JPS6197717A - Supply system of optimum control data for program control system - Google Patents

Abstract

PURPOSE:To obtain an optimum amount of forecast data and to reduce a data transmission quantity or file capacity, by varying the interval of the forecast data for program tracking in relation to a local error. CONSTITUTION:An allowable error calculation part 8 calculates both the upper and lower limit levels epsilon1 and epsilon2 serving as the threshold value for variation of the time dividing width under the worst and best conditions, i.e., at the minimum and maximum angles of elevation respectively. A local error calculation part 9 calculates a local error DELTAf which is produced when the forecast data (f) is produced with the given time dividing width DELTAt. A time dividing width deciding part 10 compares the error DELTAf with errors epsilon1 and epsilon2 respectively to define DELTAt DELTAt/2 with DELTAf>epsilon1. While DELTAt 2DELTAt is defined with DELTAf<epsilon2 for change of the time dividing width. Thus the width DELTAt is decided so that the error DELTAf is always kept within an allowable error, that is, epsilon1>DELTAf>epsilon2 is always satisfied. However the maximum and minimum values DELTAt0 and DELTAtmin are included.

Description

[Detailed Description of the Invention] [Industrial Application Field] The present invention provides a system for transmitting a series of control data programmed in chronological order from a central station to a remote station control device, such as a control system for an artificial satellite tracking antenna. The present invention relates to a program control system for sequentially supplying control data to a remote station, and in particular to an optimal control data supply method that minimizes the amount of control data supplied by adjusting the data interval so that the interpolation error at a remote station is within a certain tolerance range. .

[Conventional technology]

A program tracking method is one of the control methods for tracking an artificial satellite carrying a probe, such as Landsaft, from an observation station on the ground using an antenna. This method creates forecast data at fixed times regarding the azimuth, elevation angle, etc. of a tracking antenna placed on the ground, programs this data, and sequentially drives the antenna based on this forecast day and evening. It is. : Fig. 2 schematically shows such an artificial satellite tracking system, where l is an artificial satellite, 2 is a ground station, 3 is an arethena, 4 is an observation center, and 5 is a transmission line.
.

The communication antenna 3 and the observation center 4 are geographically separated, and the observation center 4 transmits a series of forecast data for driving the antenna 3 described above to the antenna 3 via the transmission line 5. . In Ante 3, an interpolation method is applied to the series of received forecast data to interpolate intermediate values, and the antenna drive system is controlled to continuously adjust the azimuth, elevation, etc. of the antenna to target values. In this case, the forecast data interval is fixed, for example, at a 60 second interval.

FIG. 3 shows an example of a forecast data string and interpolation regarding the elevation angle supplied to the antenna. t7-i Lm
, jn+1 is the forecast time, d, , -1, dn, d.

, 1 indicates a forecast data string, and rr+-1, r, , indicates a linearly interpolated result value. Note that 5fi-Sn represents the true elevation angle value of the artificial satellite. The error between the linearly interpolated result value and the true elevation angle value is called an interpolation error or local error.

[Problem that the invention seeks to solve]

Antenna tracking errors are largely due to interpolation errors, so to improve tracking accuracy it is necessary to shorten the data interval of forecast data.

However, this poses a problem in that the amount of forecast data supplied to the antenna via the transmission line increases.

[Means for Solving the Problem] The present invention provides that the interpolation error in a controlled object in a program control system generally varies depending on the control position.For example, in the case of the antenna that tracks the artificial satellite described above, the rate of change near the horizon is Since the rate of change is smaller than the rate of change near the maximum elevation angle, when performing linear interpolation with a constant data interval,
Focusing on the fact that the interpolation error is larger near the zenith than near the horizon, to improve accuracy, instead of uniformly shortening the data interval of forecast data, we change the data interval in relation to the amount of interpolation error. , it is possible to suppress the increase in the amount of forecast data to be supplied as a whole.

