This paper describes the composition and working principle of the magnetic suspension spindle system, and proposes a new digital controller design based on the conventional PID intelligent PID controller. The core component is TI's TMS320LF2407A, and the overall hardware block diagram of the 5-DOF magnetic suspension spindle system is designed. Using C2000 as a development platform, an intelligent PID controller based on conventional PID is designed. The theoretical analysis results show that this intelligent PID controller can achieve better control effects and achieve higher control accuracy requirements.

1 Introduction

Active Magnetic Bearings (AMB) (hereinafter abbreviated as magnetic bearings) is a collection of many disciplines that best embody mechatronic products. Compared with conventional bearings, magnetic bearings have the following advantages: no contact, no friction, high speed, and high precision. After a long time of traditional bearings, the wear is serious and must be replaced. The service life of the oil-lubricated bearings will be prolonged, but it will inevitably lead to oil leakage and affect the environment. This can be avoided for magnetic bearings. It can be said that it is an environmentally friendly product. Magnetic bearings not only have research significance, but also have a broad application space: aerospace, transportation, medical, mechanical processing and other fields. There are many application examples abroad.

The magnetic suspension bearing system is composed of the following five parts: controller, rotor, electromagnet, sensor and power amplifier. One of the most critical components is the controller. The performance of the controller basically determines the performance of the entire magnetic bearing system. The control laws of the controller determine the dynamic performance and stiffness, damping and stability of the magnetic bearing system. There are two types of controllers: analog controllers and digital controllers. Although the current widely used analog controllers in China satisfy the stability of the system to a certain extent, the analog controllers have the following deficiencies compared to the digital controllers: (1) Inconvenient adjustment, (2) Difficult to implement complicated control (3) Two or more degrees of freedom cannot be simultaneously controlled, (4) Poor interchangeability, that is, different magnetic bearings must have corresponding controllers, (5) large power consumption, and large volume. Magnetic bearings need to be widely used. The poor performance of online adjustment of analog controllers is one of the reasons. Therefore, the direction of digitization is the development trend of magnetic bearings. At the same time, to realize the intelligentization of the magnetic bearing system, it is clear that the analog controller is difficult to meet this requirement. Therefore, from the perspectives of improving the performance of magnetic bearings, reliability, enhancing the flexibility of the controller, and reducing the volume, power consumption, and the future development toward networking and intelligence, it is necessary to realize the digitization of the controller. The control theory has developed rapidly and has been widely used in the past three decades. Research on the control laws of magnetic suspension bearing controllers has also made remarkable progress in recent years. The current control laws related to foreign countries include: conventional PID and PD control, adaptive control, H∞ control, etc. The conventional PID, PD control and H∞ control are used, but the relevant information of H∞ control successfully applied to the magnetic bearing system has not been reported yet.

Judging from the current domestic and international developments, foreign research and productization have led China for many years. In foreign countries, there are specialized magnetic bearing companies and magnetic levitation research centers engaged in research and development and application work in this area, such as SKF, NASA and others. Among them, the control law used by the SKF company's magnetic bearing controller is adaptive control. Its product range is 50 to 2500N in load capacity, 1,800 to 100,000 r/min in rotation speed, and the operating temperature is lower than 220°C. NASA is NASA. They have been conducting magnetic levitation research for several decades and are mainly used in aerospace. Research fields include rocket engines and magnetic levitation orbital propulsion systems (in September 2002, 2 gram accelerations were added to the maglev orbit to make rockets. The initial launch speed reached 643 to 965km/h, and there is currently no magnetic bearing company in China. To catch up with the development level of foreign magnetic bearings, it is necessary to increase the investment in manpower and material resources. Study on control laws of magnetic suspension bearing controllers in China Starting late, most of the current use is conventional PID and PD control, and the actual circuit also uses PIDD.The control accuracy is relatively not very high, and each system must correspond to the corresponding KP, KI, KD, adjustment It is very troublesome and the user will find it very inconvenient. In order to make the magnetic suspension bearing product, the above problem must be solved, anyone can use it conveniently, and it must be made into a product like a fool-type device. It is necessary to solve the problem of the controller first, solving this problem is to make the controller intelligent.Intelligent content package Including the intelligence of the hardware and the intelligence of the software.This article only discusses the intelligent problem and the realization means of the controller in the control algorithm, which can lay a certain foundation for the final solution of the intelligentization of the magnetic suspension bearing.

2 The composition and working principle of the magnetic bearing system

Magnetic bearing system consists of five parts: rotor, electromagnet, sensor, controller and power amplifier. The magnetic bearing system is a very complex mechatronic system. It is very difficult to accurately describe with a mathematical model. Generally, it is analyzed near the equilibrium point and then linearized. Without considering the coupling between the five degrees of freedom, only a single degree of freedom analysis is needed, as shown in Figure 1.

Fig.1 Schematic diagram of a single degree of freedom magnetic bearing system

Working principle: The rotor is in the equilibrium position x0 under the action of the bias current I0. If a disturbance f0 occurs at a certain moment, the rotor will deviate from the equilibrium position and the offset is x. In order to return the bearing to the equilibrium position, the control current must be added. Ic, the magnetic force of the electromagnet I increases, and the magnetic force of the electromagnet II decreases. The force on the rotor at this time is:

Where: μ0 is the permeability, S is the air-gap cross-sectional area, and N is the number of coil turns. Equation (1) is linearized at (x=0, ic=0). Without considering other forces, Newton's second law gives:

Among them: displacement stiffness coefficient Current stiffness factor . The Laplace transform of (2) is:

The structural block diagram of the system can be obtained by (3), as shown in (2): where: Gc(s), Gp(s), and Gs(s) are the transfer functions of the controller, power amplifier, and sensor, respectively. For the controller can choose the traditional PID, you can also use the intelligent controller described in this article.

