Asynchronous Networked Control With Multisensor Fusion: A Hybrid Framework for Active Suspension Optimization

Abstract

This study investigates the exponential stability and stabilization of multisensor multirate sampled-data networked control systems using the integral quadratic constraint (IQC) theory. The considered systems feature multiple sensing channels operating at different sampling rates and multiple zero-order holders with distinct update rates to better account for bandwidth and sampling rate limitations. For stability analysis, a mediated interconnected system is constructed to enable exponential stability evaluation within the IQC framework. Specifically, operator splitting and the introduction of a novel operator guarantee tighter upper bounds on the operator norms while significantly reducing the number of decision variables. For controller design, an optimization-based heuristic algorithm is proposed to determine the controller gains despite the presence of nonlinear coupling terms. Finally, the effectiveness and enhanced performance of the proposed control strategy are experimentally validated using an active suspension system.