Force control of a non-backdrivable robot without a force sensor

2013 ◽  
Author(s):  
Zihan Chen ◽  
Peter Kazanzides
Keyword(s):  
Force Control ◽  
Force Sensor

Force Controlled Manipulation of Biological Cells Using a Monolithic MEMS Based Nano-Micro Gripper

2012 ◽  
Author(s):  
Ali A. Abbasi ◽  
M. T. Ahmadian
Keyword(s):  
Liquid Medium ◽  
Force Control ◽  
Force Sensor ◽  
Rapid Response ◽  
Pid Controllers ◽  
Biological Cells ◽  
Matlab Software ◽  
Micro Gripper ◽  
The Future ◽  
Geometrical Dimensions

Nano-micro grippers are able to pick-transport-place the micro or nanometer–sized materials, such as manipulation of biological cells or DNA molecules in a liquid medium. This paper proposes a novel monolithic nano-micro gripper structure with two axis piezoresistive force sensor which its resolution is under nanoNewton. The results of the study have been obtained by the simulation of the proposed gripper structure in Matlab software. Motion of the gripper arm is produced by a voice coil actuator. The behavior of the cell has been derived using the assumptions in the literatures. Moreover, two simple PID controllers, one for control of the gripper motion and another for control of the force during manipulation of a biologic cell, have been implemented. Although the proposed gripper has not been fabricated, since the geometrical dimensions of the proposed gripper is the same as previously developed electrothermally actuated micro-nano gripper, the results of force control have been also compared with it. The simulated results with the very simple PID force controller which has a more rapid response than previously developed electrothermally actuated micro-nano gripper show that the designed gripper has the potential to be considered and fabricated for manipulation of biological cells in the future.

scholarly journals An Adaptive Sliding-Mode Iterative Constant-force Control Method for Robotic Belt Grinding Based on a One-Dimensional Force Sensor

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1635 ◽  
Author(s):  
Tie Zhang ◽  
Ye Yu ◽  
Yanbiao Zou
Keyword(s):  
Force Control ◽  
Control Method ◽  
Sliding Mode ◽  
Force Sensor ◽  
Grinding Force ◽  
One Dimension ◽  
Constant Force ◽  
Belt Grinding ◽  
Robotic Belt Grinding ◽  
The Relationship

To improve the processing quality and efficiency of robotic belt grinding, an adaptive sliding-mode iterative constant-force control method for a 6-DOF robotic belt grinding platform is proposed based on a one-dimension force sensor. In the investigation, first, the relationship between the normal and the tangential forces of the grinding contact force is revealed, and a simplified grinding force mapping relationship is presented for the application to one-dimension force sensors. Next, the relationship between the deformation and the grinding depth during the grinding is discussed, and a deformation-based dynamic model describing robotic belt grinding is established. Then, aiming at an application scene of robot belt grinding, an adaptive iterative learning method is put forward, which is combined with sliding mode control to overcome the uncertainty of the grinding force and improve the stability of the control system. Finally, some experiments were carried out and the results show that, after ten times iterations, the grinding force fluctuation becomes less than 2N, the mean value, standard deviation and variance of the grinding force error’s absolute value all significantly decrease, and that the surface quality of the machined parts significantly improves. All these demonstrate that the proposed force control method is effective and that the proposed algorithm is fast in convergence and strong in adaptability.

A Force-Control Model for Edge-Deburring with Filamentary Brush

1999 ◽  
Vol 123 (3) ◽  
pp. 528-532 ◽  
Author(s):  
Lienjing Chen ◽  
Robert J. Stango ◽  
Vikram Cariapa
Keyword(s):  
Force Control ◽  
Material Removal ◽  
Complete Removal ◽  
Force Sensor ◽  
Control Model ◽  
Master Curves ◽  
Machining Performance ◽  
Unknown Variable ◽  
Machining Force ◽  
On Line

In this paper a force-control model is developed for edge deburring with filamentary brushes. The model is based upon experimentally obtained “master curves,” that is, material removal data that corresponds to the actual machining performance of the brush/workpart system during the incremental burr removal process. This information is used in conjunction with the on-line brush machining force to compute the brush feed rate that ensures complete removal of the edge burr. Computer simulated results are reported for the removal of an edge burr having unknown variable height. The results indicate that the present force-control model can provide a straight forward approach for computing brush feed rates that lead to complete removal of edge burrs, and suggests that implementation can be carried out using a force sensor and a simple control strategy.

