are taken into the monitoring computer 3 via the interface 4 from sensors 9 attached to the culture tank 1 or the like. The measured values taken into the monitor computer 3 are sent to the fuzzy control computer 2. The fuzzy control computer 2 performs fuzzy inference based on information such as these measured values to estimate the culture phase. Next, commands for a predetermined control method corresponding to the culture phases determined in this way, which may be plural, are sent to each control device. In this example, control commands are sent to the culture medium supply pump 6 and the nutrient source supply pump 8, and the respective supply amounts are controlled. Thereby, the culture medium and the nutrient source in the culture medium tank 5 and the nutrient source tank 7 are supplied to the culture tank 1 at a predetermined supply rate. In the case of glutamic acid fermentation, the items measured by the sensors 9 are temperature, pH, Do, and CO.
発生速度、アンモニア添加速度などであり、培地タンク
５にはグルコース、栄養源タンフッにはアンモニア水が
仕込んである。The growth rate, ammonia addition rate, etc. are stored in the culture medium tank 5 with glucose and the nutrient source tank with aqueous ammonia.
本実施例においては、計算機（パーソナルコンピュータ
）を２台用いて制御を行っているが、１台のマルチタス
クのコンピュータを用いて制御を行うこともできるもの
である。In this embodiment, control is performed using two computers (personal computers), but control may also be performed using one multitasking computer.
また、本実施例におけるファジー制御用計算機２におけ
る機能はファジー推論による培養状態の推定と、それに
基づく制御方法の決定と、決定に従う制御指令の発信と
にある。即ち、培養状態のフェーズ推定方法として、ま
ず一連の培養経過をいくつかの培養状！！ｉ（フェーズ
）に分割する。例えば、誘導フェーズ、増殖フェーズ、
遷移フェーズ、生産フェーズ等のように対象とする培養
系の特性に応じて分割し、その各々に対して予め制御方
法を割当てておく、そして、培養時においては、培養の
各時点における培１１ｆｉの状態の計測値（センサー出
力）を用いてファジープロダクションルールにより、フ
ェーズの推定を行い、推定したフェーズに対応した制御
方法を決定するものである。用いるプロダクションルー
ルの一例として、グルタミン酸発酵の場合には、以下の
ようにしてフェーズを決定する。即ち、
ｒもし、培養時間；中
ＣＯ２発生速度； 中
Ｎ Ｈ３供給速度； 中 ならば、
現 時 点； 生産フェーズ
である。Further, the functions of the fuzzy control computer 2 in this embodiment include estimating the culture state by fuzzy inference, determining a control method based on the estimation, and issuing a control command in accordance with the determination. In other words, as a method for estimating the phase of the culture state, first, a series of culture progresses are recorded as several culture states! ! Divide into i (phases). For example, induction phase, proliferation phase,
The culture system is divided according to the characteristics of the target culture system, such as transition phase, production phase, etc., and a control method is assigned to each of them in advance. The phase is estimated using fuzzy production rules using state measurement values (sensor output), and a control method corresponding to the estimated phase is determined. As an example of the production rule used, in the case of glutamic acid fermentation, the phase is determined as follows. That is, if r: culture time; medium CO2 generation rate; medium NH3 supply rate; medium, then current point; production phase.
生産フェーズでは、下記式
グルコース供給速度＝ （ａ） Ｘ （ＮＨ３添加量）
＋（ｂ）（但、ａ、ｂは定数）
辷より、グルコース供給速度を決定する。 ｊ上記の
ようなルールを各フェーズ毎に用意しておき、培養時間
、ＣＯ２発生速度、ＮＨ３供給速度等のデータよりフェ
ーズ推定をＭＩＮ−ＭＡＸ演算により行うものである。In the production phase, the following formula glucose supply rate = (a) X (NH3 addition amount)
+(b) (where a and b are constants) Determine the glucose supply rate from the weight. j Rules such as those described above are prepared for each phase, and phase estimation is performed by MIN-MAX calculation from data such as culture time, CO2 generation rate, NH3 supply rate, etc.
これらの推論は通常のパーソナルコンピュータで数秒以
内で実行することができ、これに基づき制御方法の変更
を数分間隔で行うことを可能とするものである。These inferences can be executed within a few seconds on an ordinary personal computer, and based on this, it is possible to change the control method at intervals of several minutes.
