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We introduce an adaptive moving horizon control scheme for nonlinear stochastic systems. The scheme uses the recently developed particle filter to track the hidden state, as well as to estimate unknown parameters. In addition, expected costs are approximated by Monte Carlo integration where necessary. Although computationally intensive, the scheme has wide applicability, and we demonstrate its robustness...
This paper deals with the class of uncertain continuous-time linear systems with Markovian jumps, time-delay, and saturating actuators. Under norm-bounded uncertainties and based on the Lyapunov method, a sufficient condition on stochastic stability and stochastic stabilizability are developed. A design algorithm for a stabilizing observer-based robust output feedback controller is proposed in terms...
This paper presents a stochastic method for optimal control of a class of hybrid systems with two switching instants. For this class of hybrid systems, the problem to be solved amounts to minimising a two-dimensional continuous cost function. The optimisation method exposed here is based on a convergence theoremm An algorithm is given and tried on an illustrating example.
The purpose of this paper is to construct the estimator system for the stochastic parabolic system with the free boundary. The free boundary problem is one of important nonlinear problems in engineering. The intrinsic characteristic of the free boundary problem is that the domain of the solution of the considered equation is unknown and must be determined with the solution of the considered equation...
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