CN110687779A - PMSM self-adaptation control system based on fuzzy PID - Google Patents
PMSM self-adaptation control system based on fuzzy PID Download PDFInfo
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Abstract
The invention relates to a PMSM self-adaptive control system based on fuzzy PID, in particular to the field of industrial robot servo motor control. The method comprises the following steps: the system comprises a PI controller and a fuzzy PID controller, wherein the PI controller is used for controlling a general current loop or a speed loop of a motor, and the fuzzy PID controller is used for controlling a position 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-adjustment of PID parameters, and is suitable for the self-adaptive control of the permanent magnet synchronous motor.
Description
Technical Field
The invention relates to the field of industrial robot servo motor control, in particular to a PMSM (permanent magnet synchronous motor) self-adaptive control system based on fuzzy PID (proportion integration differentiation).
Background
Three-phase alternating current permanent magnet synchronous motors are commonly adopted in joint shafts of industrial robots, and generally one industrial robot comprises 4-6 joint shafts. The PMSM is a nonlinear, multivariable, strongly coupled system, making external disturbances very sensitive. For example, when an industrial robot performs work, the load of the industrial robot is in a time-varying state. It becomes important to make the robot reach the specified position accurately according to the planned speed and acceleration.
The traditional controller usually adopts three-loop 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 expert PID controller combines the traditional PID controller with an expert system to automatically adjust the parameters of the controller. However, this control method requires precise determination of the object model. And the quantitative representation of various variables and indexes in the control process is difficult, so the expert PID method has certain limitation.
Disclosure of Invention
The invention aims to solve the technical problem of how to realize the self-adjustment of PID parameters.
The technical scheme for solving the technical problems is as follows: a fuzzy PID based PMSM adaptive control system, comprising: the system comprises a PI controller and a fuzzy PID controller, wherein the PI controller is used for controlling a general current loop or a speed loop of a motor, and the fuzzy PID controller is used for controlling a position 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.
The beneficial effect of adopting the above further scheme is that compared with an analog PID control system, the incremental PID control can adapt to the connection with a computer, and meanwhile, the condition of insufficient memory can not occur.
Further, the input amount includes: position angle error e (k), error variance
The position angle error e (k) and the error variation
Obtained by the following formula:
e(k)＝y(k)-y*(k)
wherein y is the output signal and y is the input signal.
Further, the fuzzy control system is a two-dimensional fuzzy control system.
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, a sine function and a cosine function are used as the membership functions, 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.
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 schematic system structure diagram of an embodiment of a fuzzy PID-based PMSM adaptive control system according to the present invention;
FIG. 2 is a schematic diagram of the fuzzy PID-based structure of the present invention.
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.
The embodiment is substantially as shown in figures 1 and 2:
in this embodiment, the PMSM adaptive control system based on the fuzzy PID includes: the controller comprises a PI controller and a Fuzzy PID controller (Fuzzy-PID), wherein the PI controller is used for controlling a general current loop or a speed loop of the motor, and the Fuzzy PID controller is used for controlling a position loop;
the output of the position loop is used as the input of the speed loop, and when the position difference is 0, the ideal value of the speed is also 0; 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 adaptive control system in the embodiment is used, the output quantity of the PI controller needs to be decoupled by coordinate transformation, so that each physical quantity is converted into a direct current quantity from a static three-phase coordinate system (d-q) to a moving two-phase synchronous coordinate system (alpha-beta), each space vector in the synchronous coordinate system is converted into a direct current quantity, and thus, 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 control performance of the direct current motor can be achieved.
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.
Optionally, in some other embodiments, the PID control system is an incremental PID control.
Compared with an analog PID control system, the incremental PID control can adapt to the connection with a computer, and meanwhile, the condition of insufficient memory cannot occur.
Optionally, in some other embodiments, the input quantity comprises: position angle error e (k), error variance
Position angle error e (k) and error variance
Obtained by the following formula:
e(k)＝y(k)-y*(k)
wherein y is an output signal, the output signal in this embodiment is an actual motor rotation angle acquired by the encoder, y is an input signal, and the input signal in this embodiment is an expected motor rotation angle calculated by the robot controller.
Optionally, in some other embodiments, the fuzzy control system is a two-dimensional fuzzy control system, and two dimensions of the two-dimensional fuzzy control system in this embodiment include a control error and an error variation.
Optionally, in some other embodiments, the fuzzy control system is configured to receive input quantities, the input quantities comprising 7 parts NB (negative large), NM (negative medium), NS (negative small), ZO (zero), PS (positive small), PM (positive medium), and PB (positive large), the specific values being modified according to actual measured values, and the input quantities being { -3, -2, -1, 0, 1, 2, 3} according to empirically set domains of arguments. Detailed fuzzy PID-based Kp、Ki、KdThe fuzzy controller in fig. 2 also applies the following fuzzy rule table:
in the embodiment, the proper domain represents the proportion of a certain input quantity divided in a certain legal fuzzy space, specific numerical values such as-3 to-2 represent NB, -3 to-2 represent NM, and other principles are analogized. And combining the fuzzy subset and the control rule to carry out fuzzy reasoning to obtain fuzzy control quantity, and finally, obtaining accurate output quantity by the fuzzy control system through the fuzzy control quantity. The control rule in this embodiment is to generate a fuzzy output based on the control error and the fuzzy subset where the variation of the error is located, and based on engineering knowledge and process experimental values. 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.
It should be noted that the above embodiments are product embodiments corresponding to the above method embodiments, and for the description of each structural device and the optional implementation in this embodiment, reference may be made to the corresponding description in the above method embodiments, and details are not repeated herein.
The reader should understand that in the description of this specification, reference to the description of the terms "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
While the invention has been described with reference to specific embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (5)
1. A fuzzy PID based PMSM adaptive control system, comprising:
the system comprises a PI controller and a fuzzy PID controller, wherein the PI controller is used for controlling a general current loop or a speed loop of a motor, and the fuzzy PID controller is used for controlling a position 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 input quantity includes: position angle error e (k), error variance
The position angle error e (k) and the error variation
Obtained by the following formula:
e(k)＝y(k)-y*(k)
wherein y is the output signal and y is the input signal.
4. The fuzzy PID based PMSM adaptive control system of claim 1, wherein: the fuzzy control system is a two-dimensional fuzzy control system.
5. 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, a sine function and a cosine function are used as the 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.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112039384A (en) * | 2020-07-24 | 2020-12-04 | 西安方元明科技股份有限公司 | High-efficiency servo drive control system |
| CN112130451A (en) * | 2020-09-23 | 2020-12-25 | 兰州理工大学 | High-precision control method for mine filling slurry concentration |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112039384A (en) * | 2020-07-24 | 2020-12-04 | 西安方元明科技股份有限公司 | High-efficiency servo drive control system |
| CN112130451A (en) * | 2020-09-23 | 2020-12-25 | 兰州理工大学 | High-precision control method for mine filling slurry concentration |
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