CN104298111B - Fuzzy control method for kiln thermal parameter control system - Google Patents

Abstract

The invention discloses a fuzzy control method for a kiln thermal parameter control system. According to the fuzzy control method, a fuzzy control rule list is partitioned according to the control characteristics of the system, and different sections are described through different analytical expressions. The fuzzy control method is used for controlling various kiln thermal parameters, has the good control effect and is simple in operation and quite high in application and popularization value.

Description

A kind of fuzzy control method for kiln thermal parameter control system

Technical field

The invention belongs to thermal process automation field, it is used for kiln thermal parameter control system more particularly to a kind of Fuzzy control method.

Background technology

In the controls, fuzzy control (f.c.) table reflects the description various factors that people summarize out in practice Between the fuzzy language of mutual relation control experience, because its be not required to mathematical models it is adaptable to linear, non-linear, when Change and the control of delay system, thus be widely used.But f.c. table also has the place of deficiency, is such as not easy to self-regulated Whole, self-correction, the shortcomings of occasionally there are output stage value and fluctuate.In order to solve these shortcomings, professor Wang Peizhuan proposes to be solved with f.c. Substituting f.c. table, f.c. analytic expression optimization is convenient, but simple analytic expression hardly possible can describe all complicated control objects for analysis formula.

Content of the invention

The present invention is intended to provide a kind of fuzzy control method that is simple, being effectively used for kiln thermal parameter control system.

For reaching above-mentioned purpose, the technical scheme is that a kind of fuzzy for kiln thermal parameter control system Control method is it is characterised in that comprise the following steps:

1) according to different controll plants, subregion is carried out to fuzzy control rule table；

2) to different sections, represented using different fuzzy control analytic expressions；The formula of fuzzy control analytic expression is: $u_{\mathrm{si}}=\frac{a}{3}(q_i-p_i)e^2-q_{i}e+\frac{a}{3}(q_i-p_i)\mathrm{ec}+(1-q_i)c$

Wherein, e is deviation, and c is change of error, and i is subregion, p_i、q_iFor intelligent Self-adjustment Factor, obtained by adjusting and optimizing To different intelligent Self-adjustment Factor p, q values, thus realizing different fuzzy control analytic expressions, p_i、q_iValue be definite value parameter, When e is negative, a=-1, otherwise, a=1.

Further, the temperature control to furnace heating-up band, chilling band, using typically positive and negative 6 grades of discretizations, positive and negative 3 Shelves obfuscation, according to the feature of input deviation fuzzy quantity e and change of error fuzzy quantity c in fuzzy control rule table r, Fuzzy Control Rule list r processed is divided into four rectangular areas.

Further divided it is characterised in that control to wind flow in kiln according to deviation e scope, Fuzzy control rule table r is divided into three strip regions according to deviation e size.

Further it is characterised in that control to deviation e, the impact of change of error c and high precision, according to deviation e and Fuzzy control rule table r is divided into three annular regions by the value of change of error c.

The beneficial effect of the inventive method is: this fuzzy control method, according to the control characteristic of system, fuzzy control is advised Then table subregion, is described with different analytical expressions to different sections, and the method is used for the control of various kiln thermal parameters System, has good control effect, and the method is simple to operate, have very high application value.

Brief description

Fig. 1 is the flow chart of the fuzzy control method that the present invention is used for kiln thermal parameter control system；

Fig. 2 is that the present invention is used for the rectangular sub-area of fuzzy control method of kiln thermal parameter control system and system exports Response curve；

Fig. 3 is the bar shaped subregion of the fuzzy control method that the present invention is used for kiln thermal parameter control system by shelves level value Dividing regions schematic diagram.

Specific embodiment

For making the object, technical solutions and advantages of the present invention of greater clarity, with reference to specific embodiment and join According to accompanying drawing, the present invention is described in more detail.It should be understood that these descriptions are simply exemplary, and it is not intended to limit this Bright scope.Additionally, in the following description, eliminate the description to known features and technology, to avoid unnecessarily obscuring this The concept of invention.

