[align=center]Deng Yaochu, Gao Chiming, Wu Xingrong, and Liu Yaqin from the School of Mechanical and Electrical Engineering, Xi'an University of Electronic Science and Technology, and the Xi'an Institute of Applied Optics, respectively[/align] This paper introduces the principle and characteristics of voice coil motors, proposes using high-speed DSP to control voice coil motors to achieve high-response, high-speed, high-frequency, and high-precision motion, and introduces the principle and application of PID control algorithms, which have strong versatility. 1 Introduction A voice coil motor (VCO) is a special type of direct-drive motor that can directly convert electrical energy into linear motion mechanical energy without any intermediate conversion mechanism. Its principle is as follows: a cylindrical winding is placed in a uniform air gap magnetic field. When the winding is energized, it generates electromagnetic force, driving the load to perform linear reciprocating motion. Changing the strength and polarity of the current changes the magnitude and direction of the electromagnetic force. Therefore, the motion of a voice coil motor can be linear or circular. It has advantages such as high response, high speed, high acceleration, simple structure, small size, good force characteristics, and convenient control. In recent years, with the rapid development of voice coil motor technology, voice coil motors have been widely used in precision positioning systems and many different types of high-acceleration, high-frequency excitation, fast and high-precision positioning motion systems. The TMS320LF2407 is a new 16-bit fixed-point DSP chip manufactured by TI. It is a low-cost, low-power, high-performance digital signal processor designed by TI specifically for digital control applications of motors, with an instruction cycle of 33ns. It integrates a front-end sampling AD converter, simplifying hardware circuit design while meeting system real-time requirements. This paper applies the DSP to the control of a voice coil motor, implementing digital PID control. This not only improves the system's integration but also enables various complex control algorithms, improving the performance of the servo system. It has strong versatility and can be used in many different applications as needed. [IMG=Ampere's Force Principle Diagram]/uploadpic/THESIS/2007/11/2007111615452523611R.jpg[/IMG] Figure 1 Ampere's Force Principle Diagram 2 Principle of Voice Coil Motor The working principle of a voice coil motor is based on the Ampere's force principle, that is, when a current-carrying conductor is placed in a magnetic field, a force F will be generated. The magnitude of the force depends on the strength of the magnetic field B, the current I, and the directions of the magnetic field and the current. If there are N wires of length L placed in the magnetic field, the force acting on the wires can be expressed as (1) where k is a constant. As shown in Figure 1, the direction of the force is a function of the current direction and the magnetic field vector, and is the interaction between the two. If the magnetic field and the length of the wires are constant, the generated force is proportional to the input current. In the simplest voice coil motor structure, the linear voice coil motor is a tubular coil winding located in the radial electromagnetic field. The magnetic field inside the ferromagnetic cylinder is generated by a permanent magnet. This arrangement allows the magnets attached to the coil to have the same polarity. The core of the ferromagnetic material is arranged on the axial center line of the coil and connected to one end of the permanent magnet to form a magnetic circuit. When the coil is energized, according to the Ampere force principle, it is subjected to the magnetic field and a force along the axis is generated between the coil and the magnet. The polarity of the voltage across the energized coil determines the direction of the force. 3 Digitalization of PID control algorithm In modern industrial control systems, the PID controller is one of the most widely used controllers. The analog expression of the ideal PID control algorithm is (2) Where: e(t) — the deviation signal of the controller, which is equal to the difference between the given value and the measured value Kp — the proportional coefficient of the controller TI — the integral time constant of the controller, which represents the magnitude of the integral speed. The larger the value, the slower the integral speed and the weaker the integral action TD — the derivative time of the controller The correction links of the PID controller are as follows: Proportional link: It reflects the deviation signal e(t) of the control system proportionally. Once the deviation is generated, the controller immediately generates a control action to reduce the deviation. Integral link: It is mainly used to eliminate steady-state error and improve the accuracy of the system. The strength of the integral action depends on the integral time constant T[sub]I[/sub]; the larger T[sub]I[/sub], the weaker the integral action, and vice versa. The derivative element reflects the changing trend of the deviation signal and can introduce an effective early correction signal into the system before the deviation signal value becomes too large, thereby accelerating the system's response speed and reducing the settling time. In computer control systems, digital PID controllers are used. Digital PID control algorithms are usually divided into positional PID control algorithms and incremental PID control algorithms. Digital positional PID control algorithm: (3) Where: k—sampling sequence number, k=0,1,2… u(k) —output value at the kth sampling time e(k) —input deviation value at the kth sampling time e(k-1) —input deviation value at the (k-1)th sampling time K[sub]I[/sub]—integral