JPH0221303A - Adaptive controller - Google Patents
Adaptive controllerInfo
- Publication number
- JPH0221303A JPH0221303A JP17068788A JP17068788A JPH0221303A JP H0221303 A JPH0221303 A JP H0221303A JP 17068788 A JP17068788 A JP 17068788A JP 17068788 A JP17068788 A JP 17068788A JP H0221303 A JPH0221303 A JP H0221303A
- Authority
- JP
- Japan
- Prior art keywords
- control
- signal
- adaptive
- constant
- section
- 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
- 230000003044 adaptive effect Effects 0.000 title claims abstract description 27
- 238000000034 method Methods 0.000 claims abstract description 42
- 230000008569 process Effects 0.000 claims abstract description 34
- 238000005070 sampling Methods 0.000 claims abstract description 7
- 238000004364 calculation method Methods 0.000 claims description 10
- 238000004806 packaging method and process Methods 0.000 abstract description 3
- 230000009022 nonlinear effect Effects 0.000 abstract 1
- 230000006978 adaptation Effects 0.000 description 13
- 238000010586 diagram Methods 0.000 description 8
- 238000006243 chemical reaction Methods 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 238000002485 combustion reaction Methods 0.000 description 2
- 230000007274 generation of a signal involved in cell-cell signaling Effects 0.000 description 2
- 238000004886 process control Methods 0.000 description 2
- RZVAJINKPMORJF-UHFFFAOYSA-N Acetaminophen Chemical compound CC(=O)NC1=CC=C(O)C=C1 RZVAJINKPMORJF-UHFFFAOYSA-N 0.000 description 1
- 101100243943 Caenorhabditis elegans pid-5 gene Proteins 0.000 description 1
- 238000000354 decomposition reaction Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 239000000446 fuel Substances 0.000 description 1
- 230000008570 general process Effects 0.000 description 1
Landscapes
- Feedback Control In General (AREA)
Abstract
Description
【発明の詳細な説明】
［発明の目的］
（産業上の利用分野）
本発明は、プロセス状態を監視制御するプロセス計装シ
ステム全般に利用する適応制御装置に係わり、特に所望
とする仕様を満足する適切な制御を実行する適応制御装
置に関する。[Detailed Description of the Invention] [Object of the Invention] (Field of Industrial Application) The present invention relates to an adaptive control device used in general process instrumentation systems that monitor and control process conditions, and particularly relates to an adaptive control device that satisfies desired specifications. The present invention relates to an adaptive control device that performs appropriate control.
（従来の技術）
従来からオートチューニング方式、セルフチューニング
方式等を用いた適応制御あるいは最適制御の技術が数多
く提案されている。例えば特開昭６２−２１０５０３号
公報が上げられる。しかし、これらオートチューニング
方式やセルフチュニング方式は何れもプロセスから出力
する制御量の変化から最適なＰ！またはＰＩＤ制御定数
を算出してＰＩＤｍｆｍ部に設定しプロセスの制御動作
を実行する構成である。(Prior Art) Many adaptive control or optimal control technologies using auto-tuning methods, self-tuning methods, etc. have been proposed. For example, Japanese Patent Application Laid-Open No. 62-210503 can be mentioned. However, both the auto-tuning method and the self-tuning method determine the optimum P! based on the change in the control amount output from the process. Alternatively, the configuration is such that a PID control constant is calculated and set in the PIDmfm unit to execute a process control operation.
（発明が解決しようとする課題）
ところで、この種の制御系においては、例えばセンサ、
操作弁等の入出力装置の精度に関する観測ノイズ、ある
いは周囲環境の変化や操業条件の変化等による負荷の変
動、さらには複数の制御系を有する場合の相互干渉等に
よる外乱が生ずる。(Problem to be solved by the invention) By the way, in this type of control system, for example, sensors,
Disturbances occur due to observation noise related to the accuracy of input/output devices such as operating valves, load fluctuations due to changes in the surrounding environment or operating conditions, and mutual interference when multiple control systems are used.
