JPH0411194A - Method of controlling direction of tunnel robot - Google Patents

Method of controlling direction of tunnel robot

Info

Publication number
JPH0411194A
JPH0411194A JP10885690A JP10885690A JPH0411194A JP H0411194 A JPH0411194 A JP H0411194A JP 10885690 A JP10885690 A JP 10885690A JP 10885690 A JP10885690 A JP 10885690A JP H0411194 A JPH0411194 A JP H0411194A
Authority
JP
Japan
Prior art keywords
robot
deviation
pitching angle
gain
angle
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
Application number
JP10885690A
Other languages
Japanese (ja)
Inventor
Shinichi Aoshima
伸一 青島
Koki Takeda
武田 幸喜
Tetsuo Yabuta
藪田 哲郎
Yoshihiro Harada
美浩 原田
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Nippon Telegraph and Telephone Corp
Original Assignee
Nippon Telegraph and Telephone Corp
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Nippon Telegraph and Telephone Corp filed Critical Nippon Telegraph and Telephone Corp
Priority to JP10885690A priority Critical patent/JPH0411194A/en
Publication of JPH0411194A publication Critical patent/JPH0411194A/en
Pending legal-status Critical Current

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Abstract

PURPOSE:To enhance the control ability by selecting an optimum gain in a feed-back control rule in which values by multiplying a positional deviation and a pitching angle deviation of a robot body by gains are used for the next input head angle. CONSTITUTION:A positional deviation of a robot from a planned line is multiple by a positional deviation feed-back gain kp while a pitching angle deviation DELTAthetap(K) is multiple by a pitching angle deviation feed-back gain ka so as to obtain input head angle from a control rule expression in order to lead a pitching angle variation DELTAthetap(K) for a direction correcting value from which a robot position Y(k) and a robot pitching angle thetap(K) are calculated for the correction of the direction. Further, the gain ka is selected in a range of 6.5 to 9.6 (dimensionless), and the ratio Ka/Kp between the gains Ka, kp is selected in a range of 32 to 140(mm/deg) in order to carry out feed-back control. Thereby it is possible to perform satisfactory control.

Description

【発明の詳細な説明】 〔産業上の利用分野〕 本発明は無排土式で押し込み推進させながらロボット先
端のヘッド角を制御し、方向修正を行なう小口径トンネ
ルロボットの方向制御方法に関するものである。
[Detailed Description of the Invention] [Field of Industrial Application] The present invention relates to a direction control method for a small-diameter tunnel robot that corrects the direction by controlling the head angle of the robot tip while pushing and propelling the robot in an unremoved manner. be.

〔従来の技術〕[Conventional technology]

第10図にトンネルロボットのシステム構成を示す。本
システムはヘッド角修正機能を持つトンネルロボット本
体1、埋設管2、埋設管を押し込む押管装置3、油圧装
置4、操作盤5よりなる。
Figure 10 shows the system configuration of the tunnel robot. This system consists of a tunnel robot main body 1 with a head angle correction function, a buried pipe 2, a push pipe device 3 for pushing the buried pipe, a hydraulic device 4, and an operation panel 5.

埋設管2は押管装置3により油圧で1木ずつ押し込まれ
る。このとき、オペレータはヘッド角を逐次修正し、計
画線に沿うように方向制御を行なう。
The buried pipe 2 is pushed in one by one using hydraulic pressure by the pushing pipe device 3. At this time, the operator sequentially corrects the head angle and performs direction control so as to follow the planned line.

この方向制御は現状ではオペレータの経験と知識に鯨っ
ている。
This directional control currently depends on the experience and knowledge of the operator.

