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Payload-specific vibration control may be suitable for a particular task butlacks generality and transferability required for adapting to the variouspayload. Self-decoupling and robust vibration control are the crucial problemsto achieve payload-agnostic vibration control. However, there are problemsstill unsolved.  In this article, we present a maglev vibration isolation platform (MVIP),which aims to attenuate vibration in the payload-agnostic task under a dynamicenvironment. Since efforts trying to suppress disturbance will encounterinevitable coupling problems, we analyzed the reasons resulting in it andproposed unique and effective solutions.  To achieve payload-agnostic vibration control, we proposed a new controlstrategy, which is the main contribution of this article. It consists of aself-construct radial basis function neural network inversion (SRBFNNI)decoupling scheme and hybrid adaptive feed-forward internal model control(HAFIMC). The former one enables the MVIP to create a self inverse model withlittle prior knowledge and achieving self-decoupling. For the unique structureof MVIP, the vibration control problem is stated and addressed by the proposedHAFIMC, which utilizes the adaptive part to deal with the periodicaldisturbance and the internal mode part to deal with the stability.

Payload-agnostic Decoupling and Hybrid Vibration Isolation Control for a Maglev Platform with Redundant Actuation