また、ＰＨプロセス制御系では入出力間に非線形要素を
持っている場合が多い。Furthermore, PH process control systems often have nonlinear elements between input and output.
従って、以上述べたように種々の制御系では外乱や非線
形性を有しているにも拘らず、従来の適応制御装置はオ
ートチューニングあるいはセルフチューニングを実現す
る手段のみに限定されており、上記構成要素から発生す
る外乱や非線形プロセスに対する考慮が充分に払われて
いない。その結果、実際のプラントの実状に適切に対応
することが難しく、プロセス計装システムの稼働後に所
望とする制御仕様を長期にわたって安定に維持すること
ができない。Therefore, as mentioned above, although various control systems have disturbances and nonlinearity, conventional adaptive control devices are limited to only means for realizing auto-tuning or self-tuning, and the above-mentioned configuration is limited. Not enough consideration is given to disturbances and nonlinear processes generated from elements. As a result, it is difficult to appropriately respond to the actual conditions of the plant, and it is not possible to stably maintain desired control specifications over a long period of time after the process instrumentation system is put into operation.
本発明は以上のような実情に鑑みてなされたもので、実
際のプロセスの実状にそくして所望とする制御仕様を充
分に満足させうる適応制御装置を提供することを目的と
する。The present invention has been made in view of the above-mentioned circumstances, and an object of the present invention is to provide an adaptive control device that can fully satisfy desired control specifications in accordance with the actual process conditions.
［発明の構成コ
（課題を解決するための手段）
本発明による適応制御装置は上記目的を達成するために
、目標値とプロセスから出力された制御量との一差信号
を受け、この一差信号を制御定数に基づいて調節演算を
行って操作量を求めて前記プロセスに印加する適応制御
装置において、前記操作量に同定信号を印加して得られ
た信号と前記制御量とをサンプリングし、このサンプリ
ングデータから前記プロセスの動特性を推定し、この動
特性推定モデルを周波数領域に変換して前記制御定数を
取得する適応部をパッケージ化した構成である。[Configuration of the Invention (Means for Solving the Problems) In order to achieve the above object, an adaptive control device according to the present invention receives a difference signal between a target value and a control amount output from a process, and calculates the difference by In an adaptive control device that performs an adjustment operation on a signal based on a control constant to obtain a manipulated variable and apply it to the process, sampling the signal obtained by applying an identification signal to the manipulated variable and the controlled variable; The configuration includes an adaptation unit that estimates the dynamic characteristics of the process from this sampling data, converts this dynamic characteristics estimation model into the frequency domain, and obtains the control constants.
（作用）
従って、本発明は以上のような手段を講じたことにより
、前記ＰＩＤ調節部から出力する操作量に同定信号を印
加して得られた信号と前記制御量とをサンプリングし、
このサンプリングデータから前記プロセスの動特性を推
定し、この動特性推定モデルを周波数領域に変換し例え
ば周波数領域における部分マツチングというアルゴリズ
ムに基づいてプロセスの最適な制御定数を得るので、外
乱を生ずる系や非線形性を持つ系であっても容易に最適
制御を実施でき、かつ、適応部をバッケジ化することに
より簡単に適用可能とするものである。(Function) Therefore, by taking the above-described measures, the present invention samples the control amount and a signal obtained by applying an identification signal to the manipulated variable output from the PID adjustment section,
The dynamic characteristics of the process are estimated from this sampling data, this dynamic characteristics estimation model is converted into the frequency domain, and the optimal control constants for the process are obtained based on an algorithm called partial matching in the frequency domain. Optimum control can be easily carried out even for systems with nonlinearity, and the adaptive part can be easily applied by packaging it into a package.
