JPS62135902A - Optimum control method for process - Google Patents
Optimum control method for processInfo
- Publication number
- JPS62135902A JPS62135902A JP27737085A JP27737085A JPS62135902A JP S62135902 A JPS62135902 A JP S62135902A JP 27737085 A JP27737085 A JP 27737085A JP 27737085 A JP27737085 A JP 27737085A JP S62135902 A JPS62135902 A JP S62135902A
- Authority
- JP
- Japan
- Prior art keywords
- process control
- response pattern
- control
- answer
- adjustment
- 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.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 62
- 230000008569 process Effects 0.000 title claims abstract description 29
- 238000004886 process control Methods 0.000 claims abstract description 20
- 239000000463 material Substances 0.000 claims abstract description 6
- 230000004044 response Effects 0.000 claims description 42
- 230000035945 sensitivity Effects 0.000 abstract description 10
- 238000013016 damping Methods 0.000 abstract description 8
- 230000010354 integration Effects 0.000 abstract description 6
- 238000005070 sampling Methods 0.000 abstract 2
- 230000003247 decreasing effect Effects 0.000 abstract 1
- 230000001351 cycling effect Effects 0.000 description 9
- 238000010586 diagram Methods 0.000 description 6
- 238000012369 In process control Methods 0.000 description 2
- 230000007613 environmental effect Effects 0.000 description 2
- 238000010965 in-process control Methods 0.000 description 2
- 239000002994 raw material Substances 0.000 description 2
- 230000009118 appropriate response Effects 0.000 description 1
- FFBHFFJDDLITSX-UHFFFAOYSA-N benzyl N-[2-hydroxy-4-(3-oxomorpholin-4-yl)phenyl]carbamate Chemical compound OC1=C(NC(=O)OCC2=CC=CC=C2)C=CC(=C1)N1CCOCC1=O FFBHFFJDDLITSX-UHFFFAOYSA-N 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000004069 differentiation Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 239000003208 petroleum Substances 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
Landscapes
- Feedback Control In General (AREA)
Abstract
Description
【発明の詳細な説明】
[産業上の利用分野]
本発明は、プロセス制御系におけるプロセスの制御を最
適に行なうための方法に関する。DETAILED DESCRIPTION OF THE INVENTION [Field of Industrial Application] The present invention relates to a method for optimally controlling a process in a process control system.
[従来の技術]
化学工業9石油工業あるいは製紙工業等のプロセス工業
においては、各種プラント等の制御をプロセス制御によ
って行なっている。そしてこの場合、一般には調節計と
して連続形調節計を用い、PID (比例、積分、微分
)動作によって制御を行なっている。一方、PID動作
のパラメータ調整方法としては、まず調節計をP動作に
して、制御系がハンチングを起す限界まで比例感度(ゲ
イン)を高めて行なう限界感度法等の理論的調整方法が
知られている。しかし、これらの方法は、工場で実際に
制御管理を行なうオペレータにとっては非常に難解な方
法であり、はとんど実用化されていない。このため、制
#8管理を行なっている現場においては、必ずしも容易
ではない調節計の調整すなわちプロセス制御における制
御動作の調整を、なんら定まったパラメータにもどづく
ことなく、手動操作により試行錯誤的は行なっている。[Prior Art] In process industries such as the chemical industry, petroleum industry, and paper industry, various plants are controlled by process control. In this case, a continuous type controller is generally used as the controller, and control is performed by PID (proportional, integral, differential) operation. On the other hand, as a parameter adjustment method for PID operation, there are known theoretical adjustment methods such as the limit sensitivity method, in which the controller is first set to P operation and the proportional sensitivity (gain) is increased to the limit at which hunting occurs in the control system. There is. However, these methods are extremely difficult for operators who actually carry out control and management in factories, and are rarely put into practical use. For this reason, in the field where control #8 management is performed, adjusting the controller, that is, adjusting the control operation in process control, which is not necessarily easy, is done manually by trial and error without relying on any fixed parameters. I am doing it.
