75 citations · 194 across the 24 of their papers we have counts for
26 papers
Path planning with moving obstacles using stochastic optimal control
Seyyed Reza Jafari, Anders Hansson, Bo Wahlberg
Navigating a collision-free and optimal trajectory for a robot is a challenging task, particularly in environments with moving obstacles such as humans. We formulate this problem a…
Time-Optimal Path Tracking for Cooperative Manipulators: A Convex Optimization Approach
Hamed Haghshenas, Anders Hansson, Mikael Norrlöf
This paper studies the time-optimal path tracking problem for a team of cooperating robotic manipulators carrying an object. Considering the problem for rigidly grasped objects, we…
On the Search for Equilibrium Points of Switched Affine Systems
Lucas N. Egidio, Anders Hansson
One of the main aspects of switched affine systems that makes their stabilizability study intricate is the existence of (generally) infinitely many equilibrium points in the state…
Learning the Step-size Policy for the Limited-Memory Broyden-Fletcher-Goldfarb-Shanno Algorithm
Lucas N. Egidio, Anders Hansson, Bo Wahlberg
We consider the problem of how to learn a step-size policy for the Limited-Memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm. This is a limited computational memory quasi-…
Efficient Robust Model Predictive Control using Chordality
Anders Hansson, Sina Khoshfetrat Pakazad
In this paper we show that chordal structure can be used to devise efficient optimization methods for robust model predictive control problems. The chordal structure is used both f…
Exploiting Chordality in Optimization Algorithms for Model Predictive Control
Anders Hansson, Sina Khoshfetrat Pakazad
In this chapter we show that chordal structure can be used to devise efficient optimization methods for many common model predictive control problems. The chordal structure is used…
Distributed, scalable and gossip-free consensus optimization with application to data analysis
Sina Khoshfetrat Pakazad, Christian A. Naesseth, Fredrik Lindsten +1
Distributed algorithms for solving additive or consensus optimization problems commonly rely on first-order or proximal splitting methods. These algorithms generally come with rest…
Subspace Identification of Large-Scale 1D Homogeneous Networks
Chengpu Yu, Michel Verhaegen, Anders Hansson
This paper considers the identification of large-scale 1D networks consisting of identical LTI dynamical systems. A new subspace identification method is developed that only uses l…
Distributed Localization of Tree-structured Scattered Sensor Networks
Sina Khoshfetrat Pakazad, Emre Özkan, Carsten Fritsche +2
Many of the distributed localization algorithms are based on relaxed optimization formulations of the localization problem. These algorithms commonly rely on first-order optimizati…
A Scalable and Distributed Solution to the Inertial Motion Capture Problem
Manon Kok, Sina Khoshfetrat Pakazad, Thomas B. Schön +2
In inertial motion capture, a multitude of body segments are equipped with inertial sensors, consisting of 3D accelerometers and 3D gyroscopes. Using an optimization-based approach…
Automated Model Generation for Analysis of Large-scale Interconnected Uncertain Systems
Farzaneh Karami, Sina Khoshfetrat Pakazad, Anders Hansson +1
The first challenge in robustness analysis of large-scale interconnected uncertain systems is to provide a model of such systems in a standard-form that is required within differen…
Distributed Semidefinite Programming with Application to Large-scale System Analysis
Sina Khoshfetrat Pakazad, Anders Hansson, Martin S. Andersen +1
Distributed algorithms for solving coupled semidefinite programs (SDPs) commonly require many iterations to converge. They also put high computational demand on the computational a…
Distributed Primal-dual Interior-point Methods for Solving Loosely Coupled Problems Using Message Passing
Sina Khoshfetrat Pakazad, Anders Hansson, Martin S. Andersen
In this paper, we propose a distributed algorithm for solving loosely coupled problems with chordal sparsity which relies on primal-dual interior-point methods. We achieve this by…
N2SID: Nuclear Norm Subspace Identification
Michel Verhaegen, Anders Hansson
The identification of multivariable state space models in innovation form is solved in a subspace identification framework using convex nuclear norm optimization. The convex optimi…
A distributed primal-dual interior-point method for loosely coupled problems using ADMM
Mariette Annergren, Sina Khoshfetrat Pakazad, Anders Hansson +1
In this paper we propose an efficient distributed algorithm for solving loosely coupled convex optimization problems. The algorithm is based on a primal-dual interior-point method…
Distributed System Identification with ADMM
Anders Hansson, Michel Verhaegen
This paper presents identification of both network connected systems as well as distributed systems governed by PDEs in the framework of distributed optimization via the Alternatin…
Distributed Robustness Analysis of Interconnected Uncertain Systems Using Chordal Decomposition
Sina Khoshfetrat Pakazad, Anders Hansson, Martin S. Andersen +1
Large-scale interconnected uncertain systems commonly have large state and uncertainty dimensions. Aside from the heavy computational cost of solving centralized robust stability a…
Nuclear Norm Subspace Identification (N2SID) for short data batches
Michel Verhaegen, Anders Hansson
Subspace identification is revisited in the scope of nuclear norm minimization methods. It is shown that essential structural knowledge about the unknown data matrices in the data…
Distributed Interior-point Method for Loosely Coupled Problems
Sina Khoshfetrat Pakazad, Anders Hansson, Martin S. Andersen
In this paper, we put forth distributed algorithms for solving loosely coupled unconstrained and constrained optimization problems. Such problems are usually solved using algorithm…
Robust Stability Analysis of Sparsely Interconnected Uncertain Systems
Martin S. Andersen, Sina Khoshfetrat Pakazad, Anders Hansson +1
In this paper, we consider robust stability analysis of large-scale sparsely interconnected uncertain systems. By modeling the interconnections among the subsystems with integral q…
Reduced-Complexity Semidefinite Relaxations of Optimal Power Flow Problems
Martin S. Andersen, Anders Hansson, Lieven Vandenberghe
We propose a new method for generating semidefinite relaxations of optimal power flow problems. The method is based on chordal conversion techniques: by dropping some equality cons…
Distributed Solutions for Loosely Coupled Feasibility Problems Using Proximal Splitting Methods
Sina Khoshfetrat Pakazad, Martin S. Andersen, Anders Hansson
In this paper, we consider convex feasibility problems where the underlying sets are loosely coupled, and we propose several algorithms to solve such problems in a distributed mann…
Distributed Robust Stability Analysis of Interconnected Uncertain Systems
Martin S. Andersen, Anders Hansson, Sina Khoshfetrat Pakazad +1
This paper considers robust stability analysis of a large network of interconnected uncertain systems. To avoid analyzing the entire network as a single large, lumped system, we mo…
Speed Tracking of a Linear Induction Motor - Enumerative Nonlinear Model Predictive Control
Jean Thomas, Anders Hansson
Direct torque control is considered as one of the most efficient techniques for speed and/or position tracking control of induction motor drives. However, this control scheme has s…