CN102328009B

CN102328009B - Fuzzy control fuzzification and fuzzy reasoning method for non-linear precise forging press

Info

Publication number: CN102328009B
Application number: CN 201110291425
Authority: CN
Inventors: 陈冰冰; 黄伟权
Original assignee: Foshan Shunde Industry And Information Technology Research Center Co ltd
Current assignee: Foshan, Shunde, Mdt InfoTech Ltd
Priority date: 2011-09-30
Filing date: 2011-09-30
Publication date: 2013-09-11
Anticipated expiration: 2031-09-30
Also published as: CN102328009A

Abstract

The invention relates to the field of industrial automatic control, in particular to a fuzzy control fuzzification and fuzzy reasoning method for a non-linear precise forging press. A control system comprises a fuzzification interface, a fuzzy reasoning machine, a knowledge base and a defuzzification interface. Input controlled quantities are the displacement error e of a slider, the displacement error change rate ce and the working slider displacement y; an output controlled quantity is the rotation angle increment delta u of a motor; the input controlled quantities: the displacement error eand the displacement error change rate ce, are converted into proper language values in a domain of discourse after defuzzification processing is carried out on the input controlled quantities by the subordinate function of the fuzzification interface; a fuzzy output quantity is obtained after fuzzy reasoning is carried out on a fuzzified input variable by the fuzzy reasoning machine according to a fuzzy rule; and an actual input motor rotation angle increment delta u is obtained after weighted average defuzzification is carried out on the fuzzified output quantity. The output of the control system disclosed by the invention is capable of better tracking input. The fuzzy control fuzzification and fuzzy reasoning method for the non-linear precise forging press is capable of realizing product processing of which the precision is 10mum when being applied to the non-linear precise forging press and can be widely applied to various non-linear precise forging presses.

Description

The obfuscation of non-linear accurate forging press fuzzy control and fuzzy reasoning method

Technical field

The present invention relates to field of industrial automatic control, especially a kind of obfuscation of non-linear accurate forging press fuzzy control and fuzzy reasoning method.

Background technology

Forging and pressing are one of fundamental technologies of machine building industry, are important substance basis and the technical foundation of research and development, all kinds of mechanized equipments of production, are the indispensable blanks of manufacturing machine product vital part and strength member.Its range of application relates to the every field of national economy, national defense industry and social life.In industrial departments such as automobile, rail vehicles, electric power, petrochemical industry, coal, metallurgy, Aeronautics and Astronautics, boats and ships, weapons and machinery, vital load-carrying member is all made by forging.

What domestic metal forming machinery control algolithm was most widely used at present is ratio, integration, differential control, is called for short PID control.The PID controller existing nearly 70 years history so far of coming out, it is simple in structure with it, good stability, reliable operation, easy to adjust and become one of major technique of Industry Control.Yet, for the nonlinear Control field, use traditional pid algorithm and but can not obtain good effect.

The Intelligent Control Theory that the later stage seventies rises is that intelligence control system is by imitating human brain neuromechanism, thinking, expert decision-making, biological evolution and group property etc., can design the controller of high intelligence, for system's control of large-scale complex provides a kind of solution.Fuzzy control is as one of Intelligent Control Theory, use concept and the correlation technique of expert system, the intelligent control system that simulating human expert's control knowledge and skilled engineers and technicians' operating experience is constructed, it is well used in many systems non-linear, that Mathematical Modeling is difficult to set up.

Summary of the invention

The technical problem that the present invention solves is to provide a kind of be suitable for obfuscation and fuzzy reasoning method non-linear accurate forging press, high-precision non-linear accurate forging press fuzzy control; Can effectively solve classical control theory in the problem that non-linear accurate forging press is difficult to modeling and effectively controls, can realize that precision is the product processing of 10 μ m.

The technical scheme that the present invention solves the problems of the technologies described above is:

Fuzzy method is: the control system of described accurate forging press is made of defuzzification interface, indistinct logic computer, knowledge base and ambiguity solution interface; The input controlled quentity controlled variable is displacement error e, displacement error rate of change ce and the work slider displacement y of slide block, and the controlled quentity controlled variable of output is the corner increment △ u of motor; Displacement error e, the displacement error rate of change ce of input control variables slide block and work slider displacement y by defuzzification interface membership function Fuzzy processing after, transform to language value suitable on the corresponding basic domain; E and ce domain are { 12 ,-8 ,-4 ,-1,1,4,8,12 }, and fuzzy language value is taken as { NB, NM, NS, NZ, PZ, PS, PM, PB }, and the y domain is { 0,20,40,60 }, and fuzzy language value is taken as { ZO, PS, PM, PB }.

The total fuzzy control of system is output as the corner increment △ u of motor, is the stack of the fuzzy reasoning output u2 of the fuzzy reasoning output u1 of e, ce and y.

Fuzzy reasoning method is: the control system of described accurate forging press is made of defuzzification interface, indistinct logic computer, knowledge base and ambiguity solution interface; The input controlled quentity controlled variable is displacement error e, displacement error rate of change ce and the work slider displacement y of slide block; u ₁Be the fuzzy reasoning output of e, ce, u ₂Fuzzy reasoning output for y; The controlled quentity controlled variable of output is the corner increment △ u of motor, △ u=u ₁+ u ₂The input variable of obfuscation obtains fuzzy output quantity according to fuzzy rule behind the indistinct logic computer fuzzy reasoning; u ₁As shown in the table with the fuzzy rule of e, ce:

u ₂As shown in the table with the fuzzy rule of y:

y	u ₂
		ZO	ZO
PS	PS
		PM	PM
PB	PB

Beneficial effect:

The invention has the beneficial effects as follows at the accurate forging press of nonlinear Control and realize that precision is the product processing of 10um, for the forging press of nonlinear Control provides a kind of control scheme.

