Robotics is an emerging synthetic science concerned with programming work. Robot
technologies are quickly advancing beyond the insights of the existing science. More secure …

Lyapunov functions are an essential tool in the stability analysis of dynamical systems, both
in theory and applications. They provide sufficient conditions for the stability of equilibria or …

Many existing tools in nonlinear control theory for establishing stability or safety of a
dynamical system can be distilled to the construction of a certificate function which …

Varying-parameter recurrent neural network, being a special kind of neural-dynamic
methodology, has revealed powerful abilities to handle various time-varying problems, such …

The widespread adoption of communication and control infrastructures will not only improve
the microgrid system performance in normal conditions but also increase microgrid …

In recent years, fractional-order differential operators, and the dynamic models constructed
based on these generalized operators have been widely considered in design and practical …

Most extremum-seeking control (ESC) approaches focus solely on the problem of finding the
extremum of some unknown, steady-state input–output map, providing parameter settings …

We show that the existence of a non-coercive Lyapunov function is sufficient for uniform
global asymptotic stability (UGAS) of infinite-dimensional systems with external disturbances …

In this paper we employ SMT solvers to soundly synthesise Lyapunov functions that assert
the stability of a given dynamical model. The search for a Lyapunov function is framed as the …

Abstract Stochastic Gradient Descent (SGD) has been the method of choice for learning
large-scale non-convex models. While a general analysis of when SGD works has been …