CN112241121A - PMSM self-tuning control system based on fuzzy PID - Google Patents
PMSM self-tuning control system based on fuzzy PID Download PDFInfo
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Abstract
The invention relates to a PMSM (permanent magnet synchronous motor) self-tuning control system based on fuzzy PID (proportion integration differentiation), in particular to the field of intelligent mobile platform servo motor control. The method comprises the following steps: the system comprises a fuzzy PID controller, a double closed-loop control system of a current inner loop and a rotating speed outer loop, wherein the fuzzy PID controller is used for controlling the rotating speed loop. The fuzzy PID controller comprises a PID control system and a fuzzy control system, the fuzzy control system is used for receiving a difference value between an input quantity and a return quantity and a change rate of the difference value and processing to obtain an accurate output quantity, the fuzzy control system is also used for transmitting the accurate output quantity to the PID control system as a PID input quantity, and the PID control system is used for executing operation according to the PID input quantity. The scheme solves the technical problem of how to realize the self-regulation of the PID parameters, and is suitable for the self-regulation control of the permanent magnet synchronous motor.
Description
Technical Field
The invention relates to the field of intelligent mobile platform servo motor control, in particular to a PMSM (permanent magnet synchronous motor) self-tuning vector control system based on fuzzy PID (proportion integration differentiation).
Background
Servo direct current permanent magnet synchronous motors are commonly adopted in intelligent mobile platforms, and generally, one intelligent mobile platform comprises four or even more driving shafts. The PMSM is a nonlinear, multivariable, strongly coupled system, making external disturbances very sensitive. For example, when the intelligent mobile platform performs work, the load of the intelligent mobile platform is in a time-varying state. It becomes important to have the platform accurately reach the specified position according to the planned speed and acceleration.
The traditional controller usually adopts traditional PID regulation, and the control method is simple and practical. However, the conventional PID controller has certain limitations, and control parameters cannot be adjusted along with changes of external environments, and it is obvious that the same set of parameters is always adopted, so that accurate control performance cannot be achieved. In order to improve the real-time control performance of the permanent magnet motor control system, the combination of PID (proportion integration differentiation) -based control and other intelligent control becomes a research hotspot at present. The fuzzy PID controller combines the traditional PID controller with a fuzzy algorithm and automatically adjusts the parameters of the controller, so that the controlled object has better dynamic performance and static performance.
Disclosure of Invention
The technical problem to be solved by the application is how to realize the self-tuning of the PID parameters.
In order to solve the technical problems, the invention adopts a technical scheme that:
the PMSM self-tuning control system based on the fuzzy PID is characterized by comprising the following steps: the double closed-loop control system comprises a fuzzy PID controller, a current inner loop and a rotating speed outer loop, wherein the fuzzy PID controller is used for controlling the rotating speed loop.
The fuzzy PID controller comprises a PID control system and a fuzzy control system, the fuzzy control system is used for receiving a difference value between an input quantity and a return quantity and a change rate of the difference value and processing to obtain an accurate output quantity, the fuzzy control system is also used for transmitting the accurate output quantity to the PID control system as a PID input quantity, and the PID control system is used for executing operation according to the PID input quantity.
The invention has the beneficial effects that: the PID control is optimized through fuzzy control, the traditional PID control is influenced by a plurality of factors such as load, external temperature and the like when in use, the optimal control can be achieved only by adjusting PID parameters, and the PID is usually adjusted manually.
On the basis of the technical scheme, the invention can be further improved as follows.
Further, the PID control system is incremental PID control.
Compared with the position PID control, the incremental PID has smaller error, error data can be automatically screened out by a logic judgment method if necessary, and the situation of insufficient memory can not occur due to smaller operation amount.
Further, the input amount includes: the velocity error e (t), the error variation e (t) 'and the position angle error e (t)' are obtained by the following equations:
e(t)＝y(t2)-y(t1)
wherein, y (t)2) To output rotational speed, y (t)1) Is the input rotational speed.
Further, the fuzzy control system is used for receiving input quantity, the input quantity comprises 7 parts of NB, NM, NS, ZO, PS, PM and PB, a triangular membership function is used as a membership function, the input quantity is fuzzified to obtain fuzzy quantity, the fuzzy quantity is changed into a fuzzy subset on a proper universe of discourse, fuzzy reasoning is carried out by combining the fuzzy subset and a control rule to obtain fuzzy control quantity, and finally, the fuzzy control system obtains accurate output quantity through the fuzzy control quantity.
Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
FIG. 1 is a system simulation model of an embodiment of the fuzzy PID based PMSM self-tuning control system of the present invention;
FIG. 2 is a block diagram of the fuzzy PID control structure of the permanent magnet synchronous motor of the invention;
FIG. 3 is a comparison graph of the speed response curves of the fuzzy PID control system of the invention and the traditional PID control system;
as can be seen from FIG. 3, the fuzzy PID has a faster speed response, higher accuracy, less overshoot and better stability than the traditional PID control system.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.
Examples are shown in figures 1 and 2:
in this embodiment, the PMSM self-tuning control system based on the fuzzy PID includes: the system comprises a fuzzy PID controller, a double closed-loop control system of a current inner loop and a rotating speed outer loop, wherein the fuzzy PID controller is used for controlling the rotating speed loop.
The output of the speed loop is the input of the current loop, when the output of the speed loop is 0, the expected value of the current loop is also 0, and limit values are set for the current loop and the speed loop according to actual conditions so as to prevent the physical device from being damaged due to overlarge control quantity.