（実施例）
以下、本発明の実施例について図面を参照して説明する
。第１図は適応制御装置の基本的な構成を示す図であっ
て、温度、圧力、流量等の伝達系等で構成されたプロセ
ス１０と、このプロセス１０を制御するパッケージ化（
ブロック化）可能な適応部１１から成り、この適応部１
１には適応制御を実施するために必要な複数の信号が入
力されている。この信号とは例えば目標値Ｓｖ、制御量
Ｐ■、同定開始信号Ｓ１．ＭＶ初期化要求信号Ｓ２．Ｍ
Ｖ初期値信号Ｓ３およびＭＶ変化量補正値信号８４等が
上げられる。この適応部１１は上記各種の信号を用いて
適応制御を実行し、得られた例えば調節後の制御定数あ
るいは操作ＱＭＶ等の少なくとも１つの信号をプロセス
１０に印加する。(Example) Hereinafter, an example of the present invention will be described with reference to the drawings. FIG. 1 is a diagram showing the basic configuration of an adaptive control device, which includes a process 10 consisting of a transmission system for temperature, pressure, flow rate, etc., and a package (
This adaptation unit 1 consists of an adaptation unit 11 that can be
A plurality of signals necessary for carrying out adaptive control are input to 1. These signals include, for example, the target value Sv, the control amount P■, the identification start signal S1. MV initialization request signal S2. M
The V initial value signal S3, the MV change amount correction value signal 84, etc. are raised. The adaptation unit 11 executes adaptive control using the various signals described above, and applies at least one obtained signal, such as an adjusted control constant or operation QMV, to the process 10.
次に、第２図はプロセス１０を含んだ適応部１１の具体
的構成を示す図である。この適応部１１は、第３図に示
す如くプロセス１０の制御と制御定数（演算定数）の設
計を行う部分であって、具体的には設定値Ｓｖとプロセ
ス１０から出力する制御量ＰＶとの一差信号′をＰＩま
たはＰＩＤ制御定数に基づいてＰＩまたはＰＩＤ調節演
算を行ってプロセス１０に印加する操作ｆｆｉＭＶを取
得するＰＩＤ調節部２１のほか、前記ＰＩまたはＰＩＤ
制御定数の最適値を求めるために、同定信号発生部２２
．同定部２３．変換部２４および設計部２５等が備えら
れている。なお、ＰＩＤ５；！］節部２１には前記ＭＶ
初期化要求信号Ｓ２．ＭＶ初期値信号Ｓ３およびＭＶ変
化量補正値信号８４等が人力される。Next, FIG. 2 is a diagram showing a specific configuration of the adaptation section 11 including the process 10. The adaptation unit 11 is a part that controls the process 10 and designs control constants (calculation constants) as shown in FIG. In addition to the PID adjustment unit 21 that performs PI or PID adjustment calculation on the first difference signal' based on the PI or PID control constant and obtains the operation ffiMV that is applied to the process 10,
In order to find the optimal value of the control constant, the identification signal generator 22
．． Identification part 23. A conversion section 24, a design section 25, and the like are provided. In addition, PID5;! ]The above-mentioned MV is in the joint part 21.
Initialization request signal S2. The MV initial value signal S3, the MV change amount correction value signal 84, etc. are manually input.
この同定信号発生部２２は、前記同定開始信号Ｓ２を受
けてプロセス１０を同定するための同定信号を発生して
前記ＰＩＤ調節部２１の出力に加えて操作量としてプロ
セス１０に印加する。なお、この同定信号は、平均値が
０で、分散が１であるＭ系列信号のほか、通常のステッ
プ信号等が用いられる。前記同定部２３は操作ｉＭＶと
制御量ｐｖとから例えば逐次形最小２乗法を用いてプロ
セス１０の動特性モデルとしてのパルス伝達関数を同定
（推定）する。この同定部２３で得られたパルス伝゛違
関数は変換部２４に送られ、ここで周波数特性モデルと
しての周波数伝達関数に変換した後設計部２５へ送出す
る。この設計部２５では人力された周波数伝達関数から
プロセス１０に最適なＰ演算定数、■演算定数およびＤ
演算定数。The identification signal generation section 22 receives the identification start signal S2, generates an identification signal for identifying the process 10, and applies it to the process 10 as a manipulated variable in addition to the output of the PID adjustment section 21. Note that, in addition to an M-sequence signal having an average value of 0 and a variance of 1, a normal step signal or the like is used as the identification signal. The identification unit 23 identifies (estimates) a pulse transfer function as a dynamic characteristic model of the process 10 from the operation iMV and the control amount pv using, for example, the successive least squares method. The pulse transmission function obtained by the identifying section 23 is sent to the converting section 24, where it is converted into a frequency transfer function as a frequency characteristic model and then sent to the designing section 25. In this design section 25, the optimum P calculation constant for the process 10, ■ calculation constant and D
Arithmetic constant.
