The paper presents conditions for the stability of a dynamical network described by a directed graph, whose nodes represent dynamical systems characterised by the same transfer function F(s) and whose edges account for the interactions between pairs of nodes. In turn, these interactions depend via a transference G(s) on the outputs of the subsystems associated with the connected nodes. The stability conditions are topology-independent, in that they hold for all possible connections of the nodes, and robust, in that they allow for uncertainties in the determination of the transferences. Two types of interactions are considered: bidirectional and unidirectional. In the first case, if nodes i and j are connected, both node i affects node j and node j affects node i, while in the second case only one of the two occurrences is admitted. The robust stability conditions are expressed as constraints for the Nyquist diagram of H = FG.@en

The paper presents and analyses some nonlinear continuous-time dynamic models of social systems whose members, groups or individuals, may change partners and/or opponents at any time, according to a greedy criterion. The main structural properties of these models, which belong to the class of positive switching systems, are investigated with particular regard to the existence of solutions, their positivity, boundedness and asymptotic behaviour. Simulations show how the cooperative or hostile attitudes of the participants affect their yield.@en

A multi-agent continuous-time nonlinear model of social behaviour allowing for both competition and cooperation is presented and analysed. The state of each agent is represented by its payoff, which the agent aims at maximising. The role of control variables is played by the model parameters, which account for the agents' decisions to either cooperate with or boycott the other agents and can vary in time within assigned intervals. Alliances and enmities can be established at any time, according to either a greedy or a longsighted criterion. The general nonlinear case is first considered. It is proved that, under realistic assumptions, the system evolution is bounded positive (no extinction) and there is a unique globally-stable equilibrium point. As is somehow expected, the optimal decision for all agents corresponds to full cooperation (decision parameters kept at their positive maximum value) in the case of both shortsighted and farsighted criteria. This is not true if some parameters have negative upper bounds (meaning that some agents systematically boycott some others). Then, in the linear case, it is shown that the system is stable for arbitrarily-varying decision parameters, provided that a Metzler matrix associated with full cooperation is Hurwitz. A characterisation of the long-term behaviour of the linear system is also provided. In particular, it is proved that, under stability conditions, a Nash equilibrium exists if a steady strategy is adopted.@en

This paper investigates the topology-independent stability of homogeneous dynamical networks, composed of interconnected equal systems. Precisely, dynamical systems with identical nominal transfer function F(s) are associated with the nodes of a directed graph, whose arcs account for their dynamic interactions, described by a common nominal transfer function G(s). It is shown that topology-independent stability is guaranteed for all possible interconnections with interaction degree (defined as the maximum number of arcs leaving a node) equal at most to N if the ∞-norm of the complementary sensitivity function NF(s)G(s)[1+NF(s)G(s)]-1 is less than 1. This bound is nonconservative in that there exist graphs with interaction degree N that are unstable for an ∞-norm greater than 1. When nodes and arcs transferences are affected by uncertainties with norm bound K> 0, topology-independent stability is robustly ensured if the ∞-norm is less than 1/(1+2NK). For symmetric systems, stability is guaranteed for all topologies with interaction degree at most N if the Nyquist plot of NF(s)G(s) does not intersect the real axis to the left of-1/2. The proposed results are applied to fluid networks and platoon formation.@en

A major drawback hinders the application of Model Predictive Control (MPC) to the regulation of electromechanical systems or, more generally, systems with fast dynamics: the time needed for the online computation of the control is often too long with respect to the sampling time. This paper shows how this problem can be overcome by suitably implementing the MPC technique. The main idea is to compute the control law using the discrete-time Euler Auxiliary System (EAS) associated with the continuous-time plant, and apply the control obtained for the discrete-time system to the continuous-time system. In this way the implementation sampling time can be much smaller than the EAS time parameter, which leads to significant savings in computation time. Theoretical results guarantee stabilisation, constraint satisfaction and robustness of such a control strategy, which is applied to the control of an electric drive and a cart-pendulum system.@en

The paper analyses some continuous-time dynamic models that describe the evolution of social systems characterized by the possibility of changing the alliances among the parties involved or damaging one's competitors. At any time each participant, either an individual or a coalition, can decide to form or terminate a bond, or to start or stop damaging an opponent (i.e., to switch from a network configuration to another), based on a greedy, or shortsighted, criterion that does not consider the long-term effects of the decision. The proposed models fall within the domain of positive switching systems. Although they can obviously simulate the behaviour of many real-life situations, in which contenders aim at prevailing over one another to achieve supremacy, the paper does not refer to a specific context and concentrates on the main structural properties of the mathematical models, such as positivity and boundedness of the solutions, existence of coalitions, steady-state behaviour. Simulations show how the different cooperative or hostile attitudes of the participants affect their yield.@en