[解決すべき問題点]
1、述のように、従来のプロセス制御におい−Cは、制
御動作の調整をL動操作により試行錯誤的に行なってい
るため、最適な制御を行なうのに長時間な要することが
しばしばあった。こ−のため、プロセスの制御を行なう
場合、オペレータの勘に頼る部分が多くなるとともに、
これにともなってオペl/−夕の熟練度によって制御結
果に差がつき、さらには未熟練のオペレータの場合には
制御性が非常に悪くなるといった問題点があった。[Problems to be solved] 1. As mentioned above, in conventional process control -C, control operations are adjusted by trial and error using L movement operation, so it takes a long time to perform optimal control. It was often necessary. For this reason, when controlling a process, a lot of parts rely on the intuition of the operator, and
This has led to problems in that control results vary depending on the level of skill of the operator, and furthermore, in the case of an unskilled operator, controllability becomes extremely poor.
なお、ファジィ集合論の概念を応用[7たファジィ論理
を採用してなる情報分析装置(特開昭50−23955
号)、あるいは知識工学の分野における推論方式(特開
昭59−223852号、同H−24844号)などが
知られているが、これらにはプロセスの最適制御を行な
う方法についてはなんら触れられていなかった。Furthermore, an information analysis device (Japanese Unexamined Patent Publication No. 50-23955
223852/1985 and 24844 (Japanese Unexamined Patent Publication No. H-24844), but these do not mention any methods for optimal control of processes. There wasn't.
本発明はL記の間h+点にかんがみてなされたもので、
熟練オベレー、夕の経験ど知識にもとづいて応答パター
ンと++fI+、1との関係なブrシイ調整則表にまと
めておき、調整する場合にはこの表から調整方法を■1
論して、プロセスを最適に制御するようにしたプロセス
の最適制御力法の1ムi供を目的とする。The present invention was made in view of the point h+ during the letter L,
Based on the knowledge of experienced oberets and evening experiences, I summarized the relationship between the response pattern and ++fI+, 1 in a table of adjustment rules, and when making adjustments, I learned the adjustment method from this table.■1
The purpose of the present invention is to provide a method of optimal control force for a process, which is designed to control the process optimally.
L問題点の解決手段1
」−記目的を達成するため本発明のプロセスの最適制御
方法は、あらかじめ、多種類の応答パターンと、これら
多種類の応答パターンに対応した調整方法を含む資料と
を作成しておき、プロセス制御系に外乱等に起因する応
答パター ンが生じた場合、この応答パターンに対応す
る調整方法を前記資料にもとづいて]イ1論し、ごの]
イ1論結果にしたがって前記プロセス制御系の調整を行
なう方ノ人としである。In order to achieve the above objectives, the method for optimally controlling a process of the present invention is based on the following: 1. Solution to Problem 1: In order to achieve the objective described above, the optimal control method for a process of the present invention is based on the following: If a response pattern occurs in the process control system due to a disturbance, etc., the adjustment method corresponding to this response pattern can be determined based on the above materials.
(a) The person who adjusts the process control system according to the results of the theory.
[実施例]
以下、本発明の一実施例について図面を参照しつつ説明
する。[Example] Hereinafter, an example of the present invention will be described with reference to the drawings.
第1図は本実施例のプロセスの最適制御方法を実施する
ための全体構成を示すブロック図である。FIG. 1 is a block diagram showing the overall configuration for implementing the process optimum control method of this embodiment.
第1図において、10はプロセス制御におけるプロセス
であり、所定の原料とエネルギーとをプラントに供給し
、それらに関する温度、流に、圧力、レベル等の環境条
件を定められた値に保つことによって目的の製品を生産
するものである。したがって、均一な製品を生産するた
めには、これらの環境条件および原料や製品の流量ある
いはエネルギー等の埴を最適に制御しなければならない
。この場合の最適制御状態を応答パターンとして示すと
第2図に示すような波形となる。すなわち、ダンピング
比(隣接する正方向の振幅の比二B/A)が1/4であ
り、サイクリング(振幅数の度合)が−周期半程度の応
答パターンでプロセスを制御すると最適な制御となる。In Figure 1, numeral 10 is a process in process control, which aims by supplying predetermined raw materials and energy to the plant and maintaining environmental conditions such as temperature, flow, pressure, and level at predetermined values. of products. Therefore, in order to produce uniform products, these environmental conditions, flow rates of raw materials and products, energy, etc. must be optimally controlled. If the optimal control state in this case is shown as a response pattern, it will have a waveform as shown in FIG. In other words, optimal control is obtained when the damping ratio (ratio of adjacent positive amplitudes 2 B/A) is 1/4 and the process is controlled with a response pattern in which cycling (degree of number of amplitudes) is about -1/2 period. .