第11図で本トンネルロボットのヘッド角とピッチング
角について定義する。第12図は実際の施工データから
求めたヘッド角−ピッチング角変化量特性である。ピッ
チング角変化量はヘッド角が同じでもかなりばらついて
おり、ヘッド角が異なると、そのばらつきかたもちがう
。このため、ある角度、方向修正したいと思っても、ど
の程度ヘッド角を修正すればよいかわからず、方向制御
が非常に困難であった。
Figure 11 defines the head angle and pitching angle of this tunnel robot. FIG. 12 shows head angle-pitting angle variation characteristics obtained from actual construction data. The amount of change in pitching angle varies considerably even when the head angle is the same, and the variation varies depending on the head angle. For this reason, even if one wishes to correct a certain angle or direction, one does not know how much the head angle should be corrected, making direction control extremely difficult.

[発明が解決しようとする課題] 本発明は上記の事情に鑑みてなされたもので、従来オペ
レータの経験と勘によって行なわれていた小口径トンネ
ルロボットの方向制御を自動化する制御方法を提供する
ことを目的とする。
[Problems to be Solved by the Invention] The present invention has been made in view of the above circumstances, and it is an object of the present invention to provide a control method that automates the direction control of a small-diameter tunnel robot, which has conventionally been performed based on the operator's experience and intuition. With the goal.

〔課題を解決するための手段と作用〕[Means and actions to solve the problem]

本発明は上記課題を解決するために、計画線に対するロ
ボット本体の位置偏差とピッチング角度偏差にゲインを
かけたものを次の人力ヘッド角とし、その位置偏差フィ
ードバックゲインkpとピッチング角度偏差kaとの比
k a / k p (mm/deg)が32〜140
 (mm/deg)であり、ピッチング角度偏差フィー
ドバックゲインka(無次元)が6.5〜9.2(無次
元)である、フィードバック制御則を用いた方向制御方
法である。
In order to solve the above-mentioned problems, the present invention takes the following manual head angle as the product of the positional deviation and pitching angle deviation of the robot body with respect to the planned line and the pitching angle deviation, and then calculates the positional deviation feedback gain kp and the pitching angle deviation ka. Ratio k a / k p (mm/deg) is 32 to 140
(mm/deg) and a pitching angle deviation feedback gain ka (dimensionless) of 6.5 to 9.2 (dimensionless).

従来技術との差異は、本発明の方向制御方法を使うこと
により、従来オペレータの経験と勘によって行なわれて
いた小口径トンネルロボットの方向制御を自動化するこ
とができる点である。
The difference from the prior art is that by using the direction control method of the present invention, it is possible to automate the direction control of a small diameter tunnel robot, which was conventionally performed based on the operator's experience and intuition.

〔実施例] 本実施例では、ロボット本体の位置偏差とピッチング角
偏差に、それぞれ、比例ゲインka、kpをかけたもの
を次の入力ヘッド角とするフィードバック制御則を用い
た方向制御のシュミレーションと評価を行ない、最適な
比例ゲインka、kpを求めている。
[Example] In this example, we will simulate directional control using a feedback control law in which the next input head angle is obtained by multiplying the position deviation and pitching angle deviation of the robot body by proportional gains ka and kp, respectively. Evaluation is performed to find the optimal proportional gains ka and kp.

方向修正に関するシュミレータはダイナミックモデル[
式(1)]とロボットのピッチング角と位置の算出式[
式(2)、 (3)] によって構成される。方向制御
のシミュレーションは以下のように行なう。
The simulator for direction correction is a dynamic model [
Equation (1)] and the calculation formula for the pitching angle and position of the robot [
Equations (2) and (3)] The direction control simulation is performed as follows.

まず、式(4)の制御則によりヘッド角を求める。次に
そのヘッド角を式(1)のダイナミックモデルに代入し
、方向修正量を計算する。そして、式(2)、 (3)
も用い、ロボットのピッチング角と位置を計算する。
First, the head angle is determined using the control law of equation (4). Next, the head angle is substituted into the dynamic model of equation (1) to calculate the amount of direction correction. And equations (2), (3)
is also used to calculate the pitching angle and position of the robot.