また、制御方法は計算機によりオンラインで実行するこ
とが応答の速さを高め、頻度を増すことがてきて望まし
いが、培養量、その他の条件によっては制御指示を作業
者によって行なフても良い。In addition, it is desirable to perform the control method online using a computer because it increases response speed and frequency, but depending on the culture volume and other conditions, control instructions may be performed by an operator. .
本例においては、培養経過を誘導フェーズ、増殖フェー
ズ、生産フェーズ等に分割して発酵の進行をとらえ、便
宜上これらの各フェーズに運転操作や制御方法を割当て
て運転を行っているが、本例に限られず種々の培養系に
適用できるものである。即ち、上記グルタミン酸発酵以
外にも枯草菌、こうじ菌による酵素生産や動物細胞培養
における生産活性物質の生産、放線菌等による抗生物質
生産にも必要に応じこれらに対応する各種フェーズを設
定して適用てきる。In this example, the progress of fermentation is divided into the induction phase, proliferation phase, production phase, etc., and operation operations and control methods are assigned to each of these phases for convenience. It can be applied to various culture systems without being limited to. That is, in addition to the above-mentioned glutamic acid fermentation, various phases corresponding to these can be set and applied as necessary to enzyme production by Bacillus subtilis and Koji bacteria, production of active substances in animal cell culture, and antibiotic production by actinomycetes. I'll come.
以下、実施例により本発明を具体的に説明する。 Hereinafter, the present invention will be specifically explained with reference to Examples.
実１江１ 第１図に示す装置を用いてグルタミン酸発酵を行った。fruit 1 jiang 1 Glutamic acid fermentation was performed using the apparatus shown in FIG.
培養系は、培養槽１に培地供給ポンプ６によって炭素源
としてグルコースを、栄１！源供給ポンプ８によって窒
素源としてアンモニア水を供給し、培ＩＩ糟１内のＢｒ
ｅｖｉｂａｃｔｅｒｉｕｍ ＳＰ、によるグルタミン酸
発酵の流加培養である。本培養系では、培養Ｊ１！１に
おいてグルタミン酸の高濃度生産を行うため、グルコー
ス濃度を約２５ ｇ／Ｉｌの一定値に保つように培地供
給ポンプ６によるグルコースの供給速度を調整する運転
を行っているが、グルコース濃度の直接測定が困難なた
め、従来自動化が難しかったものである。In the culture system, glucose is supplied as a carbon source to the culture tank 1 by a medium supply pump 6, and Sakae 1! Ammonia water is supplied as a nitrogen source by the source supply pump 8, and the Br in the culture medium 1 is
This is a fed-batch culture of glutamic acid fermentation by Evibacterium SP. In the main culture system, in order to produce high concentration of glutamic acid in culture J1!1, the glucose supply rate by the medium supply pump 6 is adjusted to maintain the glucose concentration at a constant value of about 25 g/Il. However, it has traditionally been difficult to automate because it is difficult to directly measure glucose concentration.
本実施例おいては、ファジー推論を基にフェーズ分割を
行うことにより培養槽１のグルコース濃度をほぼ一定に
保つ運転を行うことができた。In this example, by performing phase division based on fuzzy inference, it was possible to maintain the glucose concentration in the culture tank 1 almost constant.
即ち培養Ｊ１１１および栄養源タンク７からの計測デー
タをセンサー類９を通じてインターフェース４を介しモ
ニター用計算機３に取り込み、培養状態のモニターを行
い、さらにそのデータをファジー制御用計算機２に送信
し、制御方法を決定し、培地（グルコース）供給ポンプ
を調節し、グルコース濃度を一定に保った。That is, the measurement data from the culture J111 and the nutrient source tank 7 are taken into the monitoring computer 3 via the interface 4 through the sensors 9, the culture status is monitored, and the data is further sent to the fuzzy control computer 2 to perform the control method. was determined and the medium (glucose) feed pump was adjusted to keep the glucose concentration constant.
