Method and device for assessing a control loop

Abstract

A method for assessing a control loop. In the method, the control loop is assigned one degree of fulfillment each with respect to at least three quality criteria. The surface area of a polygon having a geometry defined by the degrees of fulfillment is determined. An overall control quality of the control loop is evaluated on the basis of the surface area.

Claims

1. A method for assessing a control loop, comprising the following steps: assigning the control loop one degree of fulfillment each with respect to at least three quality criteria; determining a surface area of a polygon having a geometry defined by the degrees of fulfillment; and evaluating an overall control quality of the control loop based on the determined surface area.

2. The method as recited in claim 1, wherein: the quality criteria relate to oscillations of a controlled variable of the control loop, or the quality criteria relate to a dynamic response behavior of the control loop, or the quality criteria relate to a dynamic control error of the control loop, or the quality criteria relate to a remaining steady-state control deviation of the control loop, or the quality criteria relate to a variance of the controlled variable in a steady-state operating point, or the quality criteria relate to a noise suppression attained by the control loop.

3. The method as recited in claim 1, further comprising the following step: displaying the polygon graphically.

4. The method as recited in claim 1, further comprising the following steps: determining a geometric centroid of the polygon; and deducing a design of the control loop based on the determined geometric centroid.

5. The method as recited in claim 1, further comprising: controlling a process regarding vehicle engineering using the control loop; or controlling a manufacturing process using the control loop.

6. The method as recited in claim 1, further comprising: readjusting parameters of the control loop when the overall control quality drops below a predetermined threshold; or rejecting the controller when the overall control quality drops below the predetermined threshold.

7. The method as recited in claim 6, wherein the threshold is predetermined in such a way that it corresponds to 50% of a largest possible surface area.

8. A non-transitory machine-readable storage medium on which is stored a computer program for assessing a control loop, the computer program, when executed by a computer, causing the computer to perform the following steps: assigning the control loop one degree of fulfillment each with respect to at least three quality criteria; determining a surface area of a polygon having a geometry defined by the degrees of fulfillment; and evaluating an overall control quality of the control loop based on the determined surface area.

9. A device configured to assess a control loop, the device configured to: assign the control loop one degree of fulfillment each with respect to at least three quality criteria; determine a surface area of a polygon having a geometry defined by the degrees of fulfillment; and evaluate an overall control quality of the control loop based on the determined surface area.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

(1) Exemplary embodiments of the present invention are represented in the figures and explained in greater detail below.

(2) FIG. 1 shows a flowchart of a method according to a first specific embodiment of the present invention.

(3) FIG. 2 shows a schematic diagram for the projection of six performance criteria into the two-dimensional plane.

(4) FIG. 3 shows an exemplary polygon for the degrees of fulfillment of 100%, 100%, 50%, 30%, 80% und 70%.

(5) FIG. 4 shows a corresponding representation for two data sets.

(6) FIG. 5 shows a corresponding representation for three data sets.

(7) FIG. 6 shows a corresponding representation for 100 data sets.

(8) FIG. 7 schematically, a control unit according to a second specific embodiment of the present invention.

DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS

(9) FIG. 1 illustrates the basic steps of a method (10) for assessing a control loop. In this case, the control loop is assigned one degree of fulfillment each with respect to at least three quality criteria (process 11). For the purpose of the further description, six criteria are utilized by way of example, it being explicitly emphasized that a higher number of criteria is also possible.

(10) As a first quality criterion (CPI.sub.1), an oscillation index is generated which evaluates the signal power of the oscillating components against the original signal characteristic. Since oscillations have a negative effect on the performance of a system and in addition, serve as indicators for instabilities, their detection and evaluation is especially important.

(11) As second quality criterion (CPI.sub.2), the dynamic response behavior may be considered by use of the time derivatives of setpoint variable {dot over (r)} and controlled variable {dot over (y)}. In control loops with excellent following behavior, the relationship {dot over (r)}≈y{dot over ( )} is true. For the local response deviation, the measure

(12) $\begin{array}{cc}\mathrm{RD}=\frac{\stackrel{.}{y}}{\stackrel{.}{r}}-1& \mathrm{Formula}1\end{array}$
is thus suitable and its absolute mean value mean(|RD|) in the dynamic range ({dot over (r)}≠0).

(13) As a third quality criterion (CPI.sub.3) likewise pertaining to the dynamic response behavior, the sequential error is considered.

