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20162022
most citedTracking Control by the Newton-Raphson Method with Output Prediction and Controller Speedup

4 citations · 16 across the 16 of their papers we have counts for

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8 papers · 1 filter

math.OC2020

Integral Control Barrier Functions for Dynamically Defined Control Laws

Aaron D. Ames, Gennaro Notomista, Yorai Wardi +1

This paper introduces integral control barrier functions (I-CBFs) as a means to enable the safety-critical integral control of nonlinear systems. Importantly, I-CBFs allow for the…

math.OC20194 cited

Tracking Control by the Newton-Raphson Method with Output Prediction and Controller Speedup

Yorai Wardi, Carla Seatzu, Jorge Cortes +3

This paper presents a control technique for output tracking of reference signals in continuous-time dynamical systems. The technique is comprised of the following three elements: (…

math.OC20194 cited

Path Planning in Unknown Environments Using Optimal Transport Theory

Haoyan Zhai, Magnus Egerstedt, Haomin Zhou

This paper introduces a graph-based, potential-guided method for path planning problems in unknown environments, where obstacles are unknown until the robots are in close proximity…

math.OC2019

Collective motion planning for a group of robots using intermittent diffusion

Christina Frederick, Magnus Egerstedt, Haomin Zhou

In this work we establish a simple yet effective strategy, based on optimal transport theory, for enabling a group of robots to accomplish complex tasks, such as shape formation an…

math.OC2018

Permissive Barrier Certificates for Safe Stabilization Using Sum-of-squares

Li Wang, Dongkun Han, Magnus Egerstedt

Motivated by the need to simultaneously guarantee safety and stability of safety-critical dynamical systems, we construct permissive barrier certificates in this paper that explici…

math.OC20172 cited

Differentially Private Cloud-Based Multi-Agent Optimization with Constraints

Matthew Hale, Magnus Egerstedt

We present an optimization framework that solves constrained multi-agent optimization problems while keeping each agent's state differentially private. The agents in the network se…