As shown in figure 1, for the fuzzy control method of kiln thermal parameter control system, step includes: 1) according to difference Controll plant, subregion is carried out to fuzzy control rule table；

2) to different sections, represented using different fuzzy control analytic expressions；

The basic fuzzy control analytic expression is taken to be:

U=- ＜ α e+ (1- α) c ＞ (1)

In formula: α ∈ [0,1], α are weighted value.It is a kind of single factor analytic expression, after α determines, deviation e and deviation Change c weight shared in the controlling also determines that, formula (1) approximate plane in u, e, c said three-dimensional body, and the control of reality Object often has different working condition in different phase, therefore carries out subregion according to features, with different fuzzy controls parsing Formula.In addition, different control objects has different control characteristics, its partition method is also different, and several typical cases point are described below Area's method.

1.f.c rectangular area partitioning

According to typically positive and negative 6 grades of discretizations, positive and negative 3 grades (i.e. large, medium and small shelves) obfuscations, advised according to fuzzy control Then in table r input deviation e fuzzy quantity and change of error fuzzy quantity c feature, r is divided into four rectangular areas, as shown in table 1:

Table 1 f.c rule list r rectangular sub-area

As in Fig. 1, r is control system set-point, y (k) is the output valve of controlled device.

Definition: secondary deviation: the e that samples to obtain of kth_k=-(r-y_k) (2)

Change of error: c_k=e_k-e_k-1(3)

Divide four regions: area: e ＜ 0 and c≤0 according to positive e, c negative sign；Area: e >=0 and c >=0；Area: e >=0 and c ＜ 0；Area: e ＜ 0 and c < 0.

To a specific system, " section " is different, controls rule to answer difference, introduces the intelligence tune automatically changing upper lower limit value Section factor p, q (upper lower limit value that i.e. α changes automatically) is adjusted.

Order $a_i=\frac{\left|e\right|}{3}(p_i-q_i)+q_i---\left(4\right)$

In formula: p ＞ q, p+q >=1, then fuzzy control analytic expression (1) be changed into:

$u_{\mathrm{si}}=-<(\frac{\left|e\right|}{3}(p_i-q_i)+q_i)*e+(1-\frac{\left|e\right|}{3}(p_i-q_i)-q_i)*c>$

In formula: i=,,.

Above formula removes and rounds symbol, is after arrangement:

$u_{\mathrm{si}}=\frac{a}{3}(q_i-p_i)e^2-q_{i}e+\frac{a}{3}(q_i-p_i)\mathrm{ec}+(1-q_i)c---\left(6\right)$

In formula: e is deviation, c is change of error, and i is subregion, when e is negative, a=-1, otherwise, a=1.Obvious formula (6) For quadratic form curved surface.p_i、q_iValue be definite value parameter, different intelligent Self-adjustment Factor p, q values are obtained by adjusting and optimizing, from And realize different fuzzy control analytic expressions, thus reach the purpose of temperature optimization control.

This subregion is in kiln control it is adaptable to the control of the general thermal parameter requiring, such as furnace heating-up band, chilling The temperature control of band.

2.f.c bar shaped partitioning

Bar shaped divides and is divided according to deviation e scope, is divided according to deviation size in fuzzy control rule table Become three strip regions, as shown in table 2.This subregion is applied to the control target not required to change of error sensitivity, such as The control of wind flow in kiln.

Table 2 f.c rule list bar shaped subregion

Dividing with reference to Fig. 2 of these three areas is as follows:

Area's feature: 3 grades of | e | ＜, c are any grade of value；

＜ -3 grade of area's feature: -6≤e, c are any grade of value；

Area's feature: 3 ＜ e≤6 grade, c is any grade of value.

Strip subregion does not consider the impact of change of error, and refers to that change of error does not play a leading role to controlling.As Kiln airduct nearly exit vortex is big, fluctuation is big, the stability that obviously can increase control system insensitive to its suddenly change and Reliability.