(14) The underlying measure is the percentile p.sub.99(|e.sub.dyn|) of the control error e=y−r, which is evaluated in the dynamic range. This indicator describes that limit which the dynamic control error does not exceed over a time proportion of 99%.

(15) The remaining steady-state control deviation is essential for many closed control loops, and is therefore a suitable fourth quality criterion (CPI.sub.4). Specifically, the average value of the control deviation in the steady-state range mean(e.sub.∞) is utilized as assessment criterion. In the ideal case, it always lies at zero.

(16) For constant control quality, a pure evaluation of the average control error is sometimes insufficient. In addition to this, the variance of the controlled variable Var(y) is a useful fifth quality criterion (CPI.sub.5) for evaluating the steady-state accuracy and the ability of the closed control loop to stabilize a steady-state operating point. Assuming a normally distributed output variable (at least in the steady-state operating point), the relationship
σ.sub.y.sup.2=Var(y)  Formula 2
applies for the associated standard deviation, by which, namely, a traceable default of the required variance is made possible.

(17) As a related aspect for evaluating the variance, the noise suppression comes into consideration as a sixth quality criterion (CPI.sub.6). Quantification of the propagation of the noise power in the closed control loop is thereby possible based on a dynamic error budgeting. Since noise signals n are mean-free, the noise power
Var(n)=RMS(n).sup.2.  Formula 3
is obtained. Because of the statistical independence between measurement noise n and the noise component of setpoint variable r, from this follows the noise gain

(18) $\begin{array}{cc}\mathrm{NR}=\frac{\mathrm{Var}\left(y\right)}{\mathrm{Var}\left(n\right)+\mathrm{Var}\left(r\right)}.& \mathrm{Formula}4\end{array}$

(19) These six quality criteria (CPI.sub.1, CPI.sub.2, CPI.sub.3, CPI.sub.4, CPI.sub.5, CPI.sub.6) are projected geometrically in the form of a simple regular polygon (20) onto the two-dimensional plane (FIG. 2). Preferably, the criteria are disposed in this polygon in such a way that similar aspects flow into adjacent criteria, and contrary evaluations have as great a distance from each other as possible. In this context, for each criterion, the origin of the coordinate system represents the lowest possible evaluation, while the maximum distance on the respective ray represents the highest possible evaluation. Thus, the number of vertices and rays—in the present case six—always corresponds to the number of quality criteria considered.

(20) To clarify the interpretation of this polygon, reference is made to FIG. 3. In the example shown, quality criteria (CPI.sub.1, CPI.sub.2, CPI.sub.3, CPI.sub.4, CPI.sub.5, CPI.sub.6) were assigned degrees of fulfillment of 100%, 100%, 50%, 30%, 80% and 70%, respectively. It may be inferred intuitively from the figure that the evaluated closed control loop in the selected scenario exhibits an excellent performance with respect to criteria CPI.sub.1 and CPI.sub.2, as well as a good performance in terms of CPI.sub.5 und CPI.sub.6. The grading of CPI.sub.4 may indicate an inadequate performance, that of CPI.sub.3, a still acceptable performance.

(21) Essential overall assessment criteria may be derived and interpreted on the basis of the form of display selected. To that end, the surface area of polygon (30) is determined (process 12—FIG. 1) and based on it, the overall control quality of the control loop is evaluated (process 13). The maximum achievable total surface area (compare FIG. 2) may thus be considered as reference of an optimal control quality.

(22) Further information with respect to the performance of the overall system is furnished by the centroid vector (SP—FIG. 3). Its magnitude represents a measure for the uniformity of the performance distribution to the individual criteria. The azimuthal position of the centroid vector points ultimately to that criterion which makes the greatest contribution to the overall performance. The performance of the closed control loop is obtained directly through the purposeful placement of similar CPIs.

(23) Corresponding polygons (40, 50, 60) for two, three and 100 test scenarios are shown in FIGS. 4, 5 and 6. If, as in these cases, several data sets are available, then in evaluating them, it is determined which performance ranges are covered how often. In order to promote an intuitive and meaningful interpretation of the entirety of the performance criteria, the total coverage of the respective ranges may be color-coded. This color coding may be backed up by level curves. A color progression from green (degree of fulfillment attained in each data set) through orange (attained in 50 of the data sets) to red (attained at least once) come into consideration as possible color code.

(24) Upon close examination of FIG. 5, the advantages of this assessment method already become apparent. First of all, it may be gathered that the degree of fulfillment of CPI.sub.1 matches in the selected data sets. Secondly, it becomes apparent that the degree of fulfillment of CPI.sub.2 varies the most between the data sets.