本システムのダイナミックモデルは方向修正角がヘット
角とロボットの姿勢を近似的に表わすピッチング角変化
量の時系列項および確率分布項の和で表わせる確率モデ
ルで表した。パラメータalllb、、は最小2乗法に
よって推定される。
The dynamic model of this system is expressed as a stochastic model in which the direction correction angle can be expressed as the sum of a time series term and a probability distribution term of pitching angle changes that approximately represent the head angle and robot posture. The parameters alllb, , are estimated by the least squares method.

このモデル同定は特願平1−277200号に詳述され
ている。
This model identification is detailed in Japanese Patent Application No. 1-277200.

シミュレータ Δθ、 (k) ・a +Δθp(k−1)+−十a、
Δθ、(k−n)   (1)+boθh(k)+b1
θh(k−1)+−+b、lθ、、(k−n)+e(k
)θp(k)・θ、(k−1)+Δθp(k)    
         (2)Y(k)=Y(k−1)+L
sin(θ、(k))           (3)制
御則 θ、(k)・Kp(Yd(k)−Y(k−1))+に言
θd(k)−θp(k−1))(4)第2圀で各パラメ
ータを定義する。下方の軌道が計画線であり、上方の軌
道がロボットの軌道である。ストロークkにおける計画
線の位置をYd(k)、計画線の傾きをθ、1(k) 
、ロボットの位置をY(k)、ロボットのピッチング角
をθp(k)、ピッチング角変化量をΔθp(k)、1
ストロークの長さをLとおく。また、式(2)のダイナ
ミックモデルにおいて、e (k)は残差、nはモデル
の次数である。ブロック線図を第1図に示す。
Simulator Δθ, (k) ・a +Δθp(k-1)+-10a,
Δθ, (k-n) (1)+boθh(k)+b1
θh(k-1)+-+b, lθ,,(k-n)+e(k
)θp(k)・θ, (k-1)+Δθp(k)
(2) Y(k)=Y(k-1)+L
sin(θ, (k)) (3) The control law θ, (k)・Kp(Yd(k)−Y(k−1))+ is expressed as θd(k)−θp(k−1))(4 ) Define each parameter in the second domain. The lower trajectory is the planned line, and the upper trajectory is the robot's trajectory. The position of the design line at stroke k is Yd(k), the slope of the design line is θ, 1(k)
, the position of the robot is Y(k), the pitching angle of the robot is θp(k), the amount of change in pitching angle is Δθp(k), 1
Let the length of the stroke be L. Furthermore, in the dynamic model of equation (2), e (k) is the residual and n is the order of the model. A block diagram is shown in FIG.

以下に、B地区におけるパラメータ推定値を用いたシミ
ュレーション結果を示す。計画線はすべて初期位置、角
度ともOの水平線とした。
Below, simulation results using parameter estimates for District B are shown. All planned lines were horizontal lines with initial positions and angles of O.

第3図は式(])でka=0としたもので、角度偏差量
を使わない場合のシミュレーション結果である。ただし
、kp=o、olとし、残差e (K)は平均値Ode
g、標準偏差0.13degの正規分布で近似した。初
期位置、角度はそれぞれ、500mm、Odegとした
。図を見てわかるように発散してしまう。第4図は位置
、角度偏差量の両方を使った場合で、kp=0.01、
ka=2とした。その他の条件は第3図の場合と同じで
ある。角度偏差量をいれるときれいに収束することがわ
かる。この結果より、位置偏差のフィードバックゲイン
に比較して、角度偏差のフィードバックゲインを大きく
すると方向制御効果が大きくなることがわかる。
FIG. 3 shows the simulation results when ka=0 is used in equation (]) and the angular deviation amount is not used. However, kp=o, ol, and the residual e (K) is the average value Ode
g, approximated by a normal distribution with a standard deviation of 0.13 deg. The initial position and angle were set to 500 mm and Odeg, respectively. As you can see from the diagram, it diverges. Figure 4 shows the case where both position and angular deviation are used, kp=0.01,
ka=2. Other conditions are the same as in the case of FIG. It can be seen that when the angular deviation amount is included, it converges neatly. From this result, it can be seen that the direction control effect becomes larger when the feedback gain of the angular deviation is increased compared to the feedback gain of the positional deviation.

