Control of pneumatic muscle actuators

1995 ◽  
Vol 15 (1) ◽  
pp. 40-48 ◽  
Keyword(s):  
Pneumatic Muscle ◽  
Muscle Actuators

scholarly journals Extended-State-Observer-Based Super Twisting Control for Pneumatic Muscle Actuators

Actuators ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 35
Author(s):  
Yu Cao ◽  
Zhongzheng Fu ◽  
Mengshi Zhang ◽  
