CN110045597A - The improvement fuzzy PID control method precisely to work for Tool monitoring mechanical arm - Google Patents
The improvement fuzzy PID control method precisely to work for Tool monitoring mechanical arm Download PDFInfo
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- CN110045597A CN110045597A CN201910459941.4A CN201910459941A CN110045597A CN 110045597 A CN110045597 A CN 110045597A CN 201910459941 A CN201910459941 A CN 201910459941A CN 110045597 A CN110045597 A CN 110045597A
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 11
- 230000006872 improvement Effects 0.000 title claims abstract description 9
- 238000013178 mathematical model Methods 0.000 claims abstract description 10
- 230000003044 adaptive effect Effects 0.000 claims abstract description 6
- 230000010354 integration Effects 0.000 claims description 7
- 238000001514 detection method Methods 0.000 claims description 6
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B11/00—Automatic controllers
- G05B11/01—Automatic controllers electric
- G05B11/36—Automatic controllers electric with provision for obtaining particular characteristics, e.g. proportional, integral, differential
- G05B11/42—Automatic controllers electric with provision for obtaining particular characteristics, e.g. proportional, integral, differential for obtaining a characteristic which is both proportional and time-dependent, e.g. P. I., P. I. D.
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Abstract
The present invention relates to the improvement fuzzy PID control methods precisely to work for Tool monitoring mechanical arm, it is classical PID controller and Fuzzy PID self-adaptive control device composition, the automatic switchover of two kinds of controllers is realized according to the size of control variable deviation by selection switch, this complex method takes full advantage of the flexibility of the advantages of classical PID linear precision control and the adaptive device control of fuzzy, the advantages of adaptability, it can play a role for the Linear Control problem of mathematical models, the probabilistic nonlinear Control problem of mathematical model caused by due to the interference of operating environment can be directed to again to play a role, it precisely works in operating environment under the influence of multiple non-linear factor for mechanical arm and a kind of new solution route is provided.The present invention has rational design, compact-sized and easy to use.
Description
Technical field
The present invention relates to the improvement fuzzy PID control methods precisely to work for Tool monitoring mechanical arm.
Background technique
Currently, the mechanical arm occurred on the market is mostly industrial machinery arm, working environment is good, not by other it is non-linear because
The influence of element, control method have tended to be mature, but under complex work situation, the control method of operating accuracy is still
It requires further study, especially under this severe working environment of shield machine, it is easy to control module be made to be interfered
It influences, in order to solve this problem, effective control method is to study the vital task of this field personnel.
Summary of the invention
The problem to be solved in the present invention is to provide one under complicated working environment, Tool monitoring mechanical arm can be controlled precisely
The method of system.The technical issues of solving in detail and acquirement beneficial effect in aftermentioned content and combine in specific embodiment
Hold and specifically describes.
To solve the above problems, the technical solution used in the present invention is:
A kind of improvement fuzzy PID control method precisely to work for Tool monitoring mechanical arm, it is mechanical based on Tool monitoring
Arm,
The following steps are included:
Step 1；Firstly, establishing the mathematical model that each joint of mechanical arm outputs and inputs transmission function between variable；So
Afterwards, the movement for controlling each joint drives robot arm end effector to run by given trace；
Wherein, input variable includes the control electric signal of the servo motor in each joint of mechanical arm；
Output variable includes the angle of mechanical arm rotation, displacement, speed；
Mathematical model function is
U (t) is controller output；E (t) is input and output error, kpFor proportionality coefficient, TiFor integral coefficient, TDFor integral
Coefficient；
Step 2；Firstly, any one joint in selected step 1, establishes classical PID negative feedback control model；Then,
After after debugging, pid control parameter is determined, and construct Fuzzy PID self-adaptive control device model；
Step 3；Firstly, establishing Fuzzy PID self-adaptive control model and classical PID control complex controll model；Then,
According to control variable deviation numerical value, selection switch controls complex controll model in Fuzzy PID self-adaptive control model and classical PID
Automatically switch between the model of self adaptive control；
In step 2, based on the purpose for reducing the parameter that needs are adjusted, and PID controller is used；Debugging step includes,
Initial parameter is arranged when debugging and starting based on the safety for guaranteeing system by S1, and proportionality coefficient controls within 2,
Change of integral time was preferably 1 second between 0.8-1.5 seconds, to avoid there is the exception that system is unstable or overshoot is excessive
Situation；
S2, when the overshoot for the step response that the parameter selected in S1 generates is more than 10%, by multiple oscillation ability
It is stable or at all unstable, proportionality coefficient should be reduced, increase the time of integration；If step response does not have an overshoot, but quilt
Control amount rises excessively slow, and settling time is too long, should adjusting parameter in the opposite direction；If eliminate error speed compared with
Slowly, it can suitably reduce the time of integration, enhance integral action；Proportionality coefficient and the time of integration are adjusted repeatedly, if overshoot is still
It is so larger, differential control can be added, derivative time is gradually increased from 0, repeatedly the ratio of adjusting controller, integral and differential portion
The parameter divided.