第1図において、20はプロセス10を制御するだめの
調節計であり、プロセス10とともにプロセス制御系を
形成している。この調節計20からの信号によって温度
、波用、圧力、レベル等を調整する各操作部(図示ゼず
)が操竹されプロセス制御が行なわれる。本実施例の場
合、操作部の調整をPID動作
Y =Kp(e+ l / T1争f e dt+Ta
−de/dt)Y:操作部 K4.:比例感度
e:偏 差 T1:積分時間
Td:微分時間
によって行ない、ブーヤスをPID制す1するようにし
である。In FIG. 1, 20 is a controller for controlling the process 10, and together with the process 10 forms a process control system. In response to signals from the controller 20, various operating units (not shown) for adjusting temperature, wave control, pressure, level, etc. are operated to perform process control. In the case of this embodiment, the adjustment of the operation unit is performed using PID operation Y = Kp (e + l / T1 conflict f e dt + Ta
-de/dt)Y: Operation section K4. : Proportional sensitivity e: Deviation T1: Integral time Td: Differential time, so that PID controls the booyas.
ここで、応答パターンによるPID、3iJ整法を第3
図によって説明する。外乱笠が入った場合、PIDの設
定イt(、ずなわちI’ I D !Fl+作の強弱に
よって第3図の最1−列おJ:びRk”r“列に示すよ
うな応答パターンとなる。したがって、応答パターンに
応じて次のようしこPIDの行設定(I/iを調整する
ことにより、第3図の中央に>1’;すような最適の応
答パターンとする。Here, PID based on the response pattern, 3iJ adjustment is
This will be explained using figures. When a disturbance occurs, depending on the strength of the PID setting I'I D!Fl+, the response pattern shown in the 1st column and the Rk"r" column in Figure 3 will occur. Therefore, by adjusting the following PID line settings (I/i) according to the response pattern, an optimal response pattern such as >1' in the center of FIG. 3 is obtained.
OP動作(比例動作)
(イ)B/A>1./4のときは、比例感度に、を減少
させる。OP operation (proportional operation) (a) B/A>1. /4, decrease the proportional sensitivity.
(ロ)B/A<1/4のときは、比例感度Kpを増加さ
せる。(b) When B/A<1/4, increase the proportional sensitivity Kp.
(ハ)サイクリングが大きいときは、比例感度にゆを減
少させる。(c) When cycling is large, reduce the distortion in proportional sensitivity.
(ニ)サイクリングが小さいときは、比例感度K。(d) When cycling is small, proportional sensitivity K.
を増加させる。increase.
○ I動作(積分動作)
(イ)B/A>1/4のときは、積分時間Tiを減少さ
せる。○ I operation (integral operation) (a) When B/A>1/4, reduce the integration time Ti.
(口’)B/A<1/4のときは、積分時間Tiを増加
させる。(') When B/A<1/4, the integration time Ti is increased.
(ハ)サイクリングが大きいときは、積分時間Tiを減
少させる。(c) When cycling is large, reduce the integration time Ti.
(ニ)周期が長いときは、積分時間Tiを増加させる。(iv) When the period is long, increase the integration time Ti.
○ D動作(微分動作)
(イ)オフセットがありハンチングしているときは、微
分時間Tdを増加させる。○ D operation (differential operation) (a) When there is an offset and hunting occurs, increase the differential time Td.
