Self-Correcting Quadratic Programming-Based Robot Control

Multi-robot and task-space force control with quadratic programming

We extend the task-space multi-objective controllers that write as quadratic programs (QP) to handle multi-robot systems as a single centralized control. The idea is to assemble all the ‘robots’ models and their interaction task constraints into a single QP formulation. By multi-robot we mean that whatever entities a given robot will interact with (solid or articulated systems, actuated or not ...

Optimization-based Robot Compliance Control: Geometric and Linear Quadratic Approaches

Impedance control is a compliance control strategy capable of accommodating both unconstrained and constrained motions. The performance of impedance controllers depends heavily upon environment dynamics and the choice of target impedance. To maintain performance for a wide range of environments, target impedance needs to be adjusted adaptively. In this paper, a geometric view on impedance contr...

Robot Control and Programming

Experimental characterization and quadratic programming-based control of brushless-motors

A new torque control strategy for brushless motors is presented, which results in minimum torque ripple and copper losses. The motor model assumes linear magnetics, but contains a current limit which can delimit the onset of magnetic saturation, or be the motor amplifier current limit, whichever is reached first. The control problem is formulated and solved as a quadratic programming problem wi...

Genetic Algorithm – Quadratic Programming Based Predictive Control for Mld Systems

The Mixed Logical Dynamical (MLD) formalism is an efficient modeling framework for hybrid systems described by dynamics, logic and constraints. Furthermore, it allows solving practical problems such as control using for example predictive strategies. However, its main drawback remains the computation load due to the MIQPs to be solved. This paper proposes an alternative optimization technique b...