つまり制御定数を算出し前記ＰＩＤ調節部２１へ設定す
る機能を持っている。In other words, it has a function of calculating a control constant and setting it to the PID adjustment section 21.
次に、本発明装置の動作を説明する。第４図は本発明装
置の動作フローであって、目標値Ｓｖとプロセス１０の
制御ＱＰｖとに基づいて操作量ＭＶを算出するが（ステ
ップＳ１）、この閉ループ制御を実行しながら適応動作
によってプロセス１０の動特性に応じた最適な制御定数
を設計しくステップＳ２）、以上の動作を繰返し実行し
ながらプロセス１０を適切な状態で制御する。Next, the operation of the device of the present invention will be explained. FIG. 4 shows the operation flow of the device of the present invention, in which the manipulated variable MV is calculated based on the target value Sv and the control QPv of the process 10 (step S1). In step S2), the process 10 is controlled in an appropriate state by repeatedly performing the above operations.
上記適応動作は、第５図に示す如＜ＰＩＤ調節部２１の
出力に同定信号発生部２２から同定信号を加えてプロセ
ス１０に印加し、そのときのプロセス入力端の操作１１
Ｍ Ｖとプロセス出力側の制御量Ｐｖとを同定部２３
でサンプリングする（ステップ５１１）。そこで、この
同定部２３では前記操作ＱＭＶおよび制御ＲＰＶのサン
プリングデータから逐次形赦小２乗法あるいはＵＤ分解
フィルタ等を用いてプラント１０の動特性モデルである
パルス伝達関数Ｇ（ｚ’）を推定する（ステップ５１２
）。The above adaptive operation is performed by adding an identification signal from the identification signal generating section 22 to the output of the PID adjusting section 21 and applying it to the process 10, as shown in FIG.
The identification unit 23 identifies M V and the control amount Pv on the process output side.
(step 511). Therefore, the identification unit 23 estimates the pulse transfer function G(z'), which is a dynamic characteristic model of the plant 10, from the sampling data of the operation QMV and the control RPV using the successive pardon square method or the UD decomposition filter. (Step 512
).
しかる後、以上のようにして求めたパルス伝達関数を変
換部２４に導入する。この変換部２４ではステップＳ１
３において動特性推定モデルであるパルス伝達関数を周
波数領域の表現Ｇ（ｊω）に変換した後に設計部２５に
送出する。この設計部２４においては変換部２４での変
換モデルに対して“周波数領域における部分的モデルマ
ツチングという手法を適用しプラント１０の最適な制御
定数を求める（ステップ５１４）。Thereafter, the pulse transfer function obtained as described above is introduced into the converter 24. In this converter 24, step S1
3, the pulse transfer function, which is a dynamic characteristic estimation model, is converted into a frequency domain expression G(jω) and then sent to the design unit 25. The design unit 24 applies a method called "partial model matching in the frequency domain" to the converted model in the conversion unit 24 to determine optimal control constants for the plant 10 (step 514).
