Feed Forward Control for Pneumatic Forearm Prosthesis, Manipulator

2012 ◽  
Author(s):  
Antoine Andrieu ◽  
Nobutaka Tsujiuchi ◽  
Takayuki Koizumi ◽  
Sho Maeda ◽  
Yoichiro Nakamura
Keyword(s):  
Dead Zone ◽  
Artificial Muscle ◽  
Great Accuracy ◽  
Human Hand ◽  
Hysteresis Cycle ◽  
Human Beings ◽  
Feed Forward ◽  
Pneumatic Actuators ◽  
Feed Forward Control ◽  
Rubber Balloon

In order to reach a better productivity in numerous fields, robots have been wildly used for automatic tasks. The main issue of a robot is his lack of adaptability, which is one of the most important ability of human beings. The best tool for adaptability is the human hand. Using pneumatic actuators to drive a robot forearm grants the possibility to move light articles with accuracy and without harming it. It is then necessary to develop accurate model of the different types of actuators. As every human muscle are simulated by those actuators, the size of these must vary and so their properties as well. These artificial muscle-type pneumatic actuators are composed of a rubber balloon, a net, a feeding channel and finally two anchors at both end of the net. Starting with the simplest linear model, we increased the complexity of the model to finally obtain a powerful control of the plastic muscle. To obtain the data we needed for the model, we used a test bench for pneumatic actuators and adjust it to fit the new size of the current actuator. The main difficulty to control the actuator is to find a way to overcome its hysteresis cycle. Then once the model is ready we need to use it to control the different part of the pneumatic forearm. The previous wrist and hand control is enhanced by feed forward control and can perform motion with a great accuracy. The hand can therefore be used without any electronic devices on it and remains lighter and safer. Previous starting dead-zone has been understood and avoided.

A Neural Network Strategy for Learning of Nonlinearities Toward Feed-Forward Control of Pressure-Compensated Hydraulic Valves With a Significant Dead Zone

2018 ◽  
Author(s):  
Jarmo Nurmi ◽  
Mohammad M. Aref ◽  
Jouni Mattila
Keyword(s):  
Adaptive Learning ◽  
Dead Zone ◽  
Effective Means ◽  
Previous Method ◽  
Deep Convolutional Neural Networks ◽  
Feed Forward ◽  
Feed Forward Control ◽  
Highly Nonlinear ◽  
Hydraulic Manipulator ◽  
Hydraulic Valves

A velocity feed-forward-based strategy is an effective means for controlling a heavy-duty hydraulic manipulator; in particular, a typical valve-controlled hydraulic manipulator, to compensate for valve dead-zone and other hydraulic valve nonlinearities. Based on our previous work on the adaptive learning of valve velocity feed-forwards, manually labelling and identifying the dead-zones and the other nonlinearities in the velocity feed-forward curves of pressure-compensated hydraulic valves can be avoided. Nevertheless, it may take two to three minutes or more per actuator to identify a pressure-compensated valve’s highly nonlinear velocity feed-forward in real-time with an adaptive approach, which should be reduced for realistic applications. In this paper, inspired by brain signal analysis technologies, we propose a new method based on deep convolutional neural networks comparing with the previous method to significantly reduce this online learning process with the strong nonlinearities of pressure-compensated hydraulic valves. We present simulation results to demonstrate the effectiveness of the deep learning-based learning method compared to the previous results with an adaptive control-based learning.

scholarly journals An Improved Frequency Dead Zone with Feed-Forward Control for Hydropower Units: Performance Evaluation of Primary Frequency Control

Energies ◽  
2019 ◽  
Vol 12 (8) ◽  
pp. 1497 ◽  
Author(s):  
Hao An ◽  
Jiandong Yang ◽  
Weijia Yang ◽  
Yuanchu Cheng ◽  
Yumin Peng
Keyword(s):  
Frequency Control ◽  
Dead Zone ◽  
Hydropower Plant ◽  
Feed Forward ◽  
Feed Forward Control ◽  
Wear And Tear ◽  
Integral Quantity ◽  
Frequency Fluctuations ◽  
Primary Frequency ◽  
Primary Frequency Control

