1. Introduction
With the development of industrial technology, there are more and more occasions in aviation, military, and mechanical manufacturing fields where multiple motors are needed to drive one or more working parts simultaneously for coordinated control. Traditional control systems mostly use a single motor to achieve single-axis control. The output torque of the motor is limited. When the transmission system requires a large driving power, a special drive motor and driver with matching power must be made, which increases the cost of the system. Moreover, motors with excessive output power are affected by manufacturing process and motor performance. The development of high-power drivers is also limited by semiconductor power devices [1]. While the motor is following the same target speed in real time, it is also necessary to keep the speed of the two motors synchronized. Otherwise, the accuracy of the subsequent mechanical transmission will decrease. The solution to the above problems is to use multiple motors to control them. However, the quality of synchronization between multiple motors directly affects production efficiency and product quality. Therefore, the research on multi-motor synchronous control has very important practical significance [2].
This paper establishes a simulation model of a dual-motor deviation coupling control algorithm based on SVPWM variable frequency speed regulation, and performs simulation using Matlab 7.1 simulation software. The simulation results are analyzed and compared.
2. Space Vector Pulse Width Modulation
Pulse width modulation (PWM) technology is the main measure for frequency converters to suppress harmonics. Sine wave PWM (SPWM) technology was first adopted and has been used ever since. After continuous improvement, it has achieved remarkable results. However, it still has shortcomings, such as low DC voltage utilization, torque ripple at low speeds, and large switching losses due to excessively high carrier frequency [3]. Space vector pulse width modulation proposed by German scholar Van Der-Broeck HW fundamentally solved the problem of high-performance control of AC motor torque [4].
Its basic idea is to simulate the torque control law of DC motor on a three-phase AC motor. On the magnetic field orientation coordinate, the stator current vector is decomposed into the excitation current component IM that generates magnetic flux and the torque current component IT that generates torque. The two components are perpendicular to each other and independent of each other, and are adjusted separately to realize torque control [5]. SVPWM regards the inverter and AC motor as one, focusing on how to make the motor obtain a circular rotating magnetic field to reduce the torque pulsation of the motor. Specifically, it takes the ideal magnetic flux circle of the AC motor stator when the three-phase symmetrical sinusoidal voltage is supplied as the reference. When the motor is supplied with a three-phase symmetrical sinusoidal voltage, a circular magnetic flux is generated in the AC motor. SVPWM uses this circular magnetic flux as the reference and generates an effective voltage vector through different switching modes of the inverter power devices to approximate the reference circle, that is, to approximate the circle with a polygon. The result of their comparison determines the inverter switching state and forms a PWM wave [6].
3. Synchronous Control Model of Two Motors Based on MATLAB
3.1 Dual-motor synchronous control strategy
The existing synchronous control technologies include parallel control, master-slave control, cross-coupling control, and deviation coupling control. Parallel control and master-slave control are non-cross-coupling synchronous control. When the load changes, the synchronization accuracy between motors cannot be guaranteed. The main feature of cross-coupling control is to compare the speed or position signals of two motors to obtain a difference as an additional feedback signal. Using this additional feedback signal as a tracking signal, the system can reflect the load change of any motor, thereby obtaining good synchronous control accuracy. However, this control strategy is not suitable for the synchronous control of more than two motors. The main idea of deviation coupling control is to subtract the speed feedback of one motor from the speed feedback of other motors, and then add the resulting deviations as the speed compensation signal of that motor. This deviation coupling control strategy can overcome the shortcomings of the above control strategies and achieve good synchronization performance [7].
3.2 Deviation Coupled PID Control System
PID control is highly robust, offering excellent control performance and robustness for most processes. Its algorithm is simple, the physical meaning of the parameters is clear, its theoretical analysis system is complete, and its application experience is rich. Therefore, a PID controller can be used to address the system's requirement for interference suppression. A dual-closed-loop design is employed for single-motor control, using SVPWM for speed regulation to ensure good system stability. The simulation diagram of the SVPWM speed regulation module is shown in Figure 1. The speed difference fed back from the two motors is then calculated and used as additional compensation for speed feedback when the load changes. The system simulation model is shown in Figure 2.
4. Analysis of System Simulation Results
The system uses an AC permanent magnet synchronous motor (PMSM) and the model in this paper is simulated using Simulink.
In the MATLAB 7.1 system, the main parameters of the motor model used are: stator resistance Rs = 0.0918Ω, quadrature-axis and direct-axis stator inductance Ld = Lq = 0.000975H, rotor magnetic flux λ = 0.1688Wb, moment of inertia J = 0.003945kg·m², viscous friction coefficient B = 0.0004924N·m·s, and number of pole pairs P = 4.
The motor speed was set to 400 r/min, allowing for a zero-load start-up. The simulation time was set to 0.2 s. To verify the impact of load changes on the system and the tracking performance of the dual motors, a load torque of TM = 20 N·m was suddenly applied to PMSM2 at t = 0.05 s. The simulation results are shown in Figure 3.
As shown in Figure 3, the motor quickly reaches a stable state after startup, with the rotor speed stabilizing at 400 r/min. When a sudden load torque is applied to the PMSM2 motor, the PMSM2 speed drops briefly before quickly stabilizing, with the torque remaining constant at 20 N·m.
The speed of PMSM1 was slightly reduced due to the change in the load of PMSM2, but quickly recovered to a stable state. The torque also fluctuated slightly before rapidly stabilizing. This indicates that the PID dual-closed-loop control system based on SVPWM speed regulation has strong robustness, and the deviation coupling compensation strategy between the two motors demonstrates good following performance when the load of one motor changes.
5. Conclusion
The system incorporates a PID control compensator on top of the deviation coupling control strategy, enabling excellent synchronous control. Each motor employs a dedicated controller and speed compensation module, with speed regulation via SVPWM. A dual closed-loop control system (current loop and speed loop) is used, where each motor and its controller form a closed-loop system. Subsystems are coupled through the speed compensation module, creating a complete control system and enhancing its anti-interference capabilities. Simulation results show that the SVPWM-based PID dual closed-loop system exhibits low overshoot, rapid response, and strong robustness, while the dual-motor control system with the deviation coupling control strategy demonstrates excellent synchronization.
