Networkbased control of a semilinear damped beam equation under point and pointlike measurements Abstract   We consider distributed static outputfeedback stabilization of a damped semilinear beam equation. Distributed in space measurements are either point or pointlike, where a pointlike measurement is the state value averaged on a small subdomain. Networkbased implementation of the control law which enters the PDE through shape functions is studied, where variable sampling intervals and transmission delays are taken into account. Our main objective is to derive and compare the results under both types of measurements in terms of the upper bound on the delays and sampling intervals that preserve the stability for the same (as small as possible) number of sensorsactuators. For locally Lipschitz nonlinearities, regional stabilization is achieved. Numerical results show that the pointlike measurements lead to larger delays and samplings, provided the subdomains, where these measurements are averaged, are not too small.

A Sparse Polytopic LPV Controller for FullyDistributed Nonlinear Optimal Control. In this paper we deal with distributed optimal control for nonlinear dynamical systems over graph, that is largescale systems in which the dynamics of each subsystem depends on neighboring states only. Starting from a previous work in which we designed a partially distributed solution based on a cloud, here we propose a fullydistributed algorithm. The key novelty of the approach in this paper is the design of a sparse controller to stabilize trajectories of the nonlinear system at each iteration of the distributed algorithm. The proposed controller is based on the design of a stabilizing controller for polytopic Linear Parameter Varying (LPV) systems satisfying nonconvex sparsity constraints. Thanks to a suitable choice of vertex matrices and to an iterative procedure using convex approximations of the nonconvex matrix problem, we are able to design a controller in which each agent can locally compute the feedback gains at each iteration by simply combining coefficients of some vertex matrices that can be precomputed offline. We show the effectiveness of the strategy on simulations performed on a multiagent formation control problem.