Force Control of Robot Manipulator by Neural Network Model - Experiment and Evaluation of One-Degree-of-Freedom Manipulator -

1990 ◽  
Vol 2 (4) ◽  
pp. 273-281 ◽  
Author(s):  
Masatoshi Tokita ◽  
◽  
Toyokazu Mitsuoka ◽  
Toshio Fukuda ◽  
Takashi Kurihara ◽  
...  
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Force Control ◽  
Pid Controller ◽  
Robot Manipulator ◽  
Force Sensor ◽  
Robotic Manipulator ◽  
The Neural Network ◽  
The Stability

In this paper, a force control of a robotic manipulator based on a neural network model is proposed with consideration of the dynamics of both the force sensor and objects. This proposed system consists of the standard PID controller, the gains of which are augmented and adjusted depending on objects through a process of learning. The authors proposed a similar method previously for the force control of the robotic manipulator with consideration of dynamics of objects, but without consideration of dynamics of the force sensor, showing only simulation results. This paper shows the similar structure of the controller via the neural network model applicable to the cases with consideration of both effects and demonstrates that the proposed method shows the better performance than the conventional PID type of controller, yielding to the wider range of applications, consequently. Therefore, this method can be applied to the force/compliance control problems. The effects of the number of neurons and hidden layers of the neural network model are also discussed through the simulation and experimental results as well as the stability of the control system.

Wave Variable Based Force Control

2007 ◽  
Author(s):  
J. Scot Hart ◽  
Gu¨nter Niemeyer
Keyword(s):  
Time Delay ◽  
Force Control ◽  
Time Delays ◽  
Communication Channel ◽  
Force Feedback ◽  
Low Frequency ◽  
Force Sensor ◽  
Wave Variable ◽  
Communication Time ◽  
Frictional Forces

Wave variable controllers maintain passive communication across time delays in telerobotics. As passive elements, wave variable controllers interact well with other passive elements, such as P.D. controllers and masses, and use a combination of force and velocity signals to apply force feedback. Currently we are exploring the use of wave variable controllers with large non-backdrivable industrial-type slave devices where dynamics are dominated by inertial and frictional forces. The objective is to integrate force sensor measurements into wave variable controllers to provide low frequency force feedback and hide the slave’s friction and inertia from the user in the presence of a communication time delay. This paper presents and uses a wave variable based approach to design force control. The resulting wave variable based force controller is converted to power variables and shown to be similar to traditional force controllers. A 1-DOF telerobotic system is used to experimentally show the wave variable based force control combines with the enhanced stability properties of the wave communication channel to produce robust slave side force control. The resulting system is better able to maintain force control with rigid environments then a traditional controller both with and without communication time delay.

Trajectory and Force Control of a Manipulator with Elastic Links

2004 ◽  
Vol 10 (9) ◽  
pp. 1271-1289 ◽  
Author(s):  
Katsuyoshi Tsujita ◽  
Kazuo Tsuchiya ◽  
Takateru Urakubo ◽  
Zenta Sugawara
Keyword(s):  
Control System ◽  
Force Control ◽  
Inverse Kinematics ◽  
Inverse Dynamics ◽  
Equations Of Motion ◽  
Force Sensor ◽  
Feedback Controller ◽  
Lagrangian Multiplier ◽  
Elastic Links ◽  
Feedforward Controller

This paper deals with trajectory and force control of a two-link manipulator with elastic links. The manipulator has a macro–micro mechanism and at the tip of which is an end-effector with a force sensor. Equations of motion are first derived by using a finite-element method for the elastic deformations. Then, by eliminating the residual modes based on the eigenvalue analysis, the reduced-order equations for controller design are derived. Geometrical constraints are modeled by using a Lagrangian multiplier. The proposed control system consists of a feedforward controller and a feedback controller. The feedforward controller generates the input torques and force based on inverse dynamics. It also generates the reference signals for the feedback controller based on inverse kinematics. The calculation methods for inverse dynamics and inverse kinematics are based on the algorithm that we have proposed. The performance of the proposed control system is verified by numerical simulations and hardware experiments.

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