The configuration of the present invention thereby enables the program control system to change the time step size between successive control data, so that the local error caused by interpolation between the control data falls within a predetermined tolerance range. It is characterized by determining continuously.

[Action of the invention]

Forecast data in program control system Time t1 control function E/! (t), El (
The time differential l1(t) of t) can be given by an analytical formula. If this is considered as an initial value problem for a -order ordinary differential equation, the local error can be calculated by applying the known predictor/corrector method (PC method). Therefore, sequential data intervals may be determined so that this local error does not exceed predetermined upper and lower tolerance values. However, in practice, the data interval does not need to be varied continuously, but can be varied in two steps or in other appropriate steps. Furthermore, a low-order numerical solution to the differential equation of formula +1) above is sufficient. This is Ef
This is because the purpose is not to obtain the value of (1), but to obtain a guideline for changing the data interval based on the local error.

(Example of the invention) The details of the present invention will be explained below based on examples.

FIG. 1 is a schematic diagram of an artificial satellite tracking system that is an embodiment of the present invention. In the figure, 3 is an antenna, 4 is an observation center, 5 is a transmission line, 6 is a tracking control device, 7 is a forecast data creation unit, 8 is a tolerance calculation unit, 9 is a local error calculation unit, and 10 is a time step size determination unit. 11 and 12 are transmission control units, 13 is an antenna drive device, 14 is an azimuth drive motor, and 15 is an elevation drive motor. Note that the transmission and processing system for the information received by the antenna 3 from the artificial satellite is not directly related to the description of the present invention, and is therefore omitted for the sake of brevity.

The observation center 4 uses the tracking control device 6 to create a series of forecast data specified at the optimum data interval, that is, the time step size, and transmits the forecast data to the antenna drive device via the transmission control section 11, transmission line 5, and transmission control section 12. 13. The antenna driving device 13 performs linear interpolation between individual forecast data for the series of supplied forecast data, and controls the azimuth drive motor 14 and the elevation drive motor 15 to move the antenna 3 toward the target artificial satellite. Let it track you.

The forecast data creation unit 7 calculates the azimuth and elevation angle of the antenna 3 with respect to the target artificial satellite at an arbitrary time, and creates forecast data f.

The tolerance calculation unit 8 calculates the upper limit value ε1 and the lower limit value ε2 of the tolerance error, which are dark values for changing the time step size, under the worst and best tracking conditions, that is, in this embodiment, at the minimum elevation angle and the maximum elevation angle. .

The local error calculation unit 9 calculates a local error Δf that occurs when forecast data f is created with a given time step width Δt.

The time step size determining unit 10 compares the calculated local error Δf with the tolerance 81 and ε8, and if Δf>8°, Δf
is - Δt/2, and in the case of Δf<ε2, Δt+−
The time step width is changed as 2Δt. This ensures that the local error is always within the tolerance, i.e. ε, 〉Δ
The time step width Δt is determined so that f>ε2. However, it has a maximum value Δt0 and a minimum value Δt,1.

Next, the process of creating forecast data having an optimal time step size in the tracking control device 6 of FIG. 1 will be described in accordance with the flowcharts of FIGS. 4 and 5.

The symbols used are as follows, and their contents are illustrated diagrammatically in FIG.

t: Time.

El (t): Tracking angle wa (elevation angle).

t, °: Tracking start time.

tII Tortoise X: Time when the elevation angle El (t) becomes maximum.

tll: Time of the nth forecast data.

Δt: Time step width.

Δt0: Initial value of time step width, maximum value.

Δ’+mia: Minimum allowable time step width.

f (t) :=El (t) f, :f (t,)=Effi (t,)f”
a:=f (tn) +f (t1%-+)
−Δt −(218ax :=f (L−me)
Cocoon +r(tea,)・Δ! Fraud
...(3) f8゜:=r (to
) +f (to) ・Ato −(4)Δ f
:=lf ゎ − f , 1 1
...ku5) ε1:=Δ
f,,X=l 8ax' (t+amx +Δ
t, tll) l...(6)ε2:Δf
o = l f'. f (to +Δt6) 1
(7) FIG. 4 is a flowchart of the initial processing.