ファジー制御用計算機２においては、まず本培養系の培
養状態を誘導フェーズ、増殖フェーズ、遷移フェーズ、
及び生産フェーズに予め分割し、それぞれのフェーズに
おける制御方法、即ちグルコースの添加量を定めた。即
ち、ファジー推論で培養フェーズの推定を行った後、グ
ルコース供給速度＝ （ａ）Ｘ （ＮＨａ供給速度）＋
（ｂ）の式でグルコースの供給速度を算出した。なお、
ａ。The fuzzy control computer 2 first changes the culture state of the main culture system into the induction phase, proliferation phase, transition phase,
and production phases, and the control method for each phase, that is, the amount of glucose added, was determined. That is, after estimating the culture phase using fuzzy inference, glucose supply rate = (a)X (NHa supply rate) +
The glucose supply rate was calculated using the formula (b). In addition,
a.
ｂの値は各フェーズにおける適当な値を統計的、に求め
た。The value of b was statistically determined as an appropriate value for each phase.
培養状態の同定は、培養時間、００２発生速度、Ｎ Ｈ
ｓ供給速度から推定することとした。例えば、
ｒ 培 養時 間；小
ＣＯ２発生速度：小
ＮＨ，供給速度：小 」
ならば、現 時 点；誘導フェーズのようにファジ
ープロダクションルール化し、プログラミングして計算
機制御に適用した。なお、この推論は３分毎にファジー
制御用計算機２で行い、決定された供給速度になるよう
にその都度グルコース供給ポンプ６を制御した。The culture status can be identified by culture time, 002 generation rate, N H
It was decided to estimate from the s supply rate. For example, if "r culture time; small CO2 generation rate: small NH, supply rate: small", then we created a fuzzy production rule such as "currently" in the induction phase, programmed it, and applied it to computer control. This inference was performed by the fuzzy control computer 2 every 3 minutes, and the glucose supply pump 6 was controlled each time to achieve the determined supply rate.
以上の方法によって、第２図に示すように誘導フェーズ
から始まり、増殖フェーズ、遷移フェーズ、生産フェー
ズと各フェーズの制御への移行がスムーズに行えた。こ
の場合グルコースの濃度をほぼ一定に保つことに成功し
た。なお、図の上部の横軸は時間の経過と共に、どのル
ールを適用したかを示した（斜線部）ものである。交差
斜線部が各フェーズの典型領域で、その前後の一方向斜
線部は左側は立ち上り、右側は漸次そのフェーズが衰え
て消滅していく領域である。従って２以上のフェーズが
重複した時間体では、各フェーズに対応する制御が、夫
々のフェーズがそこでもつ、いわばウェイトに従って合
算された形で実行される。By the above method, as shown in FIG. 2, starting from the induction phase, the transition to the proliferation phase, transition phase, production phase, and control of each phase could be smoothly performed. In this case, we succeeded in keeping the glucose concentration almost constant. Note that the horizontal axis at the top of the figure shows which rules were applied over time (shaded area). The intersecting hatched area is a typical area of each phase, and the unidirectional hatched area before and after it is an area where the phase rises on the left side and gradually weakens and disappears on the right side. Therefore, in a time field in which two or more phases overlap, control corresponding to each phase is executed in a summed manner according to the so-called weights that each phase has.
実ｌｄ肚ｌ 第１図に示す装置を用いてグルタミン酸発酵を行った。real body Glutamic acid fermentation was performed using the apparatus shown in FIG.
培養系は、培養槽１に培地供給ポンプ６によって炭素源
としてグルコースを、栄養源供給ポンプ８によって窒素
源としてアンモニア水を供給し、培養槽１内のＢｒｅｖ
ｉｂａｃｔｅｒｉｕｍ ＳＰ、によるグルタミン酸発酵
の流加培養である。培養条件の例として、容量５ｆｉ（
有効容量３ｊり、タービンタイプの攪拌翼を備えた培養
槽を用い、温度３０℃、ＰＨ７〜８、攪拌数５００〜６
００ｒｐｍ。The culture system supplies a culture tank 1 with glucose as a carbon source by a medium supply pump 6 and aqueous ammonia as a nitrogen source by a nutrient supply pump 8.
This is a fed-batch culture of glutamic acid fermentation by Ibacterium SP. As an example of culture conditions, a capacity of 5fi (
Using a culture tank with an effective capacity of 3J and equipped with a turbine-type stirring blade, the temperature is 30°C, the pH is 7-8, and the number of stirring is 500-6.
00rpm.
