Abstract
The system considered in this article operates with a feedback that is characterized by a gain and a desired final state (DFS), which is the main parameter of interest in this article. The system is, however, subjected intermittently to stochastic inputs according to a Markov process. Since the system operates in two modes—under the feedback to the DFS and under a stochastic input—an interacting multiple model estimator is designed to handle the unknown DFS to be estimated (mode <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$M_{1}$</tex-math></inline-formula> ) and the random inputs (mode <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$M_{2}$</tex-math></inline-formula> ). Simulation results explore several scenarios and investigate the degree of observability of this stochastic problem
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