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.