JPS60218290A - Automatic operation system of crane - Google Patents

Abstract

(57) [Summary] This bulletin contains application data before electronic filing, so abstract data is not recorded.

Description

[Detailed Description of the Invention] [Field of Application of the Invention] The present invention is applicable to automatic operation systems of cranes used for cargo handling work in ports, etc. This is related to an automatic lane driving system that can stop the swinging of luggage.

[Background of the invention]

In this specification, the crane refers to a crane that handles cargo by moving a trolley 1 in a horizontal plane and raising and lowering a lobe 2 hanging from the trolley 1, as shown schematically in FIG.

Furthermore, the purpose of automatic operation of the crane shown as a model in Figure 1 is (1) to move the trolley 1 to the target point in the shortest possible time (2) to stop the swinging of the load 3 at the target point. is to control the crane. In principle, this steady rest control is
When the trolley approaches the target point, the luggage 3 is made to swing in the direction of travel relative to the trolley 1, and the trolley catches up with the luggage 3, which has swung almost to the target point and is in a nearly stationary state, and stops. This can be achieved by "let it happen."

Conventional crane automatic operation systems, for example, as shown in FIG. Ta, Kanai; “Optimum Crane Operation Method Focusing on the Maximum Speed of the Trolley,” Transactions of the Society of Instrument and Control Engineers, VAT, 25, A 6, (197
9)).

The speed pattern is calculated so that the swing angle of the rope system becomes zero at the end time.

This crane automatic operation system subtracts the speed pattern of the trolley that can achieve the above control in advance using a geometric method or an optimal control method, and prepares it as shown in Figure 2. is configured to perform speed pattern tracking. The biggest problem with this method is that the control system is in an open loop with respect to rope swing rti. Therefore, in the automatic operation method described above, various errors such as initial swing, gust of wind, control system delay time, etc. This has a serious problem in that it is not possible to correct the deflection angle of the rope if such factors exist.

[Purpose of the invention]

The present invention was developed in view of the above circumstances, and its purpose is to provide a
The purpose is to provide an automatic lane driving system that can stop the swinging of cargo with high precision.

[Summary of the invention]

The gist of the present invention is to perform fuzzy (puz
zy) Control commands are determined by inference to enable highly accurate crane automatic operation.

[Embodiments of the invention]

Hereinafter, first, a first embodiment of the present invention will be described in detail based on the drawings.

Crane Guinamitics can be divided into two types: (1) rope system and (2) trolley system. By analyzing each system, the conditions for performing steady rest control can be determined as follows.

(1) When the acceleration U of the rope system trolley is constant, if the swing angle of the rope system is θ and the angular velocity is δ, then the transition (trajectory) is δ/
Phase plane of ω-θ (ω=7g/l.

t is the length of the rope) and a counterclockwise circular locus centered on the point u/g on the θ axis (g is the acceleration of gravity).

Become.

Therefore, in order to stop the swinging of the rope system, that is, to bring the above-mentioned transient to the origin, the final step is to control it with a positive acceleration U in the second quadrant.・・・・・・・・・・・・・・・Control with negative acceleration U in the ■4th quadrant of Fig. 3(a)・・・・・・・・・・・・・・・・・・. . . One of the controls shown in (2) in FIG. 3(a) will be performed.

However, even after decelerating from a certain trolley speed (u<0),
If the vibration is also stopped, the transition of (2) above will occur, so below we will consider only the case (2) above.

As shown in FIG. 3(b), at time t, the transition area is in the fourth position.
Assuming that it is in the quadrant, the acceleration u : ufl+ for guiding this (δ0/ω, θ0) to the origin is as follows. Also, the time T(1) to reach the origin is T(return
:(!- ω.

As described above, if the rope runs for a time T(1) at an acceleration of u(1), the swinging of the rope system can be stopped after T(1).

(2) Trolley system If the position of the trolley is X, the speed is X, and the target position is XM, in order to stop it at the target position with constant acceleration, T (2I = snoring 1 yen - lower sho; If the trolley is run for T(2) time with an acceleration of uf21, the trolley can be stopped at the target position after Tf21.

Therefore, from (1) and (2), "at the final stage" of crane operation, uf'l = u f21 , 'l'+
If the crane is run so that "It = II" (ml), a fixed position stop and steady rest can be achieved at the end.However, there is a solution that satisfies the above two goals at the same time.

The existence of TI cannot generally be guaranteed. Therefore, the acceleration manual force u (u4=u'') and time T (T-
+T*) with respect to TI becomes a cause of control error at the end time.

Below, the error of the rope system (residual runout) and the error of the trolley system (
stop position error). However, it is assumed that the trolley stops after one hour, that is, x -1-u T = 0.

(1,1 rope system (see Figure 4) ψ' = ωT b/ω η = tan-', - θ--, then at the terminal time t t = t + T,
θ(tr)=-+γcos(ψ'+η) However, the residual runout Jl is expressed as.

(21 trolley system Stop position error J (21 is becomes.

FIG. 5 is a block diagram of the automatic crane operation control device according to this embodiment. In the figure, 5 indicates the momentary state of the crane, ie, position and speed.

A sensor for measuring the deflection angle, deflection angular velocity, etc. of the lobe; 6 is a processor that uses the measurement data from the sensor 5 to calculate a control command to the actuator 7 as described below; 8 is a crane; Shows the main body.