そこで、次に、位置偏差のフィードバックゲインに比較
して、どの程度、角度偏差のフィードバックゲインを大
きくすればよいのかを3周べた。
Therefore, next, we investigated three times how much the angular deviation feedback gain should be increased compared to the positional deviation feedback gain.

この方法をB地区のデータを使って説明する。This method will be explained using data from District B.

第5図にk p = 0.01 (deg/mm)とし
た時の、ka=過渡応答の偏差絶対値積分値特性を示す
。この図より、偏差絶対値積分値が最小になるkaを求
めることができる。この場合、k a = 1.5とな
る。
FIG. 5 shows the deviation absolute value integral value characteristic of ka=transient response when k p =0.01 (deg/mm). From this diagram, it is possible to find ka at which the absolute deviation integral value becomes the minimum. In this case, k a = 1.5.

次に、上記と同様に、kpを0.01から10 (de
g/mm)まで変化させて偏差絶対値積分値が最小にな
るkaを求める。これらの結果を用いると、第6図に示
すkp−最小偏差絶対値積分値特性が求まる。この図よ
り偏差絶対値積分値が最小になるkpは0.07 (d
eg/mm)となり、そのときのkaはkpが0、07
 (deg/+p+m)のときのka=過渡応答の偏差
絶対値積分値特性により7.8(無次元)と求まる。
Next, similarly to the above, kp is set from 0.01 to 10 (de
g/mm) to find the ka that minimizes the absolute deviation integral value. Using these results, the kp-minimum deviation absolute value integral value characteristic shown in FIG. 6 can be determined. From this figure, kp at which the deviation absolute value integral value is minimum is 0.07 (d
eg/mm), and at that time ka and kp are 0,07
When (deg/+p+m), ka=7.8 (dimensionless) is determined from the deviation absolute value integral value characteristic of the transient response.

従って、B地区に関する最適ゲインはkp=0.07(
deg/mm)、ka=7.8(無次元)となり、最適
ゲイン比はk a / k p (mm/deg) =
 111 (mm/deg)となる。第7図にこの最適
ka、kpを使った場合の方向制御シミュレーション結
果を示す。初期位置は500nu++、計画線は位置が
0の水平線とした。
Therefore, the optimal gain for district B is kp=0.07 (
deg/mm), ka = 7.8 (dimensionless), and the optimal gain ratio is ka / k p (mm/deg) =
111 (mm/deg). FIG. 7 shows the results of a directional control simulation using these optimal ka and kp. The initial position was 500 nu++, and the design line was a horizontal line at position 0.

図に示されるように、良好な制御が行なわれていること
がわかる。
As shown in the figure, it can be seen that good control is being performed.

上記と同様にして、N値の異なる各地区における最適ゲ
インkp、ka及び、最適ゲイン比ka/kpを求めた
。これを表1に示す。
In the same manner as above, the optimal gains kp and ka and the optimal gain ratio ka/kp in each district with different N values were determined. This is shown in Table 1.

二の表により、計画線に対するロボット本体の位置偏差
とピッチング角度偏差にゲインをかけたものを次の入力
ヘッド角とするフィードハック制御則を用いた方向制御
法を本トンネルロボットに適用する場合、実際のN値を
考慮して、ピッチング角度偏差フィードバックゲインk
aは6.5〜9.6(無次元)、位置偏差フィードバッ
クゲインkpとの比k a / k p (mm/de
g)はほぼ32〜140(mm/deg)の範囲で選択
すればよいことがわかる。
According to Table 2, when applying the direction control method using the feed hack control law to this tunnel robot, in which the next input head angle is the product of the position deviation of the robot body with respect to the planned line and the pitching angle deviation multiplied by a gain, Considering the actual N value, pitching angle deviation feedback gain k
a is 6.5 to 9.6 (dimensionless), and the ratio to position error feedback gain kp is k a / k p (mm/de
It can be seen that g) may be selected within the range of approximately 32 to 140 (mm/deg).

