A reflection of our ultimate understanding of a complex system is our ability to control its
behavior. Typically, control has multiple prerequisites: it requires an accurate map of the …

Contraction theory is an analytical tool to study differential dynamics of a non-autonomous
(ie, time-varying) nonlinear system under a contraction metric defined with a uniformly …

In this article, a robot skills learning framework is developed, which considers both motion
modeling and execution. In order to enable the robot to learn skills from demonstrations, a …

A virtual synchronous generator (VSG) control based on adaptive virtual inertia is proposed
to improve dynamic frequency regulation of microgrid. When the system frequency deviates …

The emergence of synchronization in a network of coupled oscillators is a fascinating
subject of multidisciplinary research. This survey reviews the vast literature on the theory …

The ultimate proof of our understanding of natural or technological systems is reflected in
our ability to control them. Although control theory offers mathematical tools for steering …

Retrograde tracer injections in 29 of the 91 areas of the macaque cerebral cortex revealed
1,615 interareal pathways, a third of which have not previously been reported. A weight …

Controlling complex networks is of paramount importance in science and engineering.
Despite the recent development of structural controllability theory, we continue to lack a …

In this chapter we present a state space interpretation of the small gain and passivity
approach of the previous chapter. Moreover, we will come to some kind of synthesis …

The problem of controlling locomotion is an area in which neuroscience and robotics can
fruitfully interact. In this article, I will review research carried out on locomotor central pattern …