(ロ)ハンチングし、短い周期で減衰しているときは、
微分時間Tdを減少させる。(b) When hunting occurs and decays in a short period,
Decrease the differentiation time Td.
第1図において、30は禎:論処理装置であり、入力さ
れた応答パターンに応じて調節計20のPID動作の比
例感度、積分時間および微分時間をどのように設定すれ
ばよいのかを推論して出力する。すなわち、この推論処
理装2t30には、あらかじめ作成された多種類の応答
パターンと、これら多種類の応答パターンに対応する調
整方法を含んだ資料が記憶されており、ある応答パター
ンが入力されると、その応答パターンに対応した調整方
法を推論して出力する。本実施例の場合、上記資料とし
て、オペレータの経験と知識によって作成した第4図に
示すようなファジィ(FtlZZY)調整則表を用いて
いる。In FIG. 1, 30 is a logic processing device that infers how to set the proportional sensitivity, integral time, and differential time of the PID operation of the controller 20 according to the input response pattern. and output it. That is, this inference processing device 2t30 stores materials including many types of response patterns created in advance and adjustment methods corresponding to these various types of response patterns, and when a certain response pattern is input, , infers and outputs an adjustment method corresponding to the response pattern. In the case of this embodiment, a fuzzy (FtlZZY) adjustment rule table as shown in FIG. 4, which was created based on the operator's experience and knowledge, is used as the above-mentioned material.
ここで、ファジィ(F uzziness)とは、多く
の事象に付随している曖昧さの概念をとりあげ、これを
どのように記述し、どのように処理していくかという問
題に対する一つの手法をいう。また、ファジィ調整則表
は、ダンピング比とサイクリングの組合わせに応じてと
るべき処tをマトリックスにしたものである。Here, fuzzyness refers to a method that deals with the problem of how to describe and process the concept of ambiguity that accompanies many phenomena. . Further, the fuzzy adjustment rule table is a matrix of actions t that should be taken depending on the combination of damping ratio and cycling.
次に、本実施例方法を第5図のフローチャートおよび第
6図のファジィルール例によって説明する。Next, the method of this embodiment will be explained using the flowchart of FIG. 5 and the fuzzy rule example of FIG. 6.
プロセス制御が開始された状態において、外乱あるいは
目標値変更等の入力があり、プロセスlOが第6図(1
)におけるような大きなダンピング比とサイクリング比
を有する応答パターンを示したとすると、この応答パタ
ーンをオペレータが推論処理装置30に入力する(第5
図における101の過程)。When the process control is started, there is an input such as a disturbance or a change in the target value, and the process lO changes as shown in Figure 6 (1).
), the operator inputs this response pattern into the inference processing device 30 (fifth
101 process in the figure).
Mr論無処理装置30、応答パターンが入力されると、
ファジィ調整則表にもとづいて応答パターンに対応した
調整方法を見つけ出し、調節計20のPID動作におけ
る比例感度Kpと積分時間T1を大きく減少させるべく
推論する(102の過程)。When the response pattern is input to the Mr-no-processing device 30,
An adjustment method corresponding to the response pattern is found based on the fuzzy adjustment rule table, and inference is made to greatly reduce the proportional sensitivity Kp and integral time T1 in the PID operation of the controller 20 (step 102).
オペレータは、処理装置30の推論結果にもとづいて調
節計20の各設定値を調節して操作量の調節を行なう(
103の過程)。プロセス10は上記操作量に応じた制
御を行ない、第6図(2)におけるようなダンピング比
とサイクリングがともに中ぐらいの大きさである応答パ
ターンを示す(104の過程)6オペレータは、この応
答パターンが最適な応答パターンか否かを判断する(1
05の過程)。The operator adjusts the operation amount by adjusting each set value of the controller 20 based on the inference result of the processing device 30 (
103 process). The process 10 performs control according to the above-mentioned manipulated variables, and shows a response pattern in which both the damping ratio and the cycling are medium in magnitude as shown in FIG. 6(2) (process 104). Determine whether the pattern is the optimal response pattern (1
05 process).
