Abstract
This paper discusses the control of the linear switched reluctance machines (LSRMs) network for the zero phase-difference tracking to a sinusoidal reference. The dynamics of each LSRM is derived by online system identification and modeled as a second-order linear system. Accordingly, based on the coupled harmonic oscillators synchronization manner, a distributed control strategy is proposed to synchronize each LSRM state to a virtual LSRM node representing the external sinusoidal reference for tracking it with zero phase-difference. Subsequently, a simulation scenario and an experimental platform with the identical parameter setup are designed to investigate the tracking performance of the LSRMs network constructed by the proposed distributed control strategy. Finally, the simulation and experimental results verify the effectiveness of the proposed LSRMs network controller, and also prove that the coupled harmonic oscillators synchronization method can improve the synchronization tracking performance and precision.
Highlights
Linear tracking control systems based on direct drive linear machines are vastly used in the manufacturing industry, such as parts assembly, printed circuit boarding (PCB) drilling and chip processing, etc
The results demonstrate that the linear switched reluctance machines (LSRMs) network has successfully achieved the stable state without phase-difference after 10s
A distributed control strategy of the LSRMs network is proposed for tracking a sinusoidal reference in a zero phase-difference manner
Summary
Linear tracking control systems based on direct drive linear machines are vastly used in the manufacturing industry, such as parts assembly, printed circuit boarding (PCB) drilling and chip processing, etc. Multi-agent network study has been classified into several major aspects, which include constrained or imperfect communication [12], delay or switching information linkage [13,14], agents with nonlinear dynamics [15], influence of noise [16], etc., the multi-agent networks bound by distributed control algorithms have been exploited in the regime of spacecraft cluster [17], robot coordination [18], and unmanned aerial vehicle formation [19] It can be concluded from the above analysis that current theoretical work mainly concentrates on distributed control methods to achieve the network synchronization under some network topology constraint condition. The distributed tracking control performance for the LSRMs network is investigated by a simulation and experimental platform testing
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