Publications (4)2.72 Total impact
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Article: Central suboptimal
Int. J. Systems Science. 01/2011; 42:709-716. -
Conference Proceeding: Central suboptimal H∞ filter design for nonlinear polynomial systems with multiplicative noise.
Proceedings of the 49th IEEE Conference on Decision and Control, CDC 2010, December 15-17, 2010, Atlanta, Georgia, USA; 01/2010 -
Article: Central suboptimal H∞ filtering for nonlinear polynomial systems with multiplicative noise
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ABSTRACT: This paper presents the central finite-dimensional H∞ filter for nonlinear polynomial systems with multiplicative noise, that is suboptimal for a given threshold γ with respect to a modified Bolza–Meyer quadratic criterion including the attenuation control term with the opposite sign. In contrast to the previously obtained results, the paper reduces the original H∞ filtering problem to the corresponding optimal H2 filtering problem, using the technique proposed in [1]. The paper presents the central suboptimal H∞ filter for the general case of nonlinear polynomial systems with multiplicative noise, based on the optimal H2 filter given in [31]. The central suboptimal H∞ filter is also derived in a closed finite-dimensional form for third (and less) degree polynomial system states. Numerical simulations are conducted to verify performance of the designed central suboptimal filter for nonlinear polynomial systems against the central suboptimal H∞ filters available for polynomial systems with state-independent noise and the corresponding linearized system.Journal of the Franklin Institute 347(9):1740-1754. · 2.72 Impact Factor -
Article: Mean-square optimal controller for stochastic polynomial systems with multiplicative noise
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ABSTRACT: This paper presents the mean-square optimal quadratic-Gaussian controller for stochastic polynomial sys-tems with a polynomial multiplicative noise, a linear control input, and a quadratic criterion over linear observations. The optimal closed-form controller equations are obtained using the separation principle, whose applicability to the considered problem is substantiated. As an intermediate result, the paper gives a closed-form solution of the optimal regulator (control) problem for stochastic polynomial systems with a polynomial multiplicative noise, a linear control input, and a quadratic criterion. Performance of the obtained optimal controller is ver-ified in the illustrative example against the conventional LQG controller that is optimal for linearized systems. Simulation graphs demonstrating overall performance and computational accuracy of the designed optimal controller are included.
