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This paper deals with the state filtering problem of nonlinear state-space functions with partial parameters unknown. A novel filtering algorithm is proposed based on a modified maximum likelihood method. Using a new likelihood probabilistic function, we obtain a two-stages strategy of Expectation and Maximization (EM) with the help of Monte Carlo method. The convergence of EM parameter updating strategy...
The paper addresses the problem of state estimation using the measurement output of a mobile pointwise sensor for a class of nonlinear distributed parameter systems, which are modeled by a scalar semi-linear parabolic partial differential equation. A Lyapunov-based co-design method is proposed for simultaneous design of the guidance law of the mobile sensor and the distributed-parameter Luenberger...
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