Litcius/Paper detail

Protocol‐based <i>H</i><sub><i>∞</i></sub> filtering for piecewise linear systems: A measurement‐dependent equivalent reduction approach

Jiajia Li, Guoliang Wei, Derui Ding, Engang Tian

2021International Journal of Robust and Nonlinear Control12 citationsDOI

Abstract

Abstract In this article, a protocol‐based H ∞ filtering problem is investigated for piecewise linear (PWL) systems with mixed delays. Stochastic access protocol (SAP) is utilized to schedule the signal transmission via a constrained communication channel, under which only one measurement value can be transmitted to the filter at each time instant following a Markov process. When SAP is applied to PWL systems, only a part of system modes can be observed due to the incomplete measurement information. Therefore, a measurement‐dependent parameter storage rule with a certain probability distribution is introduced to overcome the difficulties coming from SAP‐induced incomplete information. By resorting to the proposed mode storage rule, a novel measurement‐dependent asynchronous H ∞ filter model is constructed and the problem is converted into a new switching process of a larger state space following a reconstructed Markov process. Subsequently, a sufficient condition is established to guarantee the H ∞ performance, and the probability‐dependent filter parameters are obtained by applying the stochastic analysis technique. Finally, a numerical example is given to show the effectiveness of the design approach.

Topics & Concepts

Filter (signal processing)Asynchronous communicationControl theory (sociology)Reduction (mathematics)Piecewise linear functionComputer scienceFiltering problemMarkov chainLinear systemMarkov processSchedulePiecewiseMathematical optimizationTransmission (telecommunications)State spaceMathematicsFilter designStatisticsMathematical analysisComputer networkGeometryOperating systemControl (management)TelecommunicationsMachine learningComputer visionArtificial intelligenceStability and Control of Uncertain SystemsNeural Networks Stability and SynchronizationControl Systems and Identification