Abstract
A novel proportional–integral–derivative neural network (PIDNN) controller is proposed to replace the PI controller, which is adopted in conventional high-frequency signal injection to improve the speed estimating performance for start-up and low speeds of the interior permanent magnet synchronous motor (IPMSM) used in DC inverter-fed compressor drive systems. Moreover, two sensorless control schemes are also proposed for the IPMSM drive system. One is the high-frequency signal injection method combined with the commutation-signal-based (CSB) speed estimation method, and the other is the high-frequency signal injection method combined with the model reference adaptive system (MRAS) speed estimation method. Both sensorless control schemes use high-frequency signal injection as the start-up strategy to achieve sinusoidal starting. When the motor speed gradually increases to a preset speed, the sensorless drive will switch to the CSB speed estimation method or the MRAS speed estimation method for high-speed control. The theories of the high-frequency signal injection method, the CSB and MRAS speed estimation methods and the PIDNN controller are introduced in detail. Furthermore, a DSP-based computer control system is developed to implement the sensorless DC inverter-fed compressor drive system and some experimental results are given to verify the feasibility of the proposed control schemes.
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