通気量ＩＶＶＭ（ｌｊ！−工７／Ｊ２−分−液）の条件
で、初発グルコース濃度を２５ ｇ／ｌに保つように５
００ ｇ／ｊ！のグルコース溶液を流加する場合を考え
た。本培養系では、培養槽１において、グルタミン酸の
高濃度生産を行うため、グルコース濃度を約２５ ｇ／
Ｉｔの一定値に保つように培地供給ポンプ６によるグル
コースの供給速度を調整する運転を行っているが、これ
は従来はグルコース濃度の直接測定が困難なため、自動
化が難しいものであった。5 to maintain the initial glucose concentration at 25 g/l under the conditions of aeration volume IVVM (lj!-Eng.7/J2-min.-liquid).
00 g/j! We considered the case of feeding a glucose solution of In the main culture system, in order to produce high concentration of glutamic acid in culture tank 1, the glucose concentration is set at about 25 g/
The glucose supply rate by the culture medium supply pump 6 is adjusted to maintain It at a constant value, but this has conventionally been difficult to automate because it is difficult to directly measure the glucose concentration.
堤松華
実施例２と同一条件でグルタミン酸発酵を行った。但し
、ファジー制御用電子計算機は使用せず、センサーの測
定値に基づいて運転者が培地供給ポンプ６の供給量を判
断し、制御した。結果を第３図に示した。比較例の場合
には、ファジー制御用計算機を用いた本実施例の場合と
比較して、グルコース濃度の変動が大きく、その結果生
成したグルタミン酸の濃度は約半分であった。Glutamic acid fermentation was carried out under the same conditions as in Example 2. However, an electronic computer for fuzzy control was not used, and the driver determined and controlled the supply amount of the culture medium supply pump 6 based on the measured value of the sensor. The results are shown in Figure 3. In the case of the comparative example, the fluctuation in glucose concentration was large compared to the case of the present example using a fuzzy control computer, and as a result, the concentration of glutamic acid produced was about half.
本発明により、従来運転者臼らが培養状態を判定して、
かつそれに基づき制御状態を決定していた運転方法を培
養状態の判定をフェーズ分割により計算機に行わせ、か
つそれに基づき、予め定めておいた制御を実行すること
が可能となり、経験のすくない運転者によっても催実性
の高い制御が可能となり、また勿論自動制御を行うこと
ができるようになった。また、運転者のノウハウをファ
ジープロダクションルールの形で取り込むことで、直接
測定できない項目（例えば、基質濃度等）を一定に保っ
たり、目的生産物を最大にする操作を容易に行うことが
できるようになった。According to the present invention, the conventional driver mortar etc. determines the culture state,
In addition, it is now possible to use a computer to determine the culture state by dividing the operating method into phases, and to execute predetermined control based on this, even by an inexperienced driver. It has also become possible to perform highly effective control and, of course, to perform automatic control. In addition, by incorporating the operator's know-how in the form of fuzzy production rules, it is possible to maintain constant items that cannot be directly measured (e.g., substrate concentration), and to easily perform operations that maximize the desired product. Became.
また、ファジー推論を適用するため、発酵槽における各
培養フェーズ間の制御方法へ移行がスムーズに行え、発
酵槽の運転がスムーズに行える。Furthermore, since fuzzy reasoning is applied, the control method between each culture phase in the fermenter can be smoothly transitioned, and the fermenter can be operated smoothly.
さらに、本方法によりば、運転者が一部運転を行う場合
においても、運転者の判断が容易になる利点がある。Furthermore, this method has the advantage that even when the driver partially drives the vehicle, the driver can easily make decisions.
