Hybrid Position/Force Control System for Human Lower-Limb Exoskeleton

2012 ◽  
Vol 8 (1) ◽  
pp. 427-432
Author(s):  
Zhi-Yong Tang ◽  
Zhen-Zhong Tan ◽  
Ming-Yi Yang ◽  
Zhong-Cai Pei
Keyword(s):  
Control System ◽  
Force Control ◽  
Lower Limb ◽  
Lower Limb Exoskeleton ◽  
Force Control System

Effect of Inner and Outer Wheels Driving Force Control on Small Electric Vehicle

2020 ◽  
Vol 17 (4) ◽  
pp. 8246-8254
Author(s):  
K. Shibazaki ◽  
H. Nozaki
Keyword(s):  
Control System ◽  
Angular Velocity ◽  
Electric Vehicle ◽  
Force Constant ◽  
Force Control ◽  
Driving Force ◽  
Vehicle Control ◽  
Steering Angle ◽  
Force Control System ◽  
The Difference

In this study, in order to improve steering stability during turning, we devised an inner and outer wheel driving force control system that is based on the steering angle and steering angular velocity, and verified its effectiveness via running tests. In the driving force control system based on steering angle, the inner wheel driving force is weakened in proportion to the steering angle during a turn, and the difference in driving force is applied to the inner and outer wheels by strengthening the outer wheel driving force. In the driving force control (based on steering angular velocity), the value obtained by multiplying the driving force constant and the steering angular velocity,  that differentiates the driver steering input during turning output as the driving force of the inner and outer wheels. By controlling the driving force of the inner and outer wheels, it reduces the maximum steering angle by 40 deg and it became possible to improve the cornering marginal performance and improve the steering stability at the J-turn. In the pylon slalom it reduces the maximum steering angle by 45 deg and it became possible to improve the responsiveness of the vehicle. Control by steering angle is effective during steady turning, while control by steering angular velocity is effective during sharp turning. The inner and outer wheel driving force control are expected to further improve steering stability.

A Polishing Robot Force Control System Based on Time Series Data in Industrial Internet of Things

2021 ◽  
Vol 21 (2) ◽  
pp. 1-22
Author(s):  
Chen Zhang ◽  
Zhuo Tang ◽  
Kenli Li ◽  
Jianzhong Yang ◽  
Li Yang
Keyword(s):  
Time Series ◽  
Control System ◽  
Force Control ◽  
Time Series Data ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Series Data ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Force Control System

Installing a six-dimensional force/torque sensor on an industrial arm for force feedback is a common robotic force control strategy. However, because of the high price of force/torque sensors and the closedness of an industrial robot control system, this method is not convenient for industrial mass production applications. Various types of data generated by industrial robots during the polishing process can be saved, transmitted, and applied, benefiting from the growth of the industrial internet of things (IIoT). Therefore, we propose a constant force control system that combines an industrial robot control system and industrial robot offline programming software for a polishing robot based on IIoT time series data. The system mainly consists of four parts, which can achieve constant force polishing of industrial robots in mass production. (1) Data collection module. Install a six-dimensional force/torque sensor at a manipulator and collect the robot data (current series data, etc.) and sensor data (force/torque series data). (2) Data analysis module. Establish a relationship model based on variant long short-term memory which we propose between current time series data of the polishing manipulator and data of the force sensor. (3) Data prediction module. A large number of sensorless polishing robots of the same type can utilize that model to predict force time series. (4) Trajectory optimization module. The polishing trajectories can be adjusted according to the prediction sequences. The experiments verified that the relational model we proposed has an accurate prediction, small error, and a manipulator taking advantage of this method has a better polishing effect.

A voice coil motor based measuring force control system for tactile scanning profiler

2015 ◽  
Author(s):  
Shengdong Feng ◽  
Xiaojun Liu ◽  
Liangzhou Chen ◽  
Liping Zhou ◽  
Wenlong Lu
Keyword(s):  
Control System ◽  
Force Control ◽  
Voice Coil Motor ◽  
Force Control System ◽  
Measuring Force

scholarly journals Impact of Load Variation on the Accuracy of Gait Recognition from Surface EMG Signals

