H∞ filtering for linear periodic systems with parameter uncertainty
Systems & Control Letters
Robust control of a class of uncertain nonlinear systems
Systems & Control Letters
Kalman filtering for linear systems with coefficients driven by a hidden Markov jump process
Systems & Control Letters
Mathematics and Computers in Simulation
Robust filtering for jumping systems with mode-dependent delays
Signal Processing
Information Sciences: an International Journal
Information Sciences: an International Journal
H∞ filtering for discrete-time systems with time-varying delay
Signal Processing
Worst case control of uncertain jumping systems with multi-state and input delay information
Information Sciences: an International Journal
Robust H/sub /spl infin// filtering for stochastic time-delay systems with missing measurements
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Robust Fuzzy Control Approach for a Class of Markovian Jump Nonlinear Systems
IEEE Transactions on Fuzzy Systems
Brief H∞ control and filtering of discrete-time stochastic systems with multiplicative noise
Automatica (Journal of IFAC)
Improved robust energy-to-peak filtering for uncertain linear systems
Signal Processing
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The peak-to-peak filtering problem is studied for a class of Markov jump systems with uncertain parameters. By re-constructing the system, the dynamic filtering error system is obtained. The objective is to design a peak-to-peak filter such that the induced L"~ gain from the unknown inputs to the estimated errors is minimized or guaranteed to be less or equal to a prescribed value. By using appropriate stochastic Lyapunov-Krasovskii functional, sufficient conditions are initially established on the existence of mode-dependent peak-to-peak filter which also guarantees the stochastic stability of the filtering error dynamic systems. The design criterions are presented in the form of linear matrix inequalities and then described as an optimization problem. Simulation results demonstrate the validity of the proposed approaches.