オペレータは、応答パターンが最適でない場合には、再
度その応答パターンを推論処理装置30に入力し、推論
処理装置30より新たに積分時間T1を小さく減少させ
るべく旨のM]、論を得る。そして、この推論結果にも
とづいて調節計20の設定値を調整して操作量の調整を
行なう(101゜102.103の過程)、プロセス1
0は上記操作量に応じた制御を行ない第6図(3)にお
けるようなダンピング比が適当でサイクリングが巾ぐら
いの大きさである応答パターンを示す(104の過程)
。オペレータは、この応答パターンが最適な応答パター
ンか否かを再度判断する(105の過程)。If the response pattern is not optimal, the operator inputs the response pattern into the inference processing device 30 again, and obtains a new argument from the inference processing device 30 to reduce the integration time T1. Then, based on this inference result, the set value of the controller 20 is adjusted to adjust the operation amount (processes 101, 102, and 103), Process 1
0 indicates a response pattern in which control is performed according to the above-mentioned manipulated variable, the damping ratio is appropriate, and the cycling is about the width as shown in FIG. 6 (3) (step 104).
. The operator judges again whether this response pattern is the optimal response pattern (step 105).
オペレータは、応答パターンが最適でない場合には、さ
らに、その応答パターンを1t1]論処理装置30に人
力し、推論処理装置30より新たに積分昨間T1を小さ
く減少させるべく旨の推論を得る。If the response pattern is not optimal, the operator further inputs the response pattern into the logic processing device 30 and obtains a new inference from the inference processing device 30 that the integral interval T1 should be reduced to a smaller value.
そして、この推論結果にもとづいて調節計20の設定値
を調整して操作量の調整を行なう(iot 、102,
103の過程)、、プロセス10は上記操作早、に応じ
た制御を行ない第6図(4)におけるようなダンピング
比およびサイクリングがともに適当な応答パターンを示
す(104の過程)。オペレータは、この応答パターン
が最適な応答パターンか否かを再度判断する( 1.0
5の過程)。その結果、最適な応答パターンであると判
断すると、本方法による応答パターン制御の調整を終了
する。Then, based on this inference result, the set value of the controller 20 is adjusted to adjust the operation amount (iot, 102,
The process 10 performs control according to the above-mentioned operation speed, and both the damping ratio and cycling exhibit appropriate response patterns as shown in FIG. 6(4) (step 104). The operator judges again whether this response pattern is the optimal response pattern (1.0
5). As a result, if it is determined that the response pattern is optimal, the adjustment of response pattern control by this method is completed.
このように、応答パターンのダンピング比とサイクリン
グに応じた調整方法をファジィ調整地表によって推論し
、この推論結果にもとづいてプロセス制御を行なうので
、調整の難しいPID動作によるプロセス制御を迅速に
最適な制御状態とできる。したがって、オペレータの熟
練度にかかわらず、プロセスの安定制御を行なえるとと
もに、オペレータの負111荀軽減することができる。In this way, the damping ratio of the response pattern and the adjustment method according to cycling are inferred using the fuzzy adjustment surface, and process control is performed based on this inference result, so that process control using PID operation, which is difficult to adjust, can be quickly and optimally controlled. state and can. Therefore, regardless of the skill level of the operator, stable control of the process can be performed, and the burden on the operator can be reduced.
なお、本発明は、1.記実施例に限定されるものではな
く、例えば次のような変形例をも含むものである。Note that the present invention has the following features: 1. The present invention is not limited to the embodiments described above, and includes, for example, the following modifications.
■ 応答パターンの推論処理装置30への人力、推論処
理装置30からの■1論結果にもとづく調節計20の調
整、およびプロセスの制御結果を示す応答パターンが最
適か否かの判断の−・部あるいは全部を既存の手段を用
いて自動的に行なうようにしたもの。このようにすると
、本発明方法の自動化を図ることができる。■ Human input from the inference processing device 30 for the response pattern; ■ Adjustment of the controller 20 based on the results of the first theory; and a section for determining whether the response pattern indicating the process control result is optimal. Or, everything can be done automatically using existing means. In this way, the method of the present invention can be automated.
