Cooperative Control of Dynamical Systems and Its Robustness Analysis

Model‐independent consensus control of Euler‐Lagrange agents with interconnecting delays

“…Moreover, the integral of this function is also saturated. These facts force us to employ nonlinear springs between the variables q and given as saturation functions of the difference of these variables (see (7) and the proportional term in (9)). Notice that the term B included in (7) is intended to render possible consensus in the variables belonging to the different agents.…”

“…This and the fact that . and − q are bounded ensure thaẗis bounded (see (7)). Thus, invoking Corollary 1, we conclude that…”

“…Examples of important research directions include coverage control, consensus, formation control, and flocking. [6][7][8] The objective of consensus control is to design distributed protocols based on local relative information to guarantee the states of all agents to reach an agreement. 9 Consensus can be classified as follows: (1) leaderless consensus, when the consensus or agreement configuration is not specified 10 ; (2) leader-follower consensus, when the consensus configuration is specified as the constant configuration of an additional agent known as the leader 10 ; (3) tracking consensus, when the leader configuration is time-varying 11 ; and (4) containment control, when the group of followers has to be driven to the convex hull spanned by multiple leaders.…”

Cooperative Control of Dynamical Systems

“…As shown in Section 4.2, all the results presented have their graphical explanations and can be visually as explicit as a graph. In terms of analysis and design, the matrix theoretical approach has the advantage that heterogeneous systems of high relative-degree can be handled [202], control Lyapunov function can be found [205], and robustness can be analyzed [209].…”

Connectivity maintenance and distributed tracking for double‐integrator agents with bounded potential functions

“…A look back in history is the classical model proposed by Reynolds [1], where three simple local rules, that is, separation, cohesion, and alignment, successfully imitated many behaviors of flocks/schools/herds by computer [1]. Many algorithms related to these rules have been developed and analyzed recently [2][3][4][5][6], to name a few, in which a common inherent condition is the connectivity of the underlying communication network. The connectivity condition could be a valid assumption for static or state-independent switching topology.…”