coefficient, K[sub]I[/sub]=K[sub]P[/sub]T/T[sub]I[/sub] K[sub]D[/sub]—derivative coefficient, K[sub]D[/sub]=K[sub]P[/sub]T[sub]D[/sub]/T Digital incremental PID control algorithm: (4) (5) The purpose of introducing an integral element in a common digital PID controller is mainly to eliminate steady-state error and improve accuracy. However, when the process starts, ends, or the setpoint is increased or decreased significantly, the system output has a large deviation in a short period of time, which will cause the integral accumulation of the PID calculation, resulting in the calculated control quantity exceeding the limit control quantity corresponding to the maximum possible action range of the actuator, ultimately causing a large overshoot of the system, or even causing system oscillation. The introduction of the integral separation PID control algorithm maintains the integral action and reduces the overshoot, resulting in a significant improvement in control performance. Its specific implementation is as follows: (1) According to the actual situation, a threshold ε>0 is set manually. (2) At this time, PID control is used (K[sub]I[/sub] is set to 0), which can avoid a large overshoot and make the system respond faster. (3) At this time, PID control can ensure the control accuracy of the system. Therefore, the integral separation PID control algorithm is often used in actual engineering. 4. Engineering Applications In engineering applications, the TMS320LF2407 is used to control the voice coil motor. Depending on the application, a detection device is set up to sample and detect the actual output, which is then converted from digital to digital (A/D) and sent to the DSP. The converted digital value is compared with the setpoint to obtain the difference, i.e., the system deviation. This deviation is then substituted into the integral-separated PID control algorithm for calculation. Generally, the DSP can quickly calculate the system output value and perform D/A conversion to drive the voice coil motor. The real-time performance of the system largely depends on the simplification of the control algorithm. Figure 2 shows the schematic diagram. [IMG=Schematic Diagram]/uploadpic/THESIS/2007/11/2007111615542194195B.jpg[/IMG] Figure 2 Schematic Diagram In engineering applications, the parameter tuning of the PID controller is the core content of control system design. It involves determining the proportional coefficient, integral time, and derivative time of the PID controller based on the characteristics of the controlled process. There are many methods for tuning PID controller parameters, which can be broadly categorized into two types: The first is the theoretical calculation method. This method primarily relies on the system's mathematical model to determine the controller parameters through theoretical calculations. The calculated data obtained using this method may not be directly usable and must be adjusted and modified based on practical engineering applications. The second method is the trial-and-error method. In practical applications, the trial-and-error method is more commonly used to determine PID parameters: Increasing the proportional gain P generally speeds up the system response and helps reduce steady-state error in the presence of it. However, an excessively large proportional gain can lead to significant overshoot and oscillations, worsening stability. Increasing the integral time I helps reduce overshoot and oscillations, increasing system stability, but it also lengthens the time required to eliminate steady-state error. Increasing the derivative time D speeds up the system response, reduces overshoot, and increases stability, but it weakens the system's ability to suppress disturbances. During trial-and-error, the influence of these parameters on the system control process can be considered, and parameter adjustments should follow a sequence of proportional, integral, and derivative tuning. First, tune the proportional portion. Gradually increase the proportional parameter and observe the corresponding system response until a fast-responding, low-overshoot response curve is obtained. If the system has no steady-state error or the steady-state error is already within the allowable range, and the response curve is satisfactory, then only a proportional controller is needed. If the steady-state error of the system cannot meet the design requirements based on proportional control, an integral term must be added. During tuning, first set the integral time to a relatively large value, then slightly reduce the already adjusted proportional coefficient (generally to 0.8 of the original value), and then decrease the integral time, so that the steady-state error is eliminated while maintaining good dynamic performance. During this process, the proportional coefficient and integral time can be repeatedly changed according to the quality of the system's response curve to obtain a satisfactory control process and tuning parameters. If the above adjustments to the system's dynamic process still do not yield satisfactory results, a derivative term can be added. First, set the derivative time D to 0, then gradually increase the derivative time while correspondingly changing the proportional coefficient and integral time, gradually adjusting until a satisfactory tuning effect is obtained. 5 Conclusion This paper introduces the method of using a high-speed DSP to control a voice coil motor, as well as the principle and application of the PID control algorithm. The system composed of DSP and voice coil motor features high frequency, high response, and high precision, and has high versatility. It can be easily modified to meet the needs of different applications, thus possessing significant practical value in engineering applications. (Proceedings of the 2nd and 3rd Servo and Motion Control Forums)