In step 3, when the amount of deflection be less than given threshold when, PI controller detect departure signal select by
Fuzzy PID self-adaptive control selects switch detection when the amount of deflection is greater than or equal to given threshold to carry out the control of system
It selects to control complex controll model self-adapted control by classical PID to departure signal to carry out the control of system；Set threshold
Value is 2%.
In short, the debugging of pid parameter is the process of comprehensive, each parametric interaction, in practical debugging process
It repeatedly attempts to be very important and necessary.
The control method is mainly classical PID controller and Fuzzy PID self-adaptive control device composition, switchs root by selection
The automatic switchover of two kinds of controllers is realized according to the size of control variable deviation, it is linear that this complex method takes full advantage of classical PID
The advantages of flexibility of the advantages of precision controlling and the adaptive device control of fuzzy, adaptability, accurate mathematical mould can be directed to
The Linear Control problem of type plays a role, and it is probabilistic non-to be directed to mathematical model caused by due to the interference of operating environment
Linear Control problem plays a role, and precisely works in operating environment under the influence of multiple non-linear factor for mechanical arm and provides one
The new solution route of kind.
Beneficial effects of the present invention description without being limited thereto, in order to preferably be easy to understand, specific embodiment part into
More detailed description is gone.
Detailed description of the invention
Fig. 1 is classical PID control structure schematic diagram of the present invention.
Fig. 2 is Fuzzy PID self-adaptive control structure chart of the present invention.
Fig. 3 is composite control method structure diagram of the present invention.
Specific embodiment
Such as Fig. 1-3, a kind of improvement fuzzy PID control method precisely to work for Tool monitoring mechanical arm is based on cutter
Detection mechanical arm,
The following steps are included:
Step 1；Firstly, establishing the mathematical model that each joint of mechanical arm outputs and inputs transmission function between variable；So
Afterwards, the movement for controlling each joint drives robot arm end effector to run by given trace；
Wherein, input variable includes the control electric signal of the servo motor in each joint of mechanical arm；
Output variable includes the angle of mechanical arm rotation, displacement, speed；
Mathematical model function is
U (t) is controller output；E (t) is input and output error, kpFor proportionality coefficient, TiFor integral coefficient, TDFor integral
Coefficient；
Step 2；Firstly, any one joint in selected step 1, establishes classical PID negative feedback control model；Then,
After after debugging, pid control parameter is determined, and construct Fuzzy PID self-adaptive control device model；
Step 3；Firstly, establishing Fuzzy PID self-adaptive control model and classical PID control complex controll model；Then,
According to control variable deviation numerical value, selection switch controls complex controll model in Fuzzy PID self-adaptive control model and classical PID
Automatically switch between the model of self adaptive control；
In step 2, based on the purpose for reducing the parameter that needs are adjusted, and PID controller is used；Debugging step includes,
Initial parameter is arranged when debugging and starting based on the safety for guaranteeing system by S1, and proportionality coefficient controls within 2,
Change of integral time was preferably 1 second between 0.8-1.5 seconds, to avoid there is the exception that system is unstable or overshoot is excessive
Situation；
S2, when the overshoot for the step response that the parameter selected in S1 generates is more than 10%, by multiple oscillation ability
It is stable or at all unstable, proportionality coefficient should be reduced, increase the time of integration；If step response does not have an overshoot, but quilt
Control amount rises excessively slow, and settling time is too long, should adjusting parameter in the opposite direction；If eliminate error speed compared with
Slowly, it can suitably reduce the time of integration, enhance integral action；Proportionality coefficient and the time of integration are adjusted repeatedly, if overshoot is still
It is so larger, differential control can be added, derivative time is gradually increased from 0, repeatedly the ratio of adjusting controller, integral and differential portion
The parameter divided.
