Search Results for author:
Found 13 papers, 1 papers with code
Stability Certificates for Receding Horizon Games
Game-theoretic MPC (or Receding Horizon Games) is an emerging control methodology for multi-agent systems that generates control actions by solving a dynamic game with coupling constraints in a receding-horizon fashion.
Game-theoretic Model Predictive Control for Modelling Competitive Supply Chains
Supply chains transform raw materials into finished goods and distribute them to end consumers.
Layer-to-Layer Melt Pool Control in Laser Power Bed Fusion
Additive manufacturing processes are flexible and efficient technologies for producing complex geometries.
Sequential Quadratic Programming-based Iterative Learning Control for Nonlinear Systems
We present simulations to illustrate the performance of the proposed method for linear and nonlinear dynamics models.
Stochastic Wasserstein Gradient Flows using Streaming Data with an Application in Predictive Maintenance
Since estimation problems can be posed as optimization problems in the probability space, we devise a stochastic projected Wasserstein gradient flow that keeps track of the belief of the estimated quantity and can consume samples from online data.
Drone-based Volume Estimation in Indoor Environments
Volume estimation in large indoor spaces is an important challenge in robotic inspection of industrial warehouses.
Stability and Robustness of Distributed Suboptimal Model Predictive Control
In distributed model predictive control (MPC), the control input at each sampling time is computed by solving a large-scale optimal control problem (OCP) over a finite horizon using distributed algorithms.
Receding Horizon Games with Coupling Constraints for Demand-Side Management
Distributed energy storage and flexible loads are essential tools for ensuring stable and robust operation of the power grid in spite of the challenges arising from the integration of volatile renewable energy generation and increasing peak loads due to widespread electrification.
Data-driven Reference Trajectory Optimization for Precision Motion Systems
We propose a data-driven optimization-based pre-compensation method to improve the contour tracking performance of precision motion stages by modifying the reference trajectory and without modifying any built-in low-level controllers.
On Robustness in Optimization-Based Constrained Iterative Learning Control
Iterative learning control (ILC) is a control strategy for repetitive tasks wherein information from previous runs is leveraged to improve future performance.
In-layer Thermal Control of a Multi-layer Selective Laser Melting Process
Selective Laser Melting (SLM) is an additive manufacturing technology that builds three dimensional parts by melting layers of metal powder together with a laser that traces out a desired geometry.
Cross-layer Design for Real-Time Grid Operation: Estimation, Optimization and Power Flow
In this paper, we propose a combined Online Feedback Optimization (OFO) and dynamic estimation approach for a real-time power grid operation under time-varying conditions.
FBstab: A proximally stabilized semismooth algorithm for convex quadratic programming
This paper introduces the proximally stabilized Fischer-Burmeister method (FBstab); a new algorithm for convex quadratic programming which synergistically combines the proximal point algorithm with a semismooth Newton-type method.
Optimization and Control 90C20, 49M15, 65K05, 65K10