また、表1の値を使ってN値とkp、kaとの関係を図
示すると、それぞれ、第8図、第9図のような関係にな
る。白丸は表1で示した値である。
Further, when the relationships between the N value and kp and ka are illustrated using the values in Table 1, the relationships are as shown in FIGS. 8 and 9, respectively. The white circles are the values shown in Table 1.

ただし、N=5の場合は複数であるので平均値を示して
いる。また、N値がO〜2のような場合は平均値とした
。この場合はN値は1となる。実線は近似曲線である。
However, in the case of N=5, since there are multiple numbers, the average value is shown. Moreover, when the N value was O to 2, it was taken as an average value. In this case, the N value is 1. The solid line is an approximate curve.

この近似曲線式をそれぞれ、式(5)、 (6)に示す
These approximate curve equations are shown in equations (5) and (6), respectively.

kp= 0.054+t、38xto−’x N5(5
)ka−7,13十〇、0O113N’       
     (6)従って、実際のkp、kaを求める場
合は、施エする場所のN値に対応するka、kpを近似
式で求め、その値を使って方向制御すればよい。
kp=0.054+t, 38xto-'x N5(5
)ka-7,1310,0O113N'
(6) Therefore, when calculating the actual kp and ka, it is sufficient to calculate the ka and kp corresponding to the N value of the place to be treated using an approximate formula, and use the values to control the direction.

〔発明の効果〕〔Effect of the invention〕

以上説明したように本発明によれば、計画線に対するロ
ボット本体の位置偏差とピッチング角度偏差にゲインを
かけたものを次の入力ヘッド角とするフィードバック制
御則において、ピッチング角度偏差フィードバックゲイ
ンkaを6.5〜9.6(無次元)、位置偏差フィード
バックゲインkpとの比k a / k p (mm/
deg)を32〜140 (mm/deg)の範囲で選
択してフィードバック制御を行なうことにより良好な制
御が行え、従来オペレータの経験と知識に軒って制御し
ていた方向制御を自動化できる効果がある。
As explained above, according to the present invention, in the feedback control law in which the next input head angle is obtained by multiplying the positional deviation of the robot body with respect to the planned line and the pitching angle deviation by a gain, the pitching angle deviation feedback gain ka is set to 6. .5 to 9.6 (dimensionless), ratio of position error feedback gain kp (mm/
By selecting the angle (deg) in the range of 32 to 140 (mm/deg) and performing feedback control, good control can be performed, and the effect is that directional control, which was conventionally controlled based on the operator's experience and knowledge, can be automated. be.

【図面の簡単な説明】[Brief explanation of drawings]

