scholarly journals Position/Force Control of Manipulator in Contact with Flexible Environment

2019 ◽  
Vol 13 (1) ◽  
pp. 16-22 ◽  
Author(s):  
Piotr Gierlak
Keyword(s):  
Neural Networks ◽  
Significant Influence ◽  
Contact Surface ◽  
Force Control ◽  
Tracking Control ◽  
Control Algorithm ◽  
Control Law ◽  
Controlled System ◽  
End Effector ◽  
Control Purpose

Abstract The paper presents the issue position/force control of a manipulator in contact with the flexible environment. It consists of the realisation of manipulator end-effector motion on the environment surface with the simultaneous appliance of desired pressure on the surface. The paper considers the case of a flexible environment when its deformation occurs under the pressure, which has a significant influence on the control purpose realisation. The article presents the model of the controlled system and the problem of tracking control with the use of neural networks. The control algorithm includes contact surface flexibility in order to improve control quality. The article presents the results of numerical simulations, which indicate the correctness of the applied control law.

Robot force control without dynamic model: theory and experiments

Robotica ◽  
2012 ◽  
Vol 31 (1) ◽  
pp. 149-171 ◽  
Author(s):  
Juan C. Rivera-Dueñas ◽  
Marco A. Arteaga-Pérez
Keyword(s):  
Model Theory ◽  
Contact Surface ◽  
Force Control ◽  
Control Algorithm ◽  
Velocity Measurements ◽  
Unit Quaternion ◽  
End Effector ◽  
Simulation Results ◽  
The Many ◽  
Theory And Experiments

SUMMARYAmong the many challenges to deal with, when a robot is interacting with its environment, friction at the contact surface and/or at the joints is one of the most important to be considered. In this paper we propose a control algorithm for the tracking of position and force (unconstrained orientation case only) of a manipulator end-effector that does not require the robot model for implementation. This characteristic has the advantage of making it capable to compensate friction effects without any previous estimation. Furthermore, no velocity measurements are needed, and the unit quaternion is employed for orientation control. Experimental and simulation results are provided.

Dynamic trajectory-tracking control method of robotic transcranial magnetic stimulation with end-effector gravity compensation based on force sensors

2018 ◽  
Vol 45 (6) ◽  
pp. 722-731
Author(s):  
ZeCai Lin ◽  
Wang Xin ◽  
Jian Yang ◽  
Zhang QingPei ◽  
Lu ZongJie
Keyword(s):  
Neural Networks ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Magnetic Stimulation ◽  
Control Method ◽  
Gravity Compensation ◽  
Trajectory Tracking Control ◽  
End Effector ◽  
Content Type ◽  
Dynamic Trajectory

Purpose This paper aims to propose a dynamic trajectory-tracking control method for robotic transcranial magnetic stimulation (TMS), based on force sensors, which follows the dynamic movement of the patient’s head during treatment. Design/methodology/approach First, end-effector gravity compensation methods based on kinematics and back-propagation (BP) neural networks are presented and compared. Second, a dynamic trajectory-tracking method is tested using force/position hybrid control. Finally, an adaptive proportional-derivative (PD) controller is adopted to make pose corrections. All the methods are designed for robotic TMS systems. Findings The gravity compensation method, based on BP neural networks for end-effectors, is proposed due to the different zero drifts in different sensors’ postures, modeling errors in the kinematics and the effects of other uncertain factors on the accuracy of gravity compensation. Results indicate that accuracy is improved using this method and the computing load is significantly reduced. The pose correction of the robotic manipulator can be achieved using an adaptive PD hybrid force/position controller. Originality/value A BP neural network-based gravity compensation method is developed and compared with traditional kinematic methods. The adaptive PD control strategy is designed to make the necessary pose corrections more effectively. The proposed methods are verified on a robotic TMS system. Experimental results indicate that the system is effective and flexible for the dynamic trajectory-tracking control of manipulator applications.