The fuzzy PID controller comprises a PID control system and a fuzzy control system, wherein the fuzzy control system is used for receiving the difference value between the input quantity and the return quantity and the change rate of the difference value and processing the difference value to obtain an accurate output quantity, the fuzzy control system is also used for transmitting the accurate output quantity to the PID control system as a PID input quantity, and the PID control system is used for executing operation according to the PID input quantity.
When the self-tuning control system in the embodiment is used, the output quantity of the motor needs to be decoupled by coordinate transformation, so that each space vector in a synchronous rotating coordinate system of a two-phase rotating d-q coordinate system is converted into a direct current quantity from a static three-phase coordinate through Clarke transformation and Park transformation, an excitation component and a torque component in stator current are converted into scalar quantities to be independent, and the given quantities are controlled in real time, so that the purpose of controlling the performance of the direct current motor can be achieved.
In some other embodiments, a fuzzy control system is used to receive the input quantity. The transformation of the input change area into the corresponding discourse field on the fuzzy set is as follows: e, ec { -30, -20, -10, 0, 10, 20, 30}, the fuzzy set of input quantities is E, DE { NB, NM, NS, ZO, PS, PM, PB }, the elements in this set represent negative large, negative medium, negative small, zero, positive small, positive medium, positive large, respectively, and the membership function type is taken as a triangular membership function in consideration of sensitivity of the domain of interest and the requirement of reducing workload.
A detailed fuzzy rule table of Kp, Ki, Kd based on fuzzy PID is shown below
TABLE 1KPFuzzy rule
TABLE 2KiFuzzy rule
TABLE 3KDFuzzy rule
In the embodiment, the proper discourse domain represents the proportion of a certain quantity of input divided in a fuzzy space, a specific numerical value such as-30 to-20 represents NB, -30 to-20 represents NM, and the other principles are analogized. And finally, the fuzzy control system obtains the accurate output quantity through defuzzification. The control rule in this embodiment is to generate a fuzzy output based on the fuzzy subset of the control error and the variation of the error as an input and based on a plurality of expert experiences and actual field test data. For example, when the error is more negative and the change rate is more different, the control quantity P, which is the PID, must be the positive maximum to make the error progress toward a small direction, so as to achieve the ideal state where the error is 0.
Claims (5)
1. A PMSM self-tuning control system based on fuzzy PID is characterized by comprising: the system comprises a fuzzy PID controller, a double closed-loop control system of a current inner loop and a rotating speed outer loop, wherein the fuzzy PID controller is used for controlling the rotating speed loop.
The fuzzy PID controller comprises a PID control system and a fuzzy control system, the fuzzy control system is used for receiving a difference value between an input quantity and a return quantity and a change rate of the difference value and processing to obtain an accurate output quantity, the fuzzy control system is also used for transmitting the accurate output quantity to the PID control system as a PID input quantity, and the PID control system is used for executing operation according to the PID input quantity.
2. The fuzzy PID based PMSM adaptive control system of claim 1, wherein: and the PID control system is incremental PID control.
3. The fuzzy PID based PMSM adaptive control system of claim 1, wherein: the current rotating speed of the permanent magnet synchronous motor is detected in real time through a rotating speed detection device such as a speed sensor, the difference is made between the given rotating speed and the current rotating speed to obtain rotating speed deviation e (t) and the change rate e (t) ', then e (t) and e (t)' are used as the input of a fuzzy controller, different PID parameters KP, KI and KD are output in real time according to fuzzy rules, and finally, the PWM signals are adjusted in real time through the three parameters, so that the control of the motor speed is realized. The input quantity includes: the velocity error e (t), the error variation e (t) 'and the position angle error e (t)' are obtained by the following equations:
e(t)＝y(t2)-y(t1)
wherein, y (t)2) To output rotational speed, y (t)1) Is the input rotational speed.
4. The fuzzy PID based PMSM adaptive control system of claim 1, wherein: the fuzzy control system is used for receiving input quantity, the input quantity comprises 7 parts of NB, NM, NS, ZO, PS, PM and PB, a triangular membership function is used as a membership function, the input quantity is fuzzified to obtain fuzzy quantity, the fuzzy quantity is changed into a fuzzy subset on a proper domain, fuzzy reasoning is carried out by combining the fuzzy subset and a control rule to obtain fuzzy control quantity, and finally the fuzzy control system obtains accurate output quantity through the fuzzy control quantity.
5. The fuzzy PID based PMSM adaptive control system of claim 1, wherein: voltage Space Vector Pulse Width Modulation (SVPWM) is combined with a fuzzy PID control method.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113568442A (en) * | 2021-07-23 | 2021-10-29 | 山东泉清通信有限责任公司 | Satellite alignment control system and method |
| CN114047696A (en) * | 2021-11-04 | 2022-02-15 | 重庆市生态环境科学研究院 | Fuzzy control system and control method of micro-nano bubble generating device |
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2020
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113568442A (en) * | 2021-07-23 | 2021-10-29 | 山东泉清通信有限责任公司 | Satellite alignment control system and method |
| CN113568442B (en) * | 2021-07-23 | 2024-04-02 | 山东泉清通信有限责任公司 | Star alignment control system and method |
| CN114047696A (en) * | 2021-11-04 | 2022-02-15 | 重庆市生态环境科学研究院 | Fuzzy control system and control method of micro-nano bubble generating device |
| CN114047696B (en) * | 2021-11-04 | 2024-01-26 | 重庆市生态环境科学研究院 | Fuzzy control system and control method of micro-nano bubble generating device |
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