(2) First, tracking start time t0, and time t when the elevation angle El becomes maximum. ax, the initial value Δt0 of the time step width, and the allowable minimum value Δt, 87, are initially manually input to the tracking control device 6.

(2) The forecast data creation unit 7 calculates the elevation angle value f (t□
8+Δt, , , ) and f (to +Δto) are respectively determined.

■The tolerance calculation unit 8 calculates (L maX+Δjm=n)
And (to + Δto), the linear approximation value in (3
), calculated using equation (4).

The above equations (6) and (7) are used to calculate the upper limit value ε and the lower limit value ε2 of the allowable error.

(2) For the processing from the 9th time onward, set f, -0, ¥21-1←0, and Δ to Δt0 in each part of 7.9.10.

Next, the subsequent processing will be explained using the flow shown in FIG.

■The forecast data creation unit 7 generates r,...? , create.

(2) If fn-+=0, it means that the forecast data does not change, so 0 is immediately executed.

However, if fll-1≠0, the following steps (1) and (2) are executed.

(2), (2)0 The local error detection unit 9 calculates t using the above-mentioned equation (2). Find the linear approximation value f*7 in , and further calculate the above (
5) Calculate the local error Δf using the formula.

01 The time step size determining unit IO compares the local error Δf with the upper limit value ε1 of the allowable error, and if Δf>ε, executes [phase], and if Δf≦ε1, executes [phase].

[phase], Δr>ε, the time step width Δt
shorten by half.

(2) As long as @, Δt is larger than the allowable minimum value Δt, , 7, the shortened Δt is used, and if Δt is less than Δtvntn, the shortened Δt is suppressed to Δt=ΔtMin. Then execute @.

@0Save f,,,i,,for the next calculation.

If Δf≦ε in [phase] and ■, Δf is further compared with the lower limit value ε2 of the allowable error, and if Δf≧ε2, execute 0, and if Δf<ε2, execute [phase].

The fact that ∆f x ε2 in ■ and ■ means that the time step size ∆
This means that even if [ is made longer, the local error can be kept within the allowable error range, so the amount of information is reduced by changing Δt=2Δt.

[Phase], ■, Changed Δt to initial value (maximum value) Δt0
If Δt≦Δt0, it can be left as is, but Δ
If t>Δt0, 0 is executed while suppressing Δ1=Δt0.

[Phase], output the determined time step width Δt.

As described above, the time step width Δt is calculated as ΔtIllA7
It is switched in multiple stages within the range ≦Δt≦Δt0, and the minimum necessary and most efficient time step width is determined within the tolerance, and forecast data is created.

〔Effect of the invention〕

As described above, according to the present invention, the data interval of forecast data for program tracking is made possible in relation to local errors, thereby making it possible to optimize the amount of forecast data.
Data transmission amount and file capacity can be reduced.

[Brief explanation of the drawing]

Fig. 1 is a block diagram of one embodiment of the present invention, Fig. 2 is a schematic diagram of an artificial satellite tracking system, Fig. 3 is an explanatory diagram of forecast data and interpolation, and Figs. 4 and 5 are diagrams of the present embodiment. FIG. 6, a flowchart of the forecast data creation process, is an explanatory diagram of symbols used in this embodiment. In the figure, 3 is an antenna, 4 is an observation center, 5 is a transmission line,
6 is a tracking control device, 7 is a forecast data creation section, 8 is a tolerance calculation section, 9 is a local error calculation section, 10 is a time step width determination section, 11.12 is a transmission control section, 13 is an antenna drive device, 14 is an azimuth drive motor, and ]5 is an elevation drive motor.

Claims (1)

[Claims] In a program control system, the time step size between sequential control data can be changed, and the local error caused by interpolation between the control data is continuously determined so that it falls within a predetermined tolerance range. Optimal control data supply method.