Modeling and control of McKibben artificial muscle robot actuators

2000 ◽  
Vol 20 (2) ◽  
pp. 15-38 ◽  
Keyword(s):  
Artificial Muscle ◽  
Modeling And Control ◽  
And Control

204 Modeling and Control of Pneumatic Artificial Muscle Actuator

2008 ◽  
Vol 2008.83 (0) ◽  
pp. _2-4_
Author(s):  
Nobutaka TSUJIUCHI ◽  
Takayuki KOIZUMI ◽  
Hiroto KAN ◽  
Shinya NISHINO ◽  
Tatsuwo KUDAWARA ◽  
...  
Keyword(s):  
Artificial Muscle ◽  
Pneumatic Artificial Muscle ◽  
Modeling And Control ◽  
And Control

Gray-box modeling and control of torsional fishing-line artificial muscle actuators

2018 ◽  
Author(s):  
Kentaro Takagi ◽  
Chihaya Oiwa ◽  
Ken Masuya ◽  
Kenji Tahara ◽  
Toshihira Irisawa ◽  
...  
Keyword(s):  
Artificial Muscle ◽  
Modeling And Control ◽  
Muscle Actuators ◽  
And Control

Modeling and control of McKibben artificial muscle enhanced with echo state networks

2012 ◽  
Vol 20 (5) ◽  
pp. 477-488 ◽  
Author(s):  
Kexin Xing ◽  
Yongji Wang ◽  
Quanmin Zhu ◽  
Hanying Zhou
Keyword(s):  
Artificial Muscle ◽  
Modeling And Control ◽  
Echo State Networks ◽  
And Control

Learning Based Speed Control of Soft Robotic Fish

2018 ◽  
Author(s):  
Sunil Kumar Rajendran ◽  
Feitian Zhang
Keyword(s):  
Design Method ◽  
Control Design ◽  
Artificial Muscle ◽  
Speed Control ◽  
Robotic Fish ◽  
Design Approach ◽  
Modeling And Control ◽  
Model Free ◽  
Bioinspired Robotics ◽  
And Control

Bioinspired robotics takes advantage of biological systems in nature for morphology, action and perception to build advanced robots of compelling performance and wide application. This paper focuses on the design, modeling and control of a bioinspired robotic fish. The design utilizes a recently-developed artificial muscle named super coiled polymer for actuation and a soft material (silicone rubber) for building the robot body. The paper proposes a learning based speed control design approach for bioinspired robotic fish using model-free reinforcement learning. Based on a mathematically tractable dynamic model derived by approximating the robotic fish with a three-link robot, speed control simulation is conducted to demonstrate and validate the control design method. Exampled with a three-link reduced-order dynamic system, the proposed learning based control design approach is applicable to many and various complicated bioinspired robotic systems.

Modeling and Control for Plant Dynamics Based on Reinforcement Learning

2009 ◽  
Vol 129 (4) ◽  
pp. 363-367
Author(s):  
Tomoyuki Maeda ◽  
Makishi Nakayama ◽  
Hiroshi Narazaki ◽  
Akira Kitamura
Keyword(s):  
Reinforcement Learning ◽  
Modeling And Control ◽  
Plant Dynamics ◽  
And Control
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