Publications related to Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Robust and Agile 3D Biped Walking With Steering Capability Using a Footstep Predictive Approach

Auke Ijspeert, Salman Faraji, Soha Pouya

In this paper, we formulate a novel hierarchical controller for walking of torque controlled humanoid robots. Our method uses a whole body optimization approach which generates joint torques, given Cartesian accelerations of different points on the robot. ...

2014

Open-loop control of a separated boundary layer

François Gallaire, Edouard Boujo

Linear optimal gains

G_{opt}(\omega)

are computed for the separated boundary-layer flow past a two-dimensional bump in the subcritical regime. Very large values are found, making it possible for small-amplitude noise to be strongly amplified and to desta ...

Elsevier France-Editions Scientifiques Medicales Elsevier2014

Soft Constrained Model Predictive Control With Robust Stability Guarantees

Colin Neil Jones, Melanie Nicole Zeilinger

Soft constrained model predictive control (MPC) is frequently applied in practice in order to ensure feasibility of the optimization during online operation. Standard techniques offer global feasibility by relaxing state or output constraints, but cannot e ...

Institute of Electrical and Electronics Engineers2014

On real-time robust model predictive control

Colin Neil Jones, Melanie Nicole Zeilinger

High-speed applications impose a hard real-time constraint on the solution of a model predictive control (MPC) problem, which generally prevents the computation of the optimal control input. As a result, in most MPC implementations guarantees on feasibilit ...

Elsevier2014

Fixed-order Discrete-time LPV Controller Design

Alireza Karimi, Zlatko Emedi

A new method for the design of fixed-order dynamic output-feedback Linear Parameter Varying (LPV) controllers for discrete-time LPV systems with bounded scheduling parameter variations is presented in this paper. Sufficient conditions for the stability, H2 ...

2014

Adaptive Penalty-Based Distributed Stochastic Convex Optimization

Ali H. Sayed

In this work, we study the task of distributed optimization over a network of learners in which each learner possesses a convex cost function, a set of affine equality constraints, and a set of convex inequality constraints. We propose a fully distributed ...

Institute of Electrical and Electronics Engineers2014

Plug-and-Play Model Predictive Control based on robust control invariant sets

Giancarlo Ferrari Trecate, Marcello Farina

We consider the problem of designing decentralized controllers for large-scale linear constrained systems composed by a number of interacting subsystems. As in (Riverso et al., 2013) (i) the design of local controllers requires limited transmission of info ...

2014

A simple relaying strategy for diamond networks

Christina Fragouli, Siddhartha Brahma

We consider a Gaussian diamond network where a source communicates with the destination through n non-interfering half-duplex relays. Using simple approximations to the capacity of the network, we show that simple relaying strategies involving two relays a ...

Ieee2014

H-Infinity Gain-Scheduled Controller Design for Rejection of Time-Varying Disturbances with Application to an Active Suspension System

Alireza Karimi, Zlatko Emedi

A new method for H-infinity gain-scheduled controller design by convex optimization is proposed that uses only frequency-domain data. The method is based on loop shaping in the Nyquist diagram with constraints on the weighted infinity norm of closed-loop t ...

2013

H infinity Gain-scheduled Controller Design for Rejection of Time-varying Narrow-band Disturbances Applied to a Benchmark Problem

Alireza Karimi, Zlatko Emedi

A new method for H-infinity gain-scheduled controller design by convex optimization is proposed that uses only frequency-domain data. The method is based on loop shaping in the Nyquist diagram with constraints on the weighted infinity-norm of closed-loop t ...

Lavoisier2013

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

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Robust and Agile 3D Biped Walking With Steering Capability Using a Footstep Predictive Approach

Open-loop control of a separated boundary layer

Soft Constrained Model Predictive Control With Robust Stability Guarantees

On real-time robust model predictive control

Fixed-order Discrete-time LPV Controller Design

Adaptive Penalty-Based Distributed Stochastic Convex Optimization

Plug-and-Play Model Predictive Control based on robust control invariant sets

A simple relaying strategy for diamond networks

H-Infinity Gain-Scheduled Controller Design for Rejection of Time-Varying Disturbances with Application to an Active Suspension System

H infinity Gain-scheduled Controller Design for Rejection of Time-varying Narrow-band Disturbances Applied to a Benchmark Problem

Open-loop control of a separated boundary layer

Robust and Agile 3D Biped Walking With Steering Capability Using a Footstep Predictive Approach

Fixed-order Discrete-time LPV Controller Design

Adaptive Penalty-Based Distributed Stochastic Convex Optimization

H infinity Gain-scheduled Controller Design for Rejection of Time-varying Narrow-band Disturbances Applied to a Benchmark Problem

A simple relaying strategy for diamond networks

Soft Constrained Model Predictive Control With Robust Stability Guarantees

On real-time robust model predictive control

Plug-and-Play Model Predictive Control based on robust control invariant sets

H-Infinity Gain-Scheduled Controller Design for Rejection of Time-Varying Disturbances with Application to an Active Suspension System