Additionally, bar shaped subregion determines the control weight of analytic expression large deviations and change of error according to deviation size, according to Different index requests takes different analytic expression forms, typically takes p, q 0.8～0.9 about preferably.This subregion can be used It is in random suddenly change frequently in control object in some change of errors, the control such as to pneumatic system etc., is having of row The method of effect.

3.f.c annular subregion

In some control systems, whenever all should consider deviation in control process, change of error can not be ignored again Impact, and control accuracy requirement is very high, then can be using annular partitioning it is simply that according to inclined to the division of control rule table Control table is divided into three annular regions by the value of difference and change of error, as shown in table 3:

Table 3 f.c rule list annular subregion

Trizonal division is as follows:

Area: | e |≤3 grade, and | c |≤3 grade.

＜ -3 grade of area: -5≤e, and | c |≤5 grade；Or 5 grades of 3≤e ＜, and | c |≤5 grade.

＜ -5 grade of area: -6≤e, c arbitrary number of level；Or 5≤e≤6 grade, c arbitrary number of level；Or ＜ -5 grade of -6≤c, e arbitrary number of level；Or 5≤c≤6 grade, e arbitrary number of level

The corresponding analytic expression in area in annular subregion is actually and adopts in the case of deviation and change of error are all less Control strategy, Fuzzy self- turning pid parameter controller can be used, or f.c and pid mixing control, to improve control accuracy, to disappear Except static difference.

With: u_c1=f_pid(e,c,k_p,k_i,k_d)

Or: u_e=β u_f.c+(1-β)u_pid, β ∈ [0,1].

Wherein e represents deviation, and c represents change of error, and kp is scale parameter, is mainly used for quick regulation error；Ki is Integral parameter, is mainly used for adjusting steady state time；Kd is mainly used for forecast error trend for differential parameter, revises by mistake in advance Difference.β is weight coefficient, u_f.cFor fuzzy control quantity, u_pidFor pid controlled quentity controlled variable.

, twoth area, it is possible to use the advantage of fast response time in fuzzy control, using the fuzzy parsing of different p, q values Formula controls, as formula $u_{\mathrm{si}}=-<(\frac{\left|e\right|}{3}(p_i-q_i)+q_i)*e+(1-\frac{\left|e\right|}{3}(p_i-q_i)-q_i)*c>$ Shown.

Sintering zone of tunnel furnace requires temperature control precision high it is allowed to error must be within ± 3 DEG C, using annular zone method Design requirement can be reached, obtain preferable control effect.

It should be appreciated that the above-mentioned specific embodiment of the present invention is used only for exemplary illustration or explains the present invention's Principle, and be not construed as limiting the invention.Therefore, that is done in the case of without departing from the spirit and scope of the present invention is any Modification, equivalent, improvement etc., should be included within the scope of the present invention.Additionally, claims purport of the present invention Covering the whole changes falling in scope and border or the equivalents on this scope and border and repair Change example.

Claims (1)

1. a kind of fuzzy control method for kiln thermal parameter control system is it is characterised in that comprise the following steps:

1) according to different controll plants, subregion is carried out to fuzzy control rule table；

2) to different sections, represented using different fuzzy control analytic expressions；

The formula of fuzzy control analytic expression is

Wherein, e is deviation, and c is change of error, and i is subregion, p_i、q_iFor intelligent Self-adjustment Factor, obtained not by adjusting and optimizing Same intelligent Self-adjustment Factor p, q value, thus realize different fuzzy control analytic expressions, p_i、q_iValue be definite value parameter, when e is When negative, a=-1, otherwise, a=1；

Temperature control to furnace heating-up band, chilling band, using typically positive and negative 6 grades of discretizations, positive and negative 3 grades of obfuscations, according to The feature of input deviation fuzzy quantity e and change of error fuzzy quantity c in fuzzy control rule table r, is divided into fuzzy control rule table r Four rectangular areas；

Control to wind flow in kiln, is divided according to deviation e scope, in fuzzy control rule table r according to deviation e Size is divided into three strip regions；

Control to deviation e, the impact of change of error c and high precision, the value according to deviation e and change of error c is by fuzzy control Rule list r is divided into three annular regions.