従って、以上のような実施例の構成によれば、前記ＰＩ
Ｄ調節部から出力する操作量に同定信号を印加して得ら
れた信号と前記制御量とをサンプリングし、このサンプ
リングデータから前記プロセスの動特性を推定し、この
動特性推定モデルを周波数領域に変換し例えば周波数領
域における部分マツチングというアルゴリズムに基づい
てプロセスの最適な制御定数を得るので、従来のオート
チューニング方式やセルフチューニング方式と異なり外
乱を生ずる制御系や非線形性を持つ制御系であってもそ
の制御系に充分対処して簡単に最適制御を実施でき、ひ
いては所望とする制御仕様を満足する制御系を実現でき
る。Therefore, according to the configuration of the embodiment as described above, the PI
The signal obtained by applying an identification signal to the manipulated variable output from the D adjustment section and the control variable are sampled, the dynamic characteristics of the process are estimated from this sampling data, and this dynamic characteristic estimation model is converted into the frequency domain. The process is converted to obtain the optimal control constants for the process based on an algorithm called partial matching in the frequency domain, so unlike conventional auto-tuning and self-tuning methods, it is possible to use even control systems that generate disturbances or have non-linearity. Optimum control can be easily carried out by sufficiently dealing with the control system, and a control system that satisfies desired control specifications can be realized.
次に、第６図は適応制御部３０を流量制御系に適用した
例を示す概略構成図であって、この適応制御部３０は流
量計３１と操作弁３２との間に設けられている。この適
応制御部３０は具体的には第７図に示すように制御量Ｐ
ｖを開平演算する開平演算部３３と、前記適応部１１と
、弁開度補正部３４等からなっている。この適応部１１
には開平演算部３３の出力および目標＠Ｓｖのほか、同
定開始信号Ｓｌとしてディジタル信号ＤＩ、が入力され
、ＭＶ初期化要求信号Ｓ２としてディジタル信号Ｄ１２
が人力される。また、ＭＶ初期値Ｓ３には５０９６が設
定され、ＭＹ変化量補正値を用いないのでここでは０．
０％となっている。Next, FIG. 6 is a schematic configuration diagram showing an example in which the adaptive control section 30 is applied to a flow control system, and the adaptive control section 30 is provided between a flow meter 31 and an operating valve 32. Specifically, the adaptive control unit 30 controls the control amount P as shown in FIG.
It consists of a square root calculation unit 33 that performs a square root calculation of v, the adaptation unit 11, a valve opening correction unit 34, and the like. This adaptation part 11
In addition to the output of the square root calculation unit 33 and the target @Sv, a digital signal DI is input as an identification start signal Sl, and a digital signal D12 is input as an MV initialization request signal S2.
is done manually. In addition, the MV initial value S3 is set to 5096, and since the MY change amount correction value is not used, it is set to 0.
It is 0%.
また、本発明装置は第８図はカスケード制御にも適用で
きる。すなわち、このカスケード制御系は、燃料４１を
流量計４２および流量調節弁４３を通して炉４４内に供
給し燃焼動作を行うと共にこの燃焼動作時の炉内温度を
温度検出器４５で検出する。そして、この温度検出器４
５の検出温度を温度制御部４６に導入し、ここで検出温
度と目標値との一差信号を、制御定数を用いてＰＩまた
はＰＩＤ調節演算を行って操作量を得、この操作量を目
標値として流量制御部４７に供給する。この流量制御部
４７では目標値と流量計４３からの検出流量との偏差を
、同様に制御定数を用いてＰＩまたはＰＩＤ調節演算を
実行し、流量調節弁４３を操作する操作量を得る構成で
ある。Furthermore, the device of the present invention can also be applied to cascade control as shown in FIG. That is, this cascade control system supplies fuel 41 into a furnace 44 through a flow meter 42 and a flow control valve 43 to perform a combustion operation, and detects the temperature inside the furnace during this combustion operation with a temperature detector 45. And this temperature sensor 4
The detected temperature of No. 5 is introduced into the temperature control section 46, where the difference signal between the detected temperature and the target value is subjected to PI or PID adjustment calculation using the control constant to obtain the manipulated variable, and this manipulated variable is set as the target. It is supplied as a value to the flow rate control section 47. The flow rate control unit 47 is configured to similarly perform PI or PID adjustment calculations on the deviation between the target value and the detected flow rate from the flow meter 43 using control constants, and obtain the manipulated variable for operating the flow rate control valve 43. be.