In step 3, when the amount of deflection be less than given threshold when, PI controller detect departure signal select by
Fuzzy PID self-adaptive control selects switch detection when the amount of deflection is greater than or equal to given threshold to carry out the control of system
It selects to control complex controll model self-adapted control by classical PID to departure signal to carry out the control of system；Set threshold
Value is 2%.
In short, the debugging of pid parameter is the process of comprehensive, each parametric interaction, in practical debugging process
It repeatedly attempts to be very important and necessary.
The control method is mainly classical PID controller and Fuzzy PID self-adaptive control device composition, switchs root by selection
The automatic switchover of two kinds of controllers is realized according to the size of control variable deviation, it is linear that this complex method takes full advantage of classical PID
The advantages of flexibility of the advantages of precision controlling and the adaptive device control of fuzzy, adaptability, accurate mathematical mould can be directed to
The Linear Control problem of type plays a role, and it is probabilistic non-to be directed to mathematical model caused by due to the interference of operating environment
Linear Control problem plays a role, and precisely works in operating environment under the influence of multiple non-linear factor for mechanical arm and provides one
The new solution route of kind.
The advantages of this control method combines classical PID linear precision to control and Fuzzy PID self-adaptive control flexibility adapt to
Property the advantages of make detection mechanical arm under multiple non-linear factor operating accuracy vulnerable to interference the problem of obtained very good solution.
The present invention has rational design, it is low in cost, durable, safe and reliable, easy to operate, time saving and energy saving, save fund, compact-sized
And it is easy to use.
It is to disclose in order to more clear, and the prior art is just no longer enumerated that the present invention, which fully describes,.
Finally, it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；Although
Present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that: it still may be used
To modify to technical solution documented by previous embodiment or equivalent replacement of some of the technical features；Make
It is obvious for being combined for those skilled in the art to multiple technical solutions of the invention.And these are modified or replace
It changes, the spirit and scope for technical solution of the embodiment of the present invention that it does not separate the essence of the corresponding technical solution.
Claims (3)
1. a kind of improvement fuzzy PID control method precisely to work for Tool monitoring mechanical arm, it is characterised in that: be based on cutter
Detection mechanical arm,
The following steps are included:
Step 1；Firstly, establishing the mathematical model that each joint of mechanical arm outputs and inputs transmission function between variable；Then, it controls
The movement for making each joint drives robot arm end effector to run by given trace；
Wherein, input variable includes the control electric signal of the servo motor in each joint of mechanical arm；
Output variable includes the angle of mechanical arm rotation, displacement, speed；
Mathematical model function is
U (t) is controller output；E (t) is input and output error, kpFor proportionality coefficient, TiFor integral coefficient, TDFor integration system
Number；
Step 2；Firstly, any one joint in selected step 1, establishes classical PID negative feedback control model；Then, through adjusting
After examination, pid control parameter is determined, and construct Fuzzy PID self-adaptive control device model；
Step 3；Firstly, establishing Fuzzy PID self-adaptive control model and classical PID control complex controll model；Then, according to
Variable deviation numerical value is controlled, selection switch is adaptive in Fuzzy PID self-adaptive control model and classical PID control complex controll model
Automatically switch between the model that should be controlled.
