1 citations · 2 across the 15 of their papers we have counts for
5 papers · 1 filter
Learning deep Koopman operators with convex stability constraints
Marc Mitjans, Liangting Wu, Roberto Tron
In this paper, we present a novel sufficient condition for the stability of discrete-time linear systems that can be represented as a set of piecewise linear constraints, which mak…
Spline Trajectory Tracking and Obstacle Avoidance for Mobile Agents via Convex Optimization
Akua Dickson, Christos G. Cassandras, Roberto Tron
We propose an output feedback control-based motion planning technique for agents to enable them to converge to a specified polynomial trajectory while imposing a set of safety cons…
Designing Robust Linear Output Feedback Controller based on CLF-CBF framework via Linear~Programming(LP-CLF-CBF)
Mahroo Bahreinian, Mehdi Kermanshah, Roberto Tron
We consider the problem of designing output feedback controllers that use measurements from a set of landmarks to navigate through a cell-decomposable environment using duality, Co…
Lyapunov Neural Network with Region of Attraction Search
Zili Wang, Sean B. Andersson, Roberto Tron
Deep learning methods have been widely used in robotic applications, making learning-enabled control design for complex nonlinear systems a promising direction. Although deep reinf…
Control-Based Planning over Probability Mass Function Measurements via Robust Linear Programming
Mehdi Kermanshah, Calin Belta, Roberto Tron
We propose an approach to synthesize linear feedback controllers for linear systems in polygonal environments. Our method focuses on designing a robust controller that can account…