Publications related to Sample Complexity of Linear Quadratic Gaussian (LQG) Control for Output Feedback Systems

Memory of Motion for Initializing Optimization in Robotics

Many robotics problems are formulated as optimization problems. However, most optimization solvers in robotics are locally optimal and the performance depends a lot on the initial guess. For challenging problems, the solver will often get stuck at poor loc ...

EPFL2022

A Distributed Luenberger Observer for Linear State Feedback Systems With Quantized and Rate-Limited Communications

Colin Neil Jones, Ye Pu, Andrea Alessandretti, Francisco Fernandes Castro Rego

This article addresses the problem of simultaneous distributed state estimation, and control of linear systems with linear state feedback, subjected to process, and measurement noise, under the constraints of quantized, and rate-limited network data transm ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Learning Robustly Safe Output Feedback Controllers from Noisy Data with Performance Guarantees

Giancarlo Ferrari Trecate, Luca Furieri, Baiwei Guo, Andrea Martin

How can we synthesize a safe and near-optimal control policy for a partially-observed system, if all we are given is one historical input/output trajectory that has been corrupted by noise? To address this challenge, we suggest a novel data-driven controll ...

2021

System-level, Input-output and New Parameterizations of Stabilizing Controllers, and Their Numerical Computation

Maryam Kamgarpour, Luca Furieri, Na Li

It is known that the set of internally stabilizing controller

\mathcal{C}_{\text{stab}}

is non-convex, but it admits convex characterizations using certain closed-loop maps: a classical result is the {Youla parameterization}, and two recent notions are t ...

2020

Sparsity Invariance for Convex Design of Distributed Controllers

Maryam Kamgarpour, Luca Furieri, Yu Zheng

We address the problem of designing optimal linear time-invariant (LTI) sparse controllers for LTI systems, which corresponds to minimizing a norm of the closed-loop system subjected to sparsity constraints on the controller structure. This problem is NP-h ...

2020

From human action understanding to robot action execution: how the physical properties of handled objects modulate non-verbal cues

Aude Billard, Konstantinos Chatzilygeroudis, Nuno Ricardo Ferreira Duarte, José Santos-Victor

Humans manage to communicate action intentions in a non-verbal way, through body posture and movement. We start from this observation to investigate how a robot can decode a human's non-verbal cues during the manipulation of an object, with specific physic ...

IEEE2020

,

In this paper, a new data-driven method for designing robust controllers is proposed for systemswith sector-bounded nonlinearities and multimodel uncertainties. The results from the circle criterion are used to generate necessary and sufficient convex cons ...

WILEY2019

, ,

A new model-reference data-driven approach is presented which uses the frequency response data of a system in order to avoid the problem of unmodeled dynamics associated with low-order parametric models. It is shown that a convex optimization problem can b ...

PERGAMON-ELSEVIER SCIENCE LTD2019

A Robust Data-Driven Controller Design Methodology With Applications to Particle Accelerator Power Converters

Alireza Karimi, Achille Nicoletti, Michele Martino

A new data-driven approach using the frequency response function (FRF) of a system is proposed for designing robust-fixed structure digital controllers for particle accelerators' power converters. This design method ensures that the dynamics of a system ar ...

2019

Robust control for an electromagnetic actuator for a camless engine

Zlatina Kirilova Dimitrova

The increase of the effective efficiency of the internal combustion engines is important for the fuel consumption reduction and the CO2 emission reduction. The variable engine valve trains are important for the gas exchanges and influence directly the effe ...

PERGAMON-ELSEVIER SCIENCE LTD2019

Sample Complexity of Linear Quadratic Gaussian (LQG) Control for Output Feedback Systems

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Memory of Motion for Initializing Optimization in Robotics

A Distributed Luenberger Observer for Linear State Feedback Systems With Quantized and Rate-Limited Communications

Learning Robustly Safe Output Feedback Controllers from Noisy Data with Performance Guarantees

System-level, Input-output and New Parameterizations of Stabilizing Controllers, and Their Numerical Computation

Sparsity Invariance for Convex Design of Distributed Controllers

From human action understanding to robot action execution: how the physical properties of handled objects modulate non-verbal cues

A Robust Data-Driven Controller Design Methodology With Applications to Particle Accelerator Power Converters

Robust control for an electromagnetic actuator for a camless engine

Memory of Motion for Initializing Optimization in Robotics

System-level, Input-output and New Parameterizations of Stabilizing Controllers, and Their Numerical Computation

A Distributed Luenberger Observer for Linear State Feedback Systems With Quantized and Rate-Limited Communications

From human action understanding to robot action execution: how the physical properties of handled objects modulate non-verbal cues

Sparsity Invariance for Convex Design of Distributed Controllers

A Robust Data-Driven Controller Design Methodology With Applications to Particle Accelerator Power Converters

Robust control for an electromagnetic actuator for a camless engine

Learning Robustly Safe Output Feedback Controllers from Noisy Data with Performance Guarantees