2. the improvement fuzzy PID control method according to claim 1 precisely to work for Tool monitoring mechanical arm, special
Sign is: in step 2, using PID controller, debugging step includes,
Initial parameter is arranged when debugging and starting based on the safety for guaranteeing system by S1, and proportionality coefficient controls within 2, integral
Time controlled between 0.8-1.5 seconds；
S2, when the overshoot for the step response that the parameter selected in S1 generates is more than 10%, the ratio of adjusting controller, integral
With the parameter of differential part, until parameter generate step response overshoot less than 10%.
3. the improvement fuzzy PID control method according to claim 2 precisely to work for Tool monitoring mechanical arm, special
Sign is: in step 3, when the amount of deflection be less than given threshold when, PID controller detect departure signal select by
Fuzzy PID self-adaptive control selects switch detection when the amount of deflection is greater than or equal to given threshold to carry out the control of system
It selects to control complex controll model self-adapted control by classical PID to departure signal to carry out the control of system；Set threshold
Value is 2%.
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| CN201910459941.4A CN110045597A (en) | 2019-05-30 | 2019-05-30 | The improvement fuzzy PID control method precisely to work for Tool monitoring mechanical arm |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112835286A (en) * | 2020-11-27 | 2021-05-25 | 江西理工大学 | PID parameter automatic setting method and system |
| CN114637207A (en) * | 2022-03-19 | 2022-06-17 | 四川大学 | Anti-interference synchronous gait control method for shield tunnel arc-shaped part mounting machine |
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|---|---|---|---|---|
| CN102109822A (en) * | 2011-04-02 | 2011-06-29 | 重庆交通大学 | Variable structure two-degrees-of-freedom intelligent integration control method for servo motor |
| CN106707753A (en) * | 2016-12-25 | 2017-05-24 | 北京工业大学 | Pump linear motor adaptive control method |
| US20170220006A1 (en) * | 2016-02-01 | 2017-08-03 | Varian Semiconductor Equipment Associates, Inc. | Proportional integral derivative control incorporating multiple actuators |
| CN108227496A (en) * | 2018-01-08 | 2018-06-29 | 石河子大学 | A kind of improvement fuzzy PID control method for the accurate operation of mechanical arm of connecting |
| CN109445274A (en) * | 2018-10-25 | 2019-03-08 | 清华大学深圳研究生院 | A kind of Flexible Space Mechanical Arms vibration control method and system |
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2019
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Patent Citations (5)
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| CN102109822A (en) * | 2011-04-02 | 2011-06-29 | 重庆交通大学 | Variable structure two-degrees-of-freedom intelligent integration control method for servo motor |
| US20170220006A1 (en) * | 2016-02-01 | 2017-08-03 | Varian Semiconductor Equipment Associates, Inc. | Proportional integral derivative control incorporating multiple actuators |
| CN106707753A (en) * | 2016-12-25 | 2017-05-24 | 北京工业大学 | Pump linear motor adaptive control method |
| CN108227496A (en) * | 2018-01-08 | 2018-06-29 | 石河子大学 | A kind of improvement fuzzy PID control method for the accurate operation of mechanical arm of connecting |
| CN109445274A (en) * | 2018-10-25 | 2019-03-08 | 清华大学深圳研究生院 | A kind of Flexible Space Mechanical Arms vibration control method and system |
Non-Patent Citations (1)
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| 郝丽娜: "《工业机器人控制技术》", 30 November 2018, 武汉华中科技大学出版社 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112835286A (en) * | 2020-11-27 | 2021-05-25 | 江西理工大学 | PID parameter automatic setting method and system |
| CN112835286B (en) * | 2020-11-27 | 2023-02-17 | 江西理工大学 | PID parameter automatic setting method and system |
| CN114637207A (en) * | 2022-03-19 | 2022-06-17 | 四川大学 | Anti-interference synchronous gait control method for shield tunnel arc-shaped part mounting machine |
| CN114637207B (en) * | 2022-03-19 | 2023-06-30 | 四川大学 | Anti-interference synchronous gait control method for shield tunnel arc-shaped piece mounting machine |
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Application publication date: 20190723 |
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