Multi-Level Phase Shift (MLPS) Control Enabled Variable Displacement Gerotor/Geroler

2007 ◽  
Author(s):  
QingHui Yuan ◽  
Brian Armstrong
Keyword(s):  
Phase Shift ◽  
Tracking Control ◽  
Control Algorithm ◽  
Control Law ◽  
Family Selection ◽  
Control Scheme ◽  
Variable Displacement ◽  
Multi Level ◽  
Velocity Tracking ◽  
Peak Value

The research focuses on enabling gerotor/geroler, a traditional fixed displacement device, with the variable displacement capability by integrating electronically controlled digital valves and the corresponding control algorithm. Each digital valve controls polarity of each corresponding chamber of the fixed displacement device. A novel Multi-Level Phase Shift (MLPS) control scheme is developed such that the instantaneous displacement of such a system can be controlled. This control law is characteristic of classifying all the possible valve configuration into several displacement families where the peak value within each family would be identical. Given a desired displacement, both displacement family selection and phase shift technology are utilized to achieve better performance. In the experimental study, MLPS control has been verified, and successfully achieves a closed loop velocity tracking control of a hydraulic geroler motor.

Obstacle avoidance control for redundant manipulators using collidability measure

Robotica ◽  
2000 ◽  
Vol 18 (2) ◽  
pp. 143-151 ◽  
Author(s):  
Su Il Choi ◽  
Byung Kook Kim
Keyword(s):  
Obstacle Avoidance ◽  
Control Algorithm ◽  
Null Space ◽  
Control Law ◽  
Redundant Manipulators ◽  
Redundancy Resolution ◽  
End Effector ◽  
Joint Torques ◽  
Avoidance Control ◽  
Joint Acceleration

We present an efficient obstacle avoidance control algorithm for redundant manipulators using a new measure called collidability measure. Considering moving directions of manipulator links, the collidability measure is defined as the sum of inverse of predicted collision distances between links and obstacles: This measure is suitable for obstacle avoidance since directions of moving links are as important as distances to obstacles. For kinematic or dynamic redundancy resolution, null space control is utilized to avoid obstacles by minimizing the collidability measure: We present a velocity-bounded kinematic control law which allows reasonably large gains to improve the system performance. Also, by clarifying decomposition in the joint acceleration level, we present a simple dynamic control law with bounded joint torques which guarantees tracking of a given end-effector trajectory and improves a kinematic cost function such as collidability measure. Simulation results are presented to illustrate the effectiveness of the proposed algorithm.

scholarly journals Position-force control of mobile manipulator – nonadaptive and adaptive case

2017 ◽  
Vol 27 (4) ◽  
pp. 487-503 ◽  
Author(s):  
Mirela Kaczmarek ◽  
Wojciech Domski ◽  
Alicja Mazur
Keyword(s):  
Force Control ◽  
Control Algorithm ◽  
Parametric Uncertainty ◽  
Mobile Manipulator ◽  
Control Law ◽  
Mobile Manipulators ◽  
Constrained Dynamics ◽  
Holonomic Constraint ◽  
System A ◽  
Theoretical Considerations

AbstractThis article presents a control algorithm for nonholonomic mobile manipulators with a simple, geometric holonomic constraint imposed on the robot’s arm. A mathematical model in generalized, auxiliary and linearized coordinates is presented, as well as the constrained dynamics of the robotic system. A position-force control law is proposed, both for the fully known robot’s model, as well as for the model with parametric uncertainty in the dynamics. Theoretical considerations are supported by the results of computer simulations.

scholarly journals Adaptive Reinforcement Learning-Enhanced Motion/Force Control Strategy for Multirobot Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Phuong Nam Dao ◽  
Duy Khanh Do ◽  
Dinh Khue Nguyen
Keyword(s):  
Reinforcement Learning ◽  
Force Control ◽  
Tracking Control ◽  
Dynamic Control ◽  
Additional Term ◽  
Control Law ◽  
Force Coefficient ◽  
Constraint Force ◽  
Control Scheme ◽  
Force Tracking

This paper presents an adaptive reinforcement learning- (ARL-) based motion/force tracking control scheme consisting of the optimal motion dynamic control law and force control scheme for multimanipulator systems. Specifically, a new additional term and appropriate state vector are employed in designing the ARL technique for time-varying dynamical systems with online actor/critic algorithm to be established by minimizing the squared Bellman error. Additionally, the force control law is designed after obtaining the computation of constraint force coefficient by the Moore–Penrose pseudo-inverse matrix. The tracking effectiveness of the ARL-based optimal control is verified in the closed-loop system by theoretical analysis. Finally, simulation studies are conducted on a system of three manipulators to validate the physical realization of the proposed optimal tracking control design.