しかして、以上のようなカスケード制御系は、本発明装
置との関係では第９図に示すような構成となる。図中、
１１Ａは温度制御部４４に係わる適応部、１１Ｂは流量
制御部４７に係わる適応部である。The cascade control system as described above has a configuration as shown in FIG. 9 in relation to the apparatus of the present invention. In the figure,
11A is an adaptation section related to the temperature control section 44, and 11B is an adaptation section related to the flow rate control section 47.
従って、このカスケード制御系においてもそれぞれの制
御部５６．４７に適応部１１Ａ、ＩＩＢを適用すれば、
それぞれの温度変化、流量変化にも係わらず最適な制御
定数を求めて適応制御を実施することができる。Therefore, in this cascade control system, if the adaptive units 11A and IIB are applied to the respective control units 56 and 47,
Adaptive control can be performed by finding optimal control constants regardless of temperature and flow rate changes.
［発明の効果］
以上詳記したように本発明によれば、各種の制御系にお
けるプロセスの実状にそくして最適な制御定数を設計し
、その制御定数を用いて調節動作を実行するので、所望
とする制ｇａｆｔ様を充分に満足させ得、かつ、適応部
をパッケージ化することにより種々の制御系に容易に適
用できる適応制御装置を提供できる。[Effects of the Invention] As detailed above, according to the present invention, optimal control constants are designed according to the actual process conditions in various control systems, and the control constants are used to execute adjustment operations, so that desired control It is possible to provide an adaptive control device that fully satisfies the requirements of the control system and can be easily applied to various control systems by packaging the adaptive section.
第１図ないし第５図は本発明に係わる適応制御装置の一
実施例を説明するために示したもので、第１図は本発明
装置の基本的な構成図、第２図は第１図に示す適応部の
具体的な構成図、第３図は適応部の基本的な機能図、第
４図は本発明装置の基本動作流れ図、第５図は適応動作
の動作流れ図、第６図および第７図は流量制御系に本発
明装置を適用した図、第８図および第９図はカスケード
制御系に本発明装置を適用した構成図である。
１０・・・プロセス、１１，１．１Ａ、ＩＩＢ・・・適
応部、２１・・・ＰＩＤ調節部、２２・・・同定信号発
生部、２３・・・同定部、２４・・・変換部、２５・・
・設計部、３０・・・適応制御部。
出願人代理人 弁理士 鈴江武彦
ＰＶ Ｓｚ ５４
第１ 図
第３図
第６図
第７図
第８図
第９図1 to 5 are shown to explain an embodiment of an adaptive control device according to the present invention, FIG. 1 is a basic configuration diagram of the device of the present invention, and FIG. 2 is a diagram similar to that shown in FIG. 1. 3 is a basic functional diagram of the adaptation section, FIG. 4 is a basic operation flowchart of the device of the present invention, FIG. 5 is an operation flowchart of the adaptation operation, and FIGS. FIG. 7 is a diagram in which the device of the present invention is applied to a flow rate control system, and FIGS. 8 and 9 are configuration diagrams in which the device of the present invention is applied to a cascade control system. DESCRIPTION OF SYMBOLS 10... Process, 11,1.1A, IIB... Adaptation part, 21... PID adjustment part, 22... Identification signal generation part, 23... Identification part, 24... Conversion part, 25...
