Simulation study demonstrates improved estimation accuracy and reduced communication rates in discrete-time LPV systems, highlighting utility for resource-constrained environments.
This paper proposes an implicit event‐triggered set membership estimator (IET‐SME) for discrete‐time LPV systems subject to bounded uncertainties. By extracting implicit information from non‐triggering conditions via support functions, virtual measurement updates are constructed to restrain zonotope uncertainty growth during communication silences. A co‐design framework jointly tunes observer gains and triggering matrices and derives an ‐type index for the ultimate estimation‐error bound. Simulations on vehicle dynamics and an 8‐dimensional mass‐spring benchmark show that the IET‐SME improves estimation accuracy while reducing communication rates, demonstrating its effectiveness in scenarios with limited communication resources.
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Zhang et al. (2026) studied this question.
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