scholarly journals An optimization algorithm for a better PID controller

2014 ◽  
Vol 17 (2) ◽  
pp. 5-12
Author(s):  
Tung Thanh Luu ◽  
Nhan Le
Keyword(s):  
Differential Equations ◽  
Optimization Algorithm ◽  
Pid Controller ◽  
Control Algorithm ◽  
Equations Of Motion ◽  
Control Law ◽  
End Effector ◽  
Precise Position ◽  
Accurate Model ◽  
The Stability

A controller of a manipulator has studied and discussed for many years. However, many problems in controlling the precise position of the end effector are still continuing to be studied. To solve the precision of the Robot, two problems are attended. The first thing is to find the accuracy model of dynamics. The second thing is a controller for control law. However, it is so difficult to find an accurate model or differential equations of motion which is similar to the true manipulator. In addition, some unknown influences on the manipulator will make the accurate differential equations unworthy. Thus, a control algorithm will be introduced with PID controller which coefficients Kp, Kd, Ki are compensated by compensator found from optimization algorithm. With the new algorithm, the results have proved the stability and precision are better.

Design and Simulation of Space Deformable-Contact-Surface-Based End Effector

2013 ◽  
Vol 631-632 ◽  
pp. 1166-1171
Author(s):  
Huang Ran ◽  
Qian Xiang Zhou ◽  
Zhong Qi Liu
Keyword(s):  
Contact Surface ◽  
Force Control ◽  
Space Station ◽  
Matlab Software ◽  
End Effector ◽  
The Poor ◽  
The Future

It is common to use space arm for maintaining and assembling. The major technology problems to solve first are the deformability, the soft and tightening contact with the target. Use ER as the contactor of end effector which is learned from the space station end effector can overcome many problems, as the poor location precision and uncontainable attitude which is bring by the big space arm. The design of multi-DOF Deformable-Contact-Surface-Based shape adaptive end effector is introduced in this text. The simulation result by Matlab software proves the design not only can tight connect the target, but also can suppress vibration and meet the precise demand of location, precise force control and deformability. It can meet the multi-mission in the future.

Human Step Rehabilitation Using a Robot Attached to the Pelvis

2004 ◽  
Author(s):  
D. Aoyagi ◽  
W. E. Inchinose ◽  
D. J. Reinkensmeyer ◽  
J. E. Bobrow
Keyword(s):  
Force Control ◽  
Control Algorithm ◽  
Control Law ◽  
Task Space ◽  
Control Laws ◽  
Position Feedback ◽  
Pelvic Motion ◽  
Linear Force ◽  
And Control ◽  
Piston Chamber

This paper describes a new robot capable of manipulating pelvic motion during human step training on a treadmill. The robot, PAM (Pelvic Assist Manipulator), uses two pneumatically actuated subsystems arranged in a tripod configuration to measure and control the pelvis of a person during body weight supported stepping on a treadmill. The device can be used in a back-drivable mode to record pelvic trajectories, either specified manually by a therapist or pre-recorded from unimpaired subjects, then replay these trajectories using a PD position feedback control law in the task space and a non-linear force control algorithm for each piston chamber. The control laws are presented, along with data that demonstrate the ability of the device to record and replay the pelvic motions that occur during normal walking.

The Application of Neural Position/Force Control in a Robotised Machining Process

2015 ◽  
Vol 220-221 ◽  
pp. 49-54
Author(s):  
Piotr Gierlak
Keyword(s):  
Neural Networks ◽  
Mathematical Model ◽  
Force Control ◽  
Robot Control ◽  
Control Algorithm ◽  
Control Process ◽  
Robotic Manipulator ◽  
Adaptive Method ◽  
Experimental Results ◽  
Machining Process

This paper presents an application of a robotic manipulator in a machining process. Due to the specifics of the process and numerous phenomena which are difficult to be modelled, suitable tool for the robot control are neural networks. This work concentrates on the robot control process. A synthesis of a neural position/force control algorithm is presented. The algorithm was tested by simulation and in actual conditions on a laboratory stand. The work presents the experimental results with their comparison with an adaptive method based on the robot’s mathematical model.

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