■ 推論処理装置30に演算機能等を付加させ、推論処
理装置30がN1論17た谷動作の設定値の増減を、現
時点におしする設定f〆lよりどれだけ増減させればよ
いかをJj体的な数((iをもって表わすようにしたも
の。■ Add arithmetic functions to the inference processing device 30, and determine how much the inference processing device 30 should increase or decrease the setting value of the N1 theory 17 valley operation from the current setting f〆l. Jj field number ((a number expressed by i.
■ 本発明の方υ、をI’I動作、PD動作によって制
御されるプロヤス制御に適用したもの。■ The method υ of the present invention is applied to Proyas control controlled by I'I operation and PD operation.
■ 資料として、ファジィ調整地表以外の、例えばデシ
ジョン・テーブルを利用したもの。■ Materials other than fuzzy adjustment surfaces, such as decision tables.
「発明の効果1
以」−のように本発明によれば、プロセス制御を試行錯
誤的に行なうのではなく、所定のパラメータにもとづい
て行なうことができるので、容易に最適な制御状態を得
ることができ、プロセスの安定制御が回部となる。According to the present invention, as described in "Effects of the Invention 1 and Below", the process control can be performed based on predetermined parameters rather than by trial and error, so that the optimum control state can be easily obtained. This enables stable control of the process.
第1図は本実施例のプロセスの最適制御方法を実施する
ための全体構成を示すブロック図、第2図は最適応答状
態の応答パターンを示す波形図、第3図は応答パターン
によるPID調整法を示した図、第4図はファジィ調整
地表を示した図、第5図は本発明の実施例方法のフロー
チャートを示した図、第6図は第5図のフローチャート
にもとづ<PID調整のためのファジィルール例を示し
た図である。
IO=プロセス 20:調節計
30:推論処理装置Fig. 1 is a block diagram showing the overall configuration for implementing the optimal process control method of this embodiment, Fig. 2 is a waveform diagram showing the response pattern in the optimum response state, and Fig. 3 is the PID adjustment method using the response pattern. FIG. 4 is a diagram showing the fuzzy adjustment ground surface, FIG. 5 is a diagram showing a flowchart of the embodiment method of the present invention, and FIG. FIG. 2 is a diagram showing an example of fuzzy rules for. IO = Process 20: Controller 30: Inference processing device
Claims (3)
の応答パターンと、これら多種類の応答パターンに対応
した調整方法を含む資料とを作成しておき、プロセス制
御系に外乱等に起因する応答パターンが生じた場合、こ
の応答パターンに対応する調整方法を前記資料にもとづ
いて推論し、この推論結果にしたがって前記プロセス制
御系の調整を行なうことを特徴としたプロセスの最適制
御方法。(1) In the process control method, materials containing many types of response patterns and adjustment methods corresponding to these various types of response patterns are prepared in advance, and the response patterns caused by disturbances etc. in the process control system are prepared in advance. If a response pattern occurs, an adjustment method corresponding to this response pattern is inferred based on the data, and the process control system is adjusted according to the result of this inference.
される制御系であることを特徴とする特許請求の範囲第
1項記載のプロセスの最適制御方法。(2) The method for optimally controlling a process according to claim 1, wherein the process control system is a control system adjusted by PID operation.