(25) As FIG. 6 demonstrates, according to the present invention, the overall performance of a closed control loop may be assessed and displayed clearly and intuitively for a high number of data sets, as well. Especially for checking technical specifications, it is of highest relevance to be able to indicate the minimum quality which is met in each data set evaluated. Furthermore, the gradient of the superimposed polygons might be used as a measure for the sensitivity of the individual performance criteria relative to the test scenarios. For instance, the level curves closely adjoining along the corresponding rays in FIG. 6 illustrate that CPI.sub.1 and CPI.sub.6 have high agreement between the various data sets (high gradient). In contrast, CPI.sub.2 and CPI.sub.5 vary over a substantially larger area (low gradient).

(26) For example, this method (10) may be implemented in software or hardware or in a mixed form of software and hardware, e.g., in a control unit 70, as the schematic representation of FIG. 7 illustrates.

(27) Example embodiments of the present invention are further described in the following paragraphs.

(28) Paragraph 1. A method (10) for assessing a control loop, characterized by the following features:

(29) the control loop is assigned (11) one degree of fulfillment each with respect to at least three quality criteria (CPI.sub.1, CPI.sub.2, CPI.sub.3, CPI.sub.4, CPI.sub.5, CPI.sub.6), the surface area of a polygon (20, 30, 40, 50, 60) having a geometry defined by the degrees of fulfillment is determined (12), and an overall control quality of the control loop is evaluated (13) on the basis of the surface area.
Paragraph 2. The method (10) as recited in Paragraph 1, characterized by at least one of the following features: the quality criteria (CPI.sub.1, CPI.sub.2, CPI.sub.3, CPI.sub.4, CPI.sub.5, CPI.sub.6) relate to oscillations of a controlled variable of the control loop (CPI.sub.1), the quality criteria (CPI.sub.1, CPI.sub.2, CPI.sub.3, CPI.sub.4, CPI.sub.5, CPI.sub.6) relate to a dynamic response behavior of the control loop (CPI.sub.2), the quality criteria (CPI.sub.1, CPI.sub.2, CPI.sub.3, CPI.sub.4, CPI.sub.5, CPI.sub.6) relate to a dynamic control error of the control loop (CPI.sub.3), the quality criteria (CPI.sub.1, CPI.sub.2, CPI.sub.3, CPI.sub.4, CPI.sub.5, CPI.sub.6) relate to a remaining steady-state control deviation of the control loop (CPI.sub.4), the quality criteria (CPI.sub.1, CPI.sub.2, CPI.sub.3, CPI.sub.4, CPI.sub.5, CPI.sub.6) relate to a variance of the controlled variable in a steady-state operating point (CPI.sub.5) or the quality criteria (CPI.sub.1, CPI.sub.2, CPI.sub.3, CPI.sub.4, CPI.sub.5, CPI.sub.6) relate to a noise suppression attained by the control loop (CPI.sub.6).
Paragraph 3. The method (10) as recited in Paragraph 1 or 2, characterized by the following feature: the polygon (20, 30, 40, 50, 60) is displayed graphically.
Paragraph 4. The method (10) as recited in one of Paragraphs 1 through 3, characterized by one of the following features: a geometric centroid (SP) of the polygon (20, 30, 40, 50, 60) is determined and a design of the control loop is deduced on the basis of the centroid (SP).
Paragraph 5. The method as recited in one of Paragraphs 1 through 4, characterized by one of the following features: a process regarding vehicle engineering is controlled with the aid of the control loop or a manufacturing process is controlled with the aid of the control loop.
Paragraph 6. The method (10) as recited in one of Paragraphs 1 through 5, characterized by the following features: if the overall control quality drops below a predetermined threshold, then parameters of the control loop are readjusted or if the overall control quality drops below a predetermined threshold, then the controller is rejected.
Paragraph 7. The method (10) as recited in one of Paragraphs 1 through 6, characterized by the following feature: the threshold is predetermined in such a way that it corresponds to 50 of the largest possible surface area.
Paragraph 8. A computer program which is equipped to carry out the method (10) according to one of Paragraphs 1 through 7.
Paragraph 9. A machine-readable storage medium on which the computer program according to Paragraph 8 is stored.
Paragraph 10. A device (70) which is equipped to carry out the method (10) according to one of Paragraphs 1 through 7.