第1図は本発明の実施例に係るブロック線図、第2図は
本発明の実施例に係る各パラメータの定義を示す説明図
、第3図は本発明の実施例に係る位置偏差のみで角度偏
差量を使わない場合のシミュレーション結果を示す特性
図、第4図は本発明の実施例に係る位置偏差と角度偏差
量両方を使った場合のシミュレーション結果を示す特性
図、第5図は本発明の実施例に係るka−過渡応答の偏
差絶対値積分値特性図、第6図は本発明の実施例に係る
kp−最小偏差絶対値積分値特性図、第7図は本発明の
実施例に係る方向制御シミュレーション結果を示す特性
図、第8図は本発明の実施例に係るN値とkpとの関係
を示す特性図、第9図は本発明の実施例に係るN値とk
aとの関係を示す特性図、第10図は従来のトンネルロ
ボットのシステム構成図、第11図は従来のヘッド角と
ピッチング角変化量の定義を示す説明図、第12図は従
来のヘッド角とピッチング角変化量特性図である。 1・・・ロボット本体、2・・・埋設管、3・・・押管
装置、4・・・油圧装置、5・・・操作盤。
FIG. 1 is a block diagram according to an embodiment of the present invention, FIG. 2 is an explanatory diagram showing the definition of each parameter according to an embodiment of the present invention, and FIG. 3 is a diagram showing only positional deviation according to an embodiment of the present invention. FIG. 4 is a characteristic diagram showing the simulation results when the angular deviation amount is not used. FIG. 4 is a characteristic diagram showing the simulation results when both the positional deviation and angular deviation amount according to the embodiment of the present invention are used. ka-transient response deviation absolute value integral value characteristic diagram according to the embodiment of the invention, FIG. 6 is a kp-minimum deviation absolute value integral value characteristic diagram according to the embodiment of the present invention, and FIG. 7 is an embodiment of the present invention. FIG. 8 is a characteristic diagram showing the relationship between the N value and kp according to the embodiment of the present invention, and FIG. 9 is a characteristic diagram showing the relationship between the N value and kp according to the embodiment of the present invention.
Figure 10 is a system configuration diagram of a conventional tunnel robot, Figure 11 is an explanatory diagram showing the definition of the conventional head angle and pitching angle variation, and Figure 12 is the conventional head angle. and pitching angle variation characteristic diagram. 1... Robot body, 2... Buried pipe, 3... Push pipe device, 4... Hydraulic device, 5... Operation panel.

Claims (2)

【特許請求の範囲】[Claims] (1)無排土式で押し込み推進させながらロボット先端
のヘッド角を制御し、方向修正を行なう小口径トンネル
ロボットに関する、計画線に対するロボット本体の位置
偏差とピッチング角度偏差にゲインをかけたものを次の
入力ヘッド角とするフィードバック制御則において、位
置偏差フィードバックゲインkp(deg/mm)とピ
ッチング角度偏差フィードバックゲインka(無次元)
との比ka/kp(mm/deg)が32〜140(m
m/deg)であることを特徴とするトンネルロボット
の方向制御方法。
(1) For a small-diameter tunnel robot that corrects direction by controlling the head angle of the robot tip while pushing and propelling the robot without soil removal, calculate the gain multiplied by the position deviation and pitching angle deviation of the robot body with respect to the planned line. In the feedback control law with the following input head angle, position deviation feedback gain kp (deg/mm) and pitching angle deviation feedback gain ka (dimensionless)
The ratio ka/kp (mm/deg) is 32 to 140 (m
m/deg).
(2)ピッチング角度偏差フィードバックゲインka(
無次元)が6.5〜9.6(無次元)であることを特徴
とする請求項1記載のトンネルロボットの方向制御方法
(2) Pitching angle deviation feedback gain ka (
2. The direction control method for a tunnel robot according to claim 1, wherein the distance (dimensionless) is 6.5 to 9.6 (dimensionless).
JP10885690A 1990-04-26 1990-04-26 Method of controlling direction of tunnel robot Pending JPH0411194A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
JP10885690A JPH0411194A (en) 1990-04-26 1990-04-26 Method of controlling direction of tunnel robot

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
JP10885690A JPH0411194A (en) 1990-04-26 1990-04-26 Method of controlling direction of tunnel robot

Publications (1)

Publication Number Publication Date
JPH0411194A true JPH0411194A (en) 1992-01-16

Family

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Family Applications (1)

Application Number Title Priority Date Filing Date
JP10885690A Pending JPH0411194A (en) 1990-04-26 1990-04-26 Method of controlling direction of tunnel robot

Country Status (1)

Country Link
JP (1) JPH0411194A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7677365B2 (en) 2005-07-26 2010-03-16 Shimano Inc. Bicycle rim brake assembly

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7677365B2 (en) 2005-07-26 2010-03-16 Shimano Inc. Bicycle rim brake assembly

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