Due to the integration of more intermittent renewable energy into the power grid, the demand for frequency control in power systems has been on the rise, and primary frequency control of hydropower units plays an increasingly important role. This paper proposes an improved frequency dead zone with feed-forward control. The aim is to achieve a comprehensive performance of regulating rapidity, an assessment of integral quantity of electricity, and the wear and tear of hydropower units during primary frequency control, especially the unqualified performance of integral quantity of electricity assessment under frequency fluctuations with small amplitude. Based on a real hydropower plant with Kaplan units in China, this paper establishes the simulation model, which is verified by comparing experimental results. After that, based on the simulation of real power grid frequency fluctuations and a real hydropower plant case, the dynamic process of primary frequency control is evaluated for three aspects, which include speed, integral quantity of electricity, and wear and tear. The evaluation also includes the implementations of the three types of dead zones: common frequency dead zone, the enhanced frequency dead zone, and the improved frequency dead zone. The results of the study show that the improved frequency dead zone with feed-forward control increases the active power output under small frequency fluctuations. Additionally, it alleviates the wear and tear problem of the enhanced frequency dead zone in the premise of guaranteeing regulation speed and integral quantity of electricity. Therefore, the improved frequency dead zone proposed in this paper can improve the economic benefit of hydropower plants and reduce their maintenance cost. Accordingly, it has been successfully implemented in practical hydropower plants in China.

scholarly journals Model-based feed-forward control for time-varying systems with an example for SRF cavities

2020 ◽  
Vol 53 (2) ◽  
pp. 1331-1336
Author(s):  
Sven Pfeiffer ◽  
Annika Eichler ◽  
Holger Schlarb
Keyword(s):  
Time Varying ◽  
Feed Forward ◽  
Feed Forward Control ◽  
Model Based ◽  
Time Varying Systems ◽  
Srf Cavities

Flatness Feed-Forward Control Model Based on Neural Networks

2014 ◽  
Vol 989-994 ◽  
pp. 3386-3389
Author(s):  
Zhu Wen Yan ◽  
Hen An Bu ◽  
Dian Hua Zhang ◽  
Jie Sun
Keyword(s):  
Neural Networks ◽  
Rolling Mill ◽  
Rolling Force ◽  
Work Roll ◽  
Control Model ◽  
Good Effect ◽  
Feed Forward ◽  
Force Fluctuations ◽  
Feed Forward Control ◽  
Roll Bending

The influence on the shape of the strip from rolling force fluctuations has been analyzed. The combination of intermediate roll bending and work roll bending has been adopted. The principle of rolling force feed-forward control has been analyzed. The feed-forward control model has been established on the basis of neural networks. The model has been successfully applied to a rolling mill and a good effect has been achieved.

scholarly journals Feed-forward control of preshaping in the rat is mediated by the corticospinal tract

2010 ◽  
Vol 32 (10) ◽  
pp. 1678-1685 ◽  
Author(s):  
Jason B. Carmel ◽  
Sangsoo Kim ◽  
Marcel Brus-Ramer ◽  
John H. Martin
Keyword(s):  
Corticospinal Tract ◽  
Feed Forward ◽  
Feed Forward Control

Improved Pole-placement Control with Feed-forward Dead Zone Compensation for Position Tracking of Electro-Pneumatic Actuator System Improved Pole-placement Control with Feed-forward Dead Zone Compensation for Position Tracking of Electro-Pneumatic Actuato

2021 ◽  
Vol 20 (2) ◽  
pp. 25-32
Author(s):  
Noorhazirah Sunar ◽  
Mohd Fua’ad Rahmat ◽  
Ahmad ‘Athif Mohd Fauzi ◽  
Zool Hilmi Ismail ◽  
Siti Marhanis Osman ◽  
...  
Keyword(s):  
Dead Zone ◽  
Pneumatic Actuator ◽  
Pole Placement ◽  
Position Tracking ◽  
Zone Model ◽  
Feed Forward ◽  
The Dead ◽  
Chattering Effect ◽  
Pole Placement Controller ◽  
Pole Placement Control

Dead-zone in the valve degraded the performances of the Electro-Pneumatic Actuator (EPA) system.  It makes the system difficult to control, become unstable and leads to chattering effect nearest desired position.  In order to cater this issue, the EPA system transfer function and the dead-zone model is identified by MATLAB SI toolbox and the Particle Swarm Optimization (PSO) algorithm respectively.  Then a parametric control is designed based on pole-placement approach and combine with feed-forward inverse dead-zone compensation.  To reduce chattering effect, a smooth parameter is added to the controller output.  The advantages of using these techniques are the chattering effect and the dead-zone of the EPA system is reduced.  Moreover, the feed-forward system improves the transient performance.  The results are compared with the pole-placement control (1) without compensator and (2) with conventional dead-zone compensator.  Based on the experimental results, the proposed controller reduced the chattering effect due to the controller output of conventional dead-zone compensation, 90% of the pole-placement controller steady-state error and 30% and 40% of the pole-placement controller with conventional dead-zone compensation settling time and rise time.

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