Description of drawings

The present invention is further described below in conjunction with accompanying drawing:

Fig. 1 is the frame for movement schematic diagram of the accurate forging press of the present invention;

Fig. 2 is mechanism and the force analysis figure of the accurate forging press of the present invention;

Fig. 3 is the structured flowchart of fuzzy controller of the present invention;

Fig. 4 is the obfuscation membership function figure of error e of the present invention and error rate ce;

Fig. 5 is the obfuscation membership function figure of work slider displacement y of the present invention.

The specific embodiment

As shown in Figure 1, the accurate forging press that the present invention relates to is made up of fuselage, low-speed big AC servomotor, synchromesh gear, ball screw, ball spline, driving slide block, compensating cylinder, short connecting rod, bent axle, long connecting rod, slide block 1 etc.The operation principle of forging press is: controller according to the user specify slide block time-corner of position key point control servomotor, the driven by motor synchronous pulley, drive slide block by ball-screw, drive terminal slide block through force-increasing mechanism again and move in vertical direction, thereby drive mold work.Fig. 2 is mechanism and the force analysis figure of forging press, and wherein the A point maintains static, and the C point is slide block 1, and the D point links to each other with screw mandrel, drives bar c motion when screw mandrel moves up and down, because A fixes joint B drive rod b motion, thereby the vertical up-or-down movement of drive slide block.Corner and the slide block movement displacement of servomotor are non-linear relation as can be seen by its operation principle.

The structure of fuzzy controller block diagram as shown in Figure 3, according to the kinetic characteristic of motor and slide block, the control system of accurate forging press is made of defuzzification interface, indistinct logic computer, knowledge base and ambiguity solution interface; The input controlled quentity controlled variable is displacement error e, displacement error rate of change ce and the work slider displacement y of slide block, and the controlled quentity controlled variable of output is the corner increment △ u of motor; Input control variables displacement error e and displacement error rate of change ce convert language value suitable in the domain to after by defuzzification interface membership function Fuzzy processing, the input variable of obfuscation obtains fuzzy output quantity according to fuzzy rule behind the indistinct logic computer fuzzy reasoning, fuzzy output quantity obtains actual output motor corner increment △ u behind the weighted average ambiguity solution; Fuzzy controller can be expressed as Δ u=f (∫ edt, e, y).

Obfuscation is the process that input variable e, ce and y is transformed to appropriate language value on the corresponding basic domain.E and ce domain are { 12 ,-8 ,-4 ,-1,1,4,8,12 }, and fuzzy language value is taken as { NB, NM, NS, NZ, PZ, PS, PM, PB }, and membership function as shown in Figure 4; The y domain is { 0,20,40,60 }, and fuzzy language value is taken as { ZO, PS, PM, PB }, and membership function as shown in Figure 5.

Fuzzy rule adopts the structure of if-then, sums up a series of fuzzy control rules in conjunction with practical experience, forms the fringe control table, as shown in Table 1 and Table 2.Fuzzy input quantity obtains fuzzy control output quantity △ u through control law, and total output quantity is the stack of two fuzzy rule fuzzy control output quantity u1, u2.

Table 1u ₁Fuzzy reasoning table with e, ce

Table 2u ₂Fuzzy reasoning table with y

y	u ₂
		ZO	ZO
PS	PS
		PM	PM
PB	PB

The input fuzzy variable result that reasoning is calculated according to rule list still is fuzzy quantity, uses weighted mean method that the output controlled quentity controlled variable is carried out ambiguity solution, and computing formula is as follows:

u^{*} = \underset{j}{Σ} μ c_{j} (u_{j}) u_{j} / \underset{j}{Σ} {μc}_{j} (u_{j})

Claims

1. the fuzzy method of non-linear accurate forging press fuzzy control, it is characterized in that: the control system of described accurate forging press is made of defuzzification interface, indistinct logic computer, knowledge base and ambiguity solution interface; The input controlled quentity controlled variable is displacement error e, displacement error rate of change ce and the work slider displacement y of slide block, and the controlled quentity controlled variable of output is the corner increment Delta u of motor; Displacement error e, the displacement error rate of change ce of input control variables slide block and work slider displacement y by defuzzification interface membership function Fuzzy processing after, transform to language value suitable on the corresponding basic domain; E and ce domain be 12 ,-8 ,-4 ,-1,1,4,8,12}, fuzzy language value be taken as NB, NM, NS, NZ, PZ, PS, PM, PB}, y domain be 0,20,40,60}, fuzzy language value is taken as { ZO, PS, PM, PB}.

2. the fuzzy method of fuzzy control according to claim 1, it is characterized in that: the total fuzzy control of system is output as the corner increment Delta u of motor, is the stack of the fuzzy reasoning output u2 of the fuzzy reasoning output u1 of e, ce and y.

3. the fuzzy reasoning method of non-linear accurate forging press fuzzy control, it is characterized in that: the control system of described accurate forging press is made of defuzzification interface, indistinct logic computer, knowledge base and ambiguity solution interface; The input controlled quentity controlled variable is displacement error e, displacement error rate of change ce and the work slider displacement y of slide block; u ₁Be the fuzzy reasoning output of e, ce, u ₂Fuzzy reasoning output for y; The controlled quentity controlled variable of output is the corner increment Delta u of motor, Δ u=u ₁+ u ₂The input variable of obfuscation obtains fuzzy output quantity according to fuzzy rule behind the indistinct logic computer fuzzy reasoning; u ₁As shown in the table with the fuzzy rule of e, ce:

u ₂As shown in the table with the fuzzy rule of y:

。