Fig. 2 Block diagram of the closed-loop transfer function using the voltage control strategy

3 PID controller and its intelligent method

3.1 Conventional PID Controller

For comparison, it is necessary to review the traditional PID controller here.

As we all know, conventional PID control is based on having an accurate mathematical model. It has the advantages of simple structure, good stability and reliability. In the contemporary control field, PID control occupies a very large proportion in the field of control. The key to designing it is the tuning of PID parameters. However, in the actual control, the process is very complicated. At a certain time, it has a high degree of nonlinearity, time-varying uncertainty, and hysteresis. Under the influence of outside interference, load disturbance and other factors, the parameters and even the mathematical model will change. At this time, the conventional PID obviously cannot meet the requirements of those high-precision control. If you can adjust the PID parameters in real time, this will definitely meet the requirements. This PID is an intelligent PID.

3.2 Intelligent PID Controller

With the rapid development of intelligent control theory in recent decades and its continuous application in practice, currently the most active intelligent controls include: fuzzy control, neural network control, and expert control. People gradually apply the idea of ​​intelligent control to conventional PIDs to form various forms of intelligent PID control. It has both the advantages of intelligent control and traditional PID. For example, the automatic tuning control parameters in the intelligent control can well adapt to the parameter changes in the control process and the traditional PID control structure is simple, and the reliability is high. . It is based on these two major advantages that intelligent PID control is used by many control processes. Intelligent PID controller can be divided into: PID controller based on neural network, fuzzy PID controller, expert PID controller and many other.

3.3 Expert PID Controller

Expert PID controller schematic shown in Figure 3. It is a traditional PID algorithm based on the increase of the error e and the error rate of change, check the fuzzy matrix set, knowledge base, determine through knowledge to determine whether to adjust and how to adjust the three parameters of PID Kp, Ki, Kd. Obviously, it can adjust the PID parameters in real time according to expert knowledge and experience, and has good controllability and robustness. This article briefly explains the design of such controllers.

Figure 3 Expert PID Controller Schematic

4 Hardware Design

Taking into account the characteristics of the magnetic levitation spindle system, but also in order to make full use of its advantages, the digital controller uses DSP as the core component. Considering the performance of TI's various DSP chips and the modules integrated in the chip, TI has chosen to use TMS320LF2407A as its core component.

TI's TMS320LF2407A chip has the following characteristics: (a) can use the internal operating frequency of 20MHz, can also be added to the operating frequency, the maximum is 40MHz, the crystal used in this article 15MHz, after the frequency as the frequency of 30MHz. (II) The chip integrates two 8-bit, 1-bit, 10-bit A/D converters for a total of 16 channels. (C) comes with 16K Flash ROM and 544 words of data memory. (d) has 12 PWM outputs. (five) Integrated Watchdog, PLL clock, EV event manager and other circuits. Because this chip integrates these very useful circuits in the control, this on the one hand reduces the hardware design difficulty and volume, on the other hand it improves the reliability of the system.

The output range of the eddy current displacement sensor is generally relatively wide, about 0 to -24V, and the range of the integrated A/D converter in the TMS320LF2407A chip is 0 to +5V. (Cause: The DSP can only handle signals between 0 and +5V. Therefore, a level conversion circuit must be added. Conversion principle: Because the resolution of the sensor determines the minimum control precision of the magnetic bearing system, the level conversion circuit must be guaranteed under the condition of the resolution, that is, the voltage between -14.5 and -9.5V is kept constant, and the others are maximized. deal with.

Figure 4 is a hardware design block diagram of a five-degrees-of-freedom magnetic levitation spindle system.

Fig. 4 Overall block diagram of a five-degree-of-freedom magnetic bearing system

5 Software Design

As a system, its software includes system initialization, control algorithms, and special conditions (such as power down, overflow, etc.) processing. The TMS320LF2407A is based on the C2000 development environment and can be developed in assembly language and C language. C language has a short development cycle, readability and portability, but the implementation of low efficiency, fault self-diagnosis is weak. Assembler languages ​​perform efficiently, but they have many instructions and are cumbersome to write. Therefore, under normal circumstances, the calling part (such as: interrupt part and initialization part) using assembly language, control algorithm written in C language to reduce the complexity of the program and improve its modifiable. The control algorithm uses expert PID control based on traditional PID. The traditional PID control adopts the differential pre-actual differential PID. The structure is shown in Figure 5.

Figure 5 Differential Actual Differential PID

The system software written in this article is written in both assembly language and C language. The key part of the system software is the preparation of control algorithms. Before the control algorithm is written, the stability of the model of the magnetic levitation spindle system is analyzed and the three parameters Kp, Ki and Kd of the optimally controlled PID are found. Based on the previous experience of analog control and digital control, the fuzzy sets corresponding to e, & and Kp, Ki, Kd are determined. The specific software editing block diagram is shown in Figure 6. EV is the event manager, and N is the maximum control amount corresponding to the specific magnetic suspension spindle system.

Figure 6 Software Block Diagram

6 Conclusion

The simulation results of the traditional PID controller and intelligent PID controller in a single degree of freedom are analyzed and compared, and the control effect of the intelligent PID controller is better than that of the traditional PID controller, which is mainly reflected in the short time required from the start to the float to the control. High precision, strong anti-interference ability.

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