第１図は本発明の一実施態様を示すフローシート、第２
図は本発明の実施例におけるグルタミン酸発酵の経時変
化、及び制御の状態を示す説明図、第３図は比較例の結
果を示すグラフである。
１・・・培養槽、
２−ファジー制御用計算機（パーソナルコンピュータ）
、
３−・モニター用計算機、
４・・・インタフェース、
５・・・培地（グルコース）タンク、
６−・培地供給ポンプ、
７・・・栄養源（アンモニア）タンク、８・・・栄養源
供給ポンプ、
９−・各種センサー・メーター（ｐＨ１重量、Ｄｏ、温
度等）。
第
図
手続補正書働刻
平成３年１月２８日FIG. 1 is a flow sheet showing one embodiment of the present invention;
The figure is an explanatory diagram showing changes over time in glutamic acid fermentation and the state of control in Examples of the present invention, and FIG. 3 is a graph showing the results of Comparative Examples. 1...Culture tank, 2-Fuzzy control computer (personal computer)
, 3- Monitor computer, 4 Interface, 5 Culture medium (glucose) tank, 6- Culture medium supply pump, 7 Nutrient source (ammonia) tank, 8 Nutrient source supply pump. , 9-・Various sensors/meters (pH1 weight, Do, temperature, etc.). Draft procedure amendment date: January 28, 1991
Claims (1)
と共に、分割した各フェーズに対応する制御方法を定め
ておき、培養時において培養槽から取り込んだ培養槽の
状態を示すデータに基づいてファジープロダクションル
ールにより培養中のフェーズを同定すると共に、同定し
たフェーズに対応する予め定めた制御方法を実行するこ
とを特徴とする発酵槽の制御方法。 ２、フェーズに対応した制御方法を電子計算機によりオ
ンラインで実行する請求項１記載の制御方法。[Claims] 1. The process of culturing in a fermenter is divided into a plurality of phases in advance, and a control method corresponding to each divided phase is determined, and the state of the fermenter taken from the fermenter during cultivation is controlled. 1. A method for controlling a fermenter, characterized in that a phase in culture is identified by a fuzzy production rule based on the data shown, and a predetermined control method corresponding to the identified phase is executed. 2. The control method according to claim 1, wherein the control method corresponding to the phase is executed online by a computer.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2269379A JP2622024B2 (en) | 1990-10-09 | 1990-10-09 | Fermenter control method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2269379A JP2622024B2 (en) | 1990-10-09 | 1990-10-09 | Fermenter control method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| JPH04148672A true JPH04148672A (en) | 1992-05-21 |
| JP2622024B2 JP2622024B2 (en) | 1997-06-18 |
Family
ID=17471588
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2269379A Expired - Fee Related JP2622024B2 (en) | 1990-10-09 | 1990-10-09 | Fermenter control method |
Country Status (1)
| Country | Link |
|---|---|
| JP (1) | JP2622024B2 (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH06292560A (en) * | 1993-04-09 | 1994-10-21 | Toyo Eng Corp | Method for automatically controlling fermentation tank |
| JP2001145480A (en) * | 1999-10-11 | 2001-05-29 | F Hoffmann La Roche Ag | Fermentation continuous process |
| JP2003235544A (en) * | 2002-02-20 | 2003-08-26 | Hitachi Ltd | Method for controlling culture of biological cell, control device for controlling culture apparatus and culture apparatus |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS60203180A (en) * | 1984-02-28 | 1985-10-14 | シタス コーポレイシヨン | Fermentation control apparatus and method |
| JPH048282A (en) * | 1990-04-25 | 1992-01-13 | Fujiwara Jiyouki Sangyo Kk | Method for controlling solid culture apparatus |
| JPH048284A (en) * | 1990-04-25 | 1992-01-13 | Fujiwara Jiyouki Sangyo Kk | Controlling method for solid incubator |
-
1990
- 1990-10-09 JP JP2269379A patent/JP2622024B2/en not_active Expired - Fee Related
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS60203180A (en) * | 1984-02-28 | 1985-10-14 | シタス コーポレイシヨン | Fermentation control apparatus and method |
| JPH048282A (en) * | 1990-04-25 | 1992-01-13 | Fujiwara Jiyouki Sangyo Kk | Method for controlling solid culture apparatus |
| JPH048284A (en) * | 1990-04-25 | 1992-01-13 | Fujiwara Jiyouki Sangyo Kk | Controlling method for solid incubator |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH06292560A (en) * | 1993-04-09 | 1994-10-21 | Toyo Eng Corp | Method for automatically controlling fermentation tank |
| JP2001145480A (en) * | 1999-10-11 | 2001-05-29 | F Hoffmann La Roche Ag | Fermentation continuous process |
| JP2003235544A (en) * | 2002-02-20 | 2003-08-26 | Hitachi Ltd | Method for controlling culture of biological cell, control device for controlling culture apparatus and culture apparatus |
Also Published As
| Publication number | Publication date |
|---|---|
| JP2622024B2 (en) | 1997-06-18 |
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