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In order to solve the problem that the dynamic control performance of permanent magnet synchronous motor is poor when PI(proportional-integral) control strategy is used in vector control, and the motor parameters are easily affected by changes in external temperature and load, which leads to poor precision and responsiveness of the control motor, a model predictive control method is proposed to control the motor. This strategy uses the system model to predict the future input and state of the system, and directly calculates the control input by optimizing the objective function, which significantly improves the dynamic performance and steady-state accuracy. Moreover, with its strong ability to deal with nonlinearity and parameter changes, it can control the nonlinear system of permanent magnet synchronous motor well. According to the waveform diagram obtained by simulation, model predictive control is superior to PI control in dynamic response, anti-interference ability, low speed performance and robustness. Therefore, using model predictive control can effectively improve the control performance of permanent magnet synchronous motor.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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