Linear Time-Varying Parameter Estimation: Maximum A Posteriori Approach via Semidefinite Programming

We study the problem of identifying a linear time-varying output map from measurements and linear time-varying system states, which are perturbed with Gaussian observation noise and process uncertainty, respectively. Employing a stochastic model as prior knowledge for the parameters of the unknown output map, we reconstruct their estimates...

A linear matrix inequality approach to optimal reset control design for a class of nonlinear systems

In this article, the problem of the optimal reset control design for Lipschitz nonlinear systems is addressed. The reset controller includes a base linear controller and a reset law that enforces resets to the controller states. The reset law design is strongly dependent on the appropriate design of the base controller. For this reason, in...

Optimal reset law design based on guaranteed cost control method for Lipschitz nonlinear systems

This article proposes a systematic approach for optimal reset law design of a class of nonlinear systems. By using the guaranteed cost control method, sufficient conditions for the design of optimal reset law are derived in terms of linear matrix inequalities. In an offline design procedure, the reset law is computed that minimizes the upper...

A Lyapunov approach to stability analysis of partial synchronization in delay-coupled networks

Networks of interconnected dynamical systems may exhibit a so-called partial synchronization phenomenon, which refers to synchronous behaviors of some but not all of the systems. The patterns of partial synchronization are often characterized by partial synchronization manifolds, which are linear invariant subspace of the state space of the...

Absolute stabilization of Lur'e systems under event-triggered feedback

In this paper, we deal with event-triggered feedback control for Lur'e systems that consist of negative feedback interconnection of nominal linear dynamics and an unknown static nonlinearity. The unknown nonlinearity is conventionally assumed to lie in a given sector while the sector bounds are known. In the presence of event-triggered...

Sequential convex relaxation for convex optimization with bilinear matrix equalities

We consider the use of the nuclear norm operator, and its tendency to produce low rank results, to provide a convex relaxation of Bilinear Matrix Inequalities (BMIs). The BMI is first written as a Linear Matrix Inequality (LMI) subject to a bi-affine equality constraint and subsequently rewritten into an LMI subject to a rank constraint on a...