Abstract
In this paper, the event-triggered $\boldsymbol {H}_{\boldsymbol \infty }$ state estimation problem is investigated for a two-degree-of-freedom quarter-car suspension system operated over a switching-channel network environment. First, the channel-switching is governed by a nonhomogeneous Markov chain whose probability transition matrix is time-varying. Then, a Markov jump linear system model is adopted to represent the overall networked system in view of the event-triggered communication scheme, signal quantization and random packet losses on account of the limited network bandwidth. By virtue of the Lyapunov functional and linear matrix inequality method, the event-triggered $\boldsymbol {H}_{\boldsymbol \infty }$ state estimation problem is transformed into an optimization problem that switching-channel-dependent estimators are designed such that the estimation error system is exponentially stable in the mean square sense and achieves a desired performance level. Finally, a simulation example is used to demonstrate the validity of proposed design method.
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