The above fil, (terminating error J width determined by 2 + J 12)
can be said to be the predicted value of the evaluation index value at the terminal time when the control human power U is commanded in the current state (x, x, θ, b). The control command is determined by fuzzy (ii'uzzy) inference using the predicted evaluation value. The inference rules are: fl) If it can be stopped accurately with the current acceleration, and if the shaking seems to stop successfully, then Thel holds the current value.

(211f If you can stop accurately by increasing the acceleration a little, and if the shaking seems to stop correctly, (10) 'pbeH Increase the acceleration a little.

Use something like.

Evaluation indicators such as ``successfully stopped'' and ``accurate steady rest'', which are necessary for determining a control command (puzzy inference) using the above-mentioned control law, are defined using membership functions. An example is shown in FIG.

Figure 6(a) shows the membership functions μGG and μGA of the fuzzy variables GG (stops well) and GA (stops correctly), and the same figure (b)
) shows the definition of the membership function μ[lG, μ8m of the fuzzy variables 8G (well rested) and 8A (correctly rested).

Using the above parameters, the inference rule is, for example, (11) fllI f G is GA an(I S is
S.A.

'l' heHΔu is O, 0 (211f G is GA and S is 8A
.

'l'hel Δu is →-0,1(311f G
is GA and 8 is SA.

TheHΔu is −0,1 (n) And rose.

Now, the i"uzzy result created by the a.d combination of part 11f" of the first rule is expressed as Pl""GA A S A (△ indicates an intersection set). Considering the values of G and S when the control correction of ΔU is performed at time t, P t (t) = (GA AG (J l”, t
))△(8AA8 (J(ll, t))...
......(3) The Fuzzy set is obtained. Here, r+(t)=
sup , up+(t) ++m++(71)(12
) is the evaluation value of the first rule above.

Hereinafter, similarly, r (t
) = max r I(t) ..." (51, determine the most reliable control law.

FIG. 7 shows the procedure of the above processing.

In the above example, the swing angle θ of the rope system and its angular velocity θ were used, but if angular velocity data cannot be obtained, #(11)-(θ(1g)-〇(tg-tH/ (tx
It may be determined by calculation such as tK-t).

Next, a second embodiment of the present invention will be described. In this example, instead of the inference rule shown on page 11, i@
Let the inference rule Ri be I f i (X=A+x, X=A Ix,
θ=Ats) Then y−gl(X, X, θ) =P+o+PtxX+P+xX+Ptaθ. Here, Atx+AIx, At# are X, X.

The fuzzy set that determines the range of θ, fI is the inference rule R
A logical function that expresses the antecedent of +, and gI is X, X, θ
Here, (13) is a linear function.

Assuming that there are n inference rules in total, the inference value is determined by // indicates a truth value.

Note that the parameter P of the linear function g+ is determined as follows using the least squares method from actual control data and the like.

First, data of observed values (X, At this time, assuming that m pieces of data are obtained, this is expressed as. Also, at this time, the above inference rule (14
) Let the truth value Wl be w I=/ f t (x vc=A Ix, X [
C: A IX, θvc = A Iθ)/, and create.

From the above, each parameter of y=Pto+P+xX+PtxX+Puθ is estimated by the weighted least squares method.

According to this embodiment, the parameters of "fuzzy control item 1" used in crane control can be identified from the control performed by the operator and the good results of computer simulation, etc., so it is resistant to changes in conditions, accurate and lane automatic control is possible. This has the effect of making it possible to drive.

It goes without saying that the function g that determines y from X, X, and θ should not be limited to the linear function shown in the above embodiment (15).

〔Effect of the invention〕

As described above, according to the present invention, control commands are determined by fuzzy reasoning based on measurement data of trolley position and speed, rope deflection angle, and angular velocity in a crane automatic operation system, so that initial deflection and Even in the presence of disturbances such as gusts of wind, it is possible to stop the swing of the load with high precision, and it has the remarkable effect of realizing an automatic lane driving system.

[Brief explanation of drawings]

Figure 1 is a diagram showing a model crane, Figure 2 is a diagram showing the speed pattern in the conventional crane automatic operation system, Figure 3 is a phase diagram showing the principle of steady rest, and Figure 4 is a residual digging prediction calculation. 5 is a block diagram showing a crane automatic operation control device which is an embodiment of the present invention, FIG. 6 is a diagram showing the shape of the membership function, and FIG. 7 is a flowchart showing the processing procedure. It is. 1... Trolley, 2... Robe, 3... Luggage, 5
... Sen (16) Su, 6... Processor, 7... Actuator, 8
...The crane body. (17) Fig. 5 Z Fig. ρ [C starvation] M7 Fig.

Claims (1)

[Claims] 1. A device for measuring crane state quantities such as the position and speed of the trolley, the swing angle of a rope hanging from the trolley, and the swing angular velocity, an actuator for adjusting the speed of the trolley, and control given to the actuator. An automatic crane operation system, characterized in that the crane is equipped with a control mechanism for calculating and determining commands, and the control command to be given to the speed adjusting actuator of the trolley is determined by fuzzy reasoning based on the output of the measuring device. 2. The fuzzy inference format is characterized in that control results based on control commands determined based on the output of the measuring device are evaluated from time to time as fuzzy quantities, and the best control command is determined from among them. Claim 1:
Crane automatic operation method described in section. 3. The automatic crane operation system according to claim 1, wherein the fuzzy inference format is a function of a consequent of an inference rule based on the output of the measuring device. 4. The automatic crane operation system according to claim 3, wherein the function is a linear function.