ファジイ調整則表であることを特徴とする特許請求の範
囲第1項または第2項記載のプロセスの最適制御方法。(3) The method for optimally controlling a process according to claim 1 or 2, wherein the data is a fuzzy adjustment rule table based on the operator's experience and knowledge.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP27737085A JPS62135902A (en) | 1985-12-09 | 1985-12-09 | Optimum control method for process |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP27737085A JPS62135902A (en) | 1985-12-09 | 1985-12-09 | Optimum control method for process |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| JPS62135902A true JPS62135902A (en) | 1987-06-18 |
Family
ID=17582575
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP27737085A Pending JPS62135902A (en) | 1985-12-09 | 1985-12-09 | Optimum control method for process |
Country Status (1)
| Country | Link |
|---|---|
| JP (1) | JPS62135902A (en) |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS6446101A (en) * | 1987-08-14 | 1989-02-20 | Hitachi Ltd | Pid controller |
| JPH0194401A (en) * | 1987-10-07 | 1989-04-13 | Mitsubishi Electric Corp | Fuzzy operation estimation system for auto-tuning controller |
| JPH01159702A (en) * | 1987-12-17 | 1989-06-22 | Yokogawa Electric Corp | Auto-tuning initial value estimating method |
| JPH0272404A (en) * | 1988-09-08 | 1990-03-12 | Yokogawa Electric Corp | Deciding method for membership function |
| JPH0283703A (en) * | 1988-09-21 | 1990-03-23 | Hitachi Ltd | process control system |
| JPH0293905A (en) * | 1988-09-30 | 1990-04-04 | Omron Tateisi Electron Co | Control device and control method |
| JPH044401A (en) * | 1990-04-20 | 1992-01-08 | Sanyo Electric Co Ltd | Fuzzy control rule auto-tuning device |
| JPH0476702A (en) * | 1990-07-19 | 1992-03-11 | Sanyo Electric Co Ltd | Automatic tuning pid control device |
| JPH0525503U (en) * | 1991-06-11 | 1993-04-02 | 株式会社新潟鐵工所 | Hunting removal device in control device |
| JPH0981206A (en) * | 1995-09-08 | 1997-03-28 | Kayaba Ind Co Ltd | Fuzzy controller |
| JPH09128004A (en) * | 1995-10-30 | 1997-05-16 | Denso Corp | PID control device |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS5465274A (en) * | 1977-11-04 | 1979-05-25 | Hideji Hayashibe | Device of automatically adjusting pid value of regulator |
| JPS59202504A (en) * | 1983-05-02 | 1984-11-16 | Hitachi Ltd | control method |
| JPS60204002A (en) * | 1984-03-28 | 1985-10-15 | Fuji Electric Co Ltd | Mimic fuzzy estimating operating system of fuzzy control device |
-
1985
- 1985-12-09 JP JP27737085A patent/JPS62135902A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS5465274A (en) * | 1977-11-04 | 1979-05-25 | Hideji Hayashibe | Device of automatically adjusting pid value of regulator |
| JPS59202504A (en) * | 1983-05-02 | 1984-11-16 | Hitachi Ltd | control method |
| JPS60204002A (en) * | 1984-03-28 | 1985-10-15 | Fuji Electric Co Ltd | Mimic fuzzy estimating operating system of fuzzy control device |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS6446101A (en) * | 1987-08-14 | 1989-02-20 | Hitachi Ltd | Pid controller |
| JPH0194401A (en) * | 1987-10-07 | 1989-04-13 | Mitsubishi Electric Corp | Fuzzy operation estimation system for auto-tuning controller |
| JPH01159702A (en) * | 1987-12-17 | 1989-06-22 | Yokogawa Electric Corp | Auto-tuning initial value estimating method |
| JPH0272404A (en) * | 1988-09-08 | 1990-03-12 | Yokogawa Electric Corp | Deciding method for membership function |
| JPH0283703A (en) * | 1988-09-21 | 1990-03-23 | Hitachi Ltd | process control system |
| JPH0293905A (en) * | 1988-09-30 | 1990-04-04 | Omron Tateisi Electron Co | Control device and control method |
| JPH044401A (en) * | 1990-04-20 | 1992-01-08 | Sanyo Electric Co Ltd | Fuzzy control rule auto-tuning device |
| JPH0476702A (en) * | 1990-07-19 | 1992-03-11 | Sanyo Electric Co Ltd | Automatic tuning pid control device |
| JPH0525503U (en) * | 1991-06-11 | 1993-04-02 | 株式会社新潟鐵工所 | Hunting removal device in control device |
| JPH0981206A (en) * | 1995-09-08 | 1997-03-28 | Kayaba Ind Co Ltd | Fuzzy controller |
| JPH09128004A (en) * | 1995-10-30 | 1997-05-16 | Denso Corp | PID control device |
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