- Design department, 30... adaptive control section. Applicant's representative Patent attorney Takehiko Suzue PV Sz 54 Figure 1 Figure 3 Figure 6 Figure 7 Figure 8 Figure 9
Claims (1)
受け、この偏差信号を制御定数に基づいて調節演算を行
って操作量を求めて前記プロセスに印加する適応制御装
置において、 前記操作量に同定信号を印加して得られた信号と前記制
御量とをサンプリングし、このサンプリングデータから
前記プロセスの動特性を推定し、この動特性推定モデル
を周波数領域に変換して前記制御定数を取得する適応部
をパッケージ構成としたことを特徴とする適応制御装置
。[Scope of Claims] Adaptive control that receives a difference signal between a target value and a controlled variable output from a process, performs adjustment calculations on this deviation signal based on a control constant, obtains a manipulated variable, and applies it to the process. In the apparatus, a signal obtained by applying an identification signal to the manipulated variable and the controlled variable are sampled, a dynamic characteristic of the process is estimated from this sampling data, and this dynamic characteristic estimation model is converted into a frequency domain. An adaptive control device characterized in that an adaptive unit for acquiring the control constants is configured as a package.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP17068788A JPH0221303A (en) | 1988-07-08 | 1988-07-08 | Adaptive controller |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP17068788A JPH0221303A (en) | 1988-07-08 | 1988-07-08 | Adaptive controller |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| JPH0221303A true JPH0221303A (en) | 1990-01-24 |
Family
ID=15909532
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP17068788A Pending JPH0221303A (en) | 1988-07-08 | 1988-07-08 | Adaptive controller |
Country Status (1)
| Country | Link |
|---|---|
| JP (1) | JPH0221303A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0704776A1 (en) * | 1994-09-28 | 1996-04-03 | Siemens Aktiengesellschaft | Method for adjusting the parameters of a PI or a PID controller |
| JP2010229968A (en) * | 2009-03-30 | 2010-10-14 | Daihatsu Motor Co Ltd | Control device |
-
1988
- 1988-07-08 JP JP17068788A patent/JPH0221303A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0704776A1 (en) * | 1994-09-28 | 1996-04-03 | Siemens Aktiengesellschaft | Method for adjusting the parameters of a PI or a PID controller |
| JP2010229968A (en) * | 2009-03-30 | 2010-10-14 | Daihatsu Motor Co Ltd | Control device |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JPH11509345A (en) | Optimal Controller Design Method for Multivariable Predictive Control Using Range Control | |
| JP2002049409A (en) | Adaptive inference model in process control system | |
| KR20010051053A (en) | Control Arithmetic Apparatus and method | |
| JPH02186403A (en) | Adaptive controller | |
| EP0709754B1 (en) | Prediction controller | |
| US6353766B1 (en) | Method for generating control parameters from a response signal of a controlled system and system for adaptive setting of a PID controller | |
| JPH0221303A (en) | Adaptive controller | |
| Deng et al. | A novel neural internal model control for multi-input multi-output nonlinear discrete-time processes | |
| Mingxuan et al. | Iterative learning identification and control of discrete time-varying systems | |
| Radhakrishnan et al. | Non-linear control of continuous bioreactors | |
| JP3833479B2 (en) | Control device | |
| JPH07261805A (en) | Automatic adjusting device for proportional plus integral plus derivative control parameter | |
| JPH0434766B2 (en) | ||
| Olfa et al. | Implementation of remote control for time delay systems based on adaptive and internal model approaches | |
| JPH06318102A (en) | Sensor compensating device | |
| JP2752230B2 (en) | 2-DOF control device | |
| JPH06222809A (en) | Adaptive controller | |
| KR100584620B1 (en) | Method and apparatus for auto-tuning a controller of paper feeding system in a printer | |
| JPH03100704A (en) | Process controller | |
| Koshkouei et al. | Adaptive backstepping control | |
| JPS6148163B2 (en) | ||
| JPS629405A (en) | Process controller | |
| JPH04100116A (en) | Learning control system adopting correction of speed command | |
| JP2980409B2 (en) | Operating end characteristic correction method and process control device | |
| RU2079868C1 (en) | Device for control of objects with inertial delay |