Motivated by bridging the simulation to reality gap in the context of
sa...
A key assumption in the theory of adaptive control for nonlinear systems...
We combine adaptive control directly with optimal or near-optimal value
...
Real-time adaptation is imperative to the control of robots operating in...
Precise motion planning and control require accurate models which are of...
We study the problem of adaptively controlling a known discrete-time
non...
This work proposes a quaternion-based sliding variable that describes
ex...
We present neural stochastic contraction metrics, a new design framework...
Many existing tools in nonlinear control theory for establishing stabili...
Generalized linear models (GLMs) extend linear regression by generating ...
In this work, we consider a group of robots working together to manipula...
A set of new adaptive control algorithms is presented. The algorithms ar...
We propose a novel framework for learning stabilizable nonlinear dynamic...
Synchronization in distributed networks of nonlinear dynamical systems p...
We propose a novel framework for learning stabilizable nonlinear dynamic...
We present an algorithm to characterize the space of identifiable inerti...