Control of Nonlinear Elastic Joint Robots using Feed-forward Torque Decoupling

Decoupling based Cartesian impedance control of flexible joint robots

This paper addresses the impedance control problem for flexible joint manipulators. An impedance controller structure is proposed, which is based on an exact decoupling of the torque dynamics from the link dynamics. A formal stability analysis of the proposed controller is presented for the general tracking case. Preliminary experimental results are given for a single flexible joint.

Cartesian Impedance Control of Flexible Joint Robots: A Decoupling Approach

Nonlinear H Control for Uncertain Flexible Joint Robots with Unscented Kalman Filter

Todays, use of combination of two or more methods was considered to control of systems. In this paper ispresented how to design of a nonlinear H∞ (NL-H∞) controller for flexible joint robot (FJR) based on boundedUKF state estimator. The UKF has more advantages to standard EKF such as low bios and no need toderivations. In this research, based on spong primary model for FJRs, same as rigid robot...

Actuation Torque Reduction in Parallel Robots Using Joint Compliance

This work studies in detail how the judicial application of compliance in parallel manipulators can produce manipulators that require significantly lower actuator effort within a range of desired operating conditions. We propose a framework that uses the Jacobian matrices of redundant parallel manipulators to consider the influence of compliance both in parallel with the actuated joints as well...

Locally Weighted Learning Model Predictive Control for Elastic Joint Robots

This paper proposes an efficient and online learning control system that uses the successful Model Predictive Control (MPC) method in a model based locally weighted learning framework. The new approach named Locally Weighted Learning Model Predictive Control (LWL-MPC) has been proposed as a solution to learn to control complex and nonlinear Elastic Joint Robots (EJR). Elastic Joint Robots are g...