2018 ◽  
Vol 8 (9) ◽  
pp. 1462 ◽  
Author(s):  
Xianfu Zhang ◽  
Shouqian Sun ◽  
Chao Li ◽  
Zhichuan Tang
Keyword(s):  
Control System ◽  
Lower Limb ◽  
Gait Recognition ◽  
Training Data ◽  
Support Vector ◽  
K Nearest Neighbor ◽  
Real Time Control ◽  
Lower Limb Exoskeleton ◽  
Load Variation ◽  
Significant Difference

As lower-limb exoskeleton and prostheses are developed to become smarter and to deploy man–machine collaboration, accurate gait recognition is crucial, as it contributes to the realization of real-time control. Many researchers choose surface electromyogram (sEMG) signals to recognize the gait and control the lower-limb exoskeleton (or prostheses). However, several factors still affect its applicability, of which variation in the loads is an essential one. This study aims to (1) investigate the effect of load variation on gait recognition; and to (2) discuss whether a lower-limb exoskeleton control system trained by sEMG from different loads works well in multi-load applications. In our experiment, 10 male college students were selected to walk on a treadmill at three different speeds (V3 = 3 km/h, V5 = 5 km/h, and V7 = 7 km/h) with four different loads (L0 = 0, L20 = 20%, L30 = 30%, L40 = 40% of body weight, respectively), and 50 gait cycles were performed. Back propagation neural networks (BPNNs) were used for gait recognition, and a support vector machine (SVM) and k-nearest neighbor (k-NN) were used for comparison. The result showed that (1) load variation has significant effects on the accuracy of gait recognition (p < 0.05) under the three speeds when the loads range in L0, L20, L30, or L40, but no significant impact is found when the loads range in L0, L20, or L30. The least significant difference (LSD) post hoc, which can explore all possible pair-wise comparisons of means that comprise a factor using the equivalent of multiple t-tests, reveals that there is a significant difference between the L40 load and the other three loads (L0, L20, L30), but no significant difference was found among the L0, L20, and L30 loads. The total mean accuracy of gait recognition of the intra-loads and inter-loads was 91.81%, and 69.42%, respectively. (2) When the training data was taken from more types of loads, a higher accuracy in gait recognition was obtained at each speed, and the statistical analysis shows that there was a substantial influence for the kinds of loads in the training set on the gait recognition accuracy (p < 0.001). It can be concluded that an exoskeleton (or prosthesis) control system that is trained in a single load or the parts of loads is insufficient in the face of multi-load applications.

scholarly journals Development of ER Actuator and Basic Study on its Force Control System.

1998 ◽  
Vol 16 (8) ◽  
pp. 1108-1114 ◽  
Author(s):  
Masamichi Sakaguchi ◽  
Junji Furusho ◽  
Guoguang Zhang ◽  
Zhidan Wei
Keyword(s):  
Control System ◽  
Force Control ◽  
Basic Study ◽  
Force Control System

scholarly journals Development of human lower limbs exoskeleton robot for medical rehabilitation

2021 ◽  
pp. 91-97
Author(s):  
E. A. Kotov ◽  
◽  
A. D. Druk ◽  
D. N. Klypin ◽  
◽  
...  
Keyword(s):  
Control System ◽  
Experimental Research ◽  
Lower Limb ◽  
Lower Limbs ◽  
Medical Rehabilitation ◽  
Lower Limb Exoskeleton ◽  
Exoskeleton Robot ◽  
Controlled Motion ◽  
And Control

The article deals with the solution of the problem of optimizing the characteristics of controlled motion of human lower limb exoskeleton robot for improving medical rehabilitation. The aim of the work is to develop a rehabilitation device capable of providing controlled motion in two planes, as well as maintaining balance without loss of mobility. The design and control system of a rehabilitation trainer designed for performing mechanotherapy of the lower limbs of patients with locomotive disorders are proposed and characterized. The developed system has a number of significant differences from analogues and can be recommended for experimental research on patients with impaired locomotive functions

Design of force control system using tendon-driven mechanism including linear springs and ultrasonic motor

2018 ◽  
Vol 205 (1) ◽  
pp. 36-45 ◽  
Author(s):  
Daiki Yonemoto ◽  
Daisuke Yashiro ◽  
Kazuhiro Yubai ◽  
Satoshi Komada
Keyword(s):  
Control System ◽  
Force Control ◽  
Ultrasonic Motor ◽  
Force Control System
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