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In this paper control of high index or even non-regular linear descriptor systems subject to general quadratic constraints is considered. This setup especially includes the H∞ control problem and the design for strict passivity. In a previous paper [9] this problem was addressed by a linearizing change of variables approach under a certain assumption on the structure of the algebraic equations within...
Models of biochemical reaction networks can be decomposed into a stoichiometric part and a kinetic part. The stoichiometric part describes the structural mass flows while the kinetic part describes how the flow rates vary with substrate concentrations and regulatory interactions. Herein a method for analyzing the robustness of biochemical networks with respect to perturbations of the kinetic part...
This paper considers a linear precoding for a Kalman filter which receives the measurements over an erasure channel. We show how to design the precoding matrix that either robustifies the Kalman filter with respect to packet losses or reduces the estimation error. The effectiveness of the proposed method is demonstrated by two examples.
This article is concerned with the assessment and derivation of (best) linear models for nonlinear systems. We introduce a general framework reminiscent of uncertainty descriptions in linear robust control theory in order to define a family of six model quality indices for linear models of nonlinear systems. Each quality index corresponds to the gain of an error system, where the nonlinear system...
In this paper two model predictive control (MPC) approaches, an on-line and an off-line MPC approach, for constrained uncertain continuous-time systems with piecewise constant control input are presented. Both MPC approaches guarantee robust asymptotic stability by taking into account the hybrid dynamics of the closed-loop system, resulting from the continuous-time system dynamics and the discrete-time...
We consider the Lscr2-gain of nonlinear Port-Hamiltonian systems. Using the Hamiltonian and an additional scaling matrix, we show that an upper bound on the Lscr2-gain can be computed by solving a matrix inequality. The Lscr2-gain is typically used in combination with the small-gain theorem. In particular it can be used to guarantee robust stability with respect to gain-bounded model uncertainties...
This paper provides a novel solution to the problem of robust output feedback model predictive control of constrained, linear, discrete-time systems in the presence of additive but bounded state and output disturbances. The overall controller consists of two components, a stable state estimator and a tube based, robustly stabilizing model predictive controller. The proposed robust output-feedback...
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