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This paper discusses the tracking coordination of a linear switched reluctance machine (LSRM) network based on a global feedback control strategy with a full-state observation framework. The observer is allocated on the follower instead of the leader to form a leader--follower--observer network, by utilizing the leader as the global feedback tracking controller and the observer as the observation of the full states. The internal model compensator (IMC) is applied to the leader for the improvement of the network performance. The full-state information of the LSRM network is reconfigured by the output of the LSRM where the observer is located to provide necessary feedback information to the leader. Then, the controllability and observability of the leader--follower--observer network with the IMC are inspected, serving as a basis for the design of the global controller with the IMC and full-state observer. Experimentation verifies the effectiveness of the proposed network control scheme and the results demonstrate that both the absolute and the relative accuracy can be simultaneously improved, compared to the LSRM network with only the consensus algorithm and no global feedback mechanism. [ABSTRACT FROM AUTHOR]

This paper investigates the controllability of a closed-loop tracking synchronization network based on multiple linear-switched reluctance machines (LSRMs). The LSRM network is constructed from a global closed-loop manner, and the closed loop only replies to the input and output information from the leader node. Then, each local LSRM node is modeled as a general second-order system, and the model parameters are derived by the online system identification method based on the least square method. Next, to guarantee the LSRM network's controllability condition, a theorem is deduced that clarifies the relationship among the LSRM network's controllability, the graph controllability of the network and the controllability of the node dynamics. A state feedback control strategy with the state observer located on the leader is then proposed to improve the tracking performance of the LSRM network. Last, both the simulation and experiment results prove the effectiveness of the network controller design scheme and the results also verify that the leader-based global feedback strategy not only improves the tracking performance but also enhances the synchronization accuracy of the LSRM network experimentally. [ABSTRACT FROM AUTHOR]

This paper investigates a distributed, coordinated motion control network based on multiple direct-drive, linear switched reluctance machines (LSRMs). A hierarchical, two-level synchronization control strategy is proposed for the four LSRMs based motion control network. The high-level, reference signals agreement algorithm is first employed to correct the asynchronous behaviors of the position commands. Then, the low-level tracking synchronization method is applied for the collaborative position control of the four LSRMs. The proposed two-level, fault-tolerant control strategy eliminates the asynchrony of the reference signals and it also guarantees the coordinated tracking control performance of the four LSRMs. Experimental results demonstrate that effective coordinated tracking control can be ensured, based on the successful agreement of reference signals and an absolute tracking error falling within 2 mm can be achieved. [ABSTRACT FROM AUTHOR]