Abstract
In this paper, a novel control scheme with respect to the adaptive decoupling controller based on radial basis function neural network (ADEC-RBFNN) is developed. On one hand, in order to improve the system performance of the torque closed-loop control system (TCLCS) of the permanent magnet synchronous motor (PMSM) with the effects of the dynamic coupling and back electromotive force (EMF), we present a novel ADEC with which the TCLCS is asymptotically stable under Lyapunov stability theory. On the other hand, considering the uncertainty and time variant of both the PMSM and ADEC parameters, the RBFNN is utilized to optimize the ADEC parameters to achieve optimal system performance. Ultimately, experimental results demonstrate that the torque and current with the proposed control scheme have the good performance of small fluctuation and fast response in the whole ranges of the speed and torque, that is to say, the system with the proposed control scheme is with the good decoupling performance.
Highlights
Due to the advantages of simple structure, small volume, high power density, high efficiency, high reliability, and fast response, the permanent magnet synchronous motor (PMSM) has been extensively applied in various fields such as the ship propulsion system, electric vehicle, and industrial control [1], [2]
EXPERIMENTAL RESULTS In order to demonstrate the effectiveness of the proposed adaptive decoupling controller (ADEC)-RBFNN control scheme, an experimental bench of the torque closed-loop control system (TCLCS) of the PMSM is built
The AC induction motor works in speed mode to adjust the speed of the TCLCS, and the proposed ADEC-RBFNN control scheme shown in Fig. 3 is implemented in the controller
Summary
Due to the advantages of simple structure, small volume, high power density, high efficiency, high reliability, and fast response, the permanent magnet synchronous motor (PMSM) has been extensively applied in various fields such as the ship propulsion system, electric vehicle, and industrial control [1], [2]. The dynamic coupling terms, back EMF term, and uncertain and time-varying motor parameters inevitably lead to the poor system performance of large torque fluctuation, large current fluctuation, slow torque response, and slow current response, especially when the PMSM is operated in the high speed condition, and the torque and speed are changed rapidly. In [8], a deviation decoupling method is proposed to improve the dynamic performance of TCLCS of the PMSM. In [9], the coupling terms are modeled as disturbances and are observed These observed disturbances are used in the control laws to improve the dynamic performance. These methods are simple and easy to implement.
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