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Abstract-This technical note presents a solution to the problem of regulating a general nonlinear dynamical system to an economically optimal operating point. The system is characterized by a set of exogenous inputs as an abstraction of time-varying loads and disturbances. The economically optimal operating point is implicitly defined as a solution to a given constrained convex optimization problem, which is related to steady-state operation. The system outputs and the exogenous inputs represent respectively the decision variables and the parameters in the optimization problem. The proposed solution is based on a specific dynamic extension of the Karush-Kuhn-Tucker optimality conditions for the steady-state related optimization problem, which is conceptually related to the continuous-time Arrow-Hurwicz-Uzawa algorithm. Furthermore, it can be interpreted as a generalization of the standard output regulation problem with respect to a constant reference signal.

Abstract-This paper deals with stabilization of interconnected discrete-time nonlinear systems under given, arbitrary information constraints on the controller structure. As a prominent example, the considered information constraints on the controller structure include decentralized and distributed control over a given communication network. The main contribution of this paper is twofold. Firstly, we introduce the notion of structured control Lyapunov functions (CLFs) as a suitable tool for stabilizing controller synthesis under information constraints. This includes the relaxation of Lyapunov conditions at the local level. Secondly, we present a method for constructing structured CLFs and we show that the controller synthesis problem using structured CLFs can be formulated as a convex optimization problem. Possible solutions for solving this problem efficiently under several different types of information constraints are also indicated.

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