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System identification with binary or quantized measurements is a problem relevant to a number of applications in different fields. While identification of FIR models has been studied in depth, more complex model structures still need to be investigated. In this paper, identification of ARX models with quantized measurements is addressed in a set membership setting. In particular, the problem of characterizing...
In this paper we provide sufficient conditions for regional asymptotic and nonlinear ℒ2m gain estimation of linear systems subject to saturations and/or deadzones, based on piecewise polynomial Lyapunov functions. By using sum-of-squares relaxations, these conditions are formulated in terms of linear matrix inequalities for the global case, and bilinear ones for the regional case. The results are...
This paper analyzes two classes of consensus algorithms in presence of bounded measurement errors. The protocols taken into account adopt an updating rule based either on constant or vanishing weights. The bounded error assumption allows one to cast the consensus problem in a set-membership framework, and to study the team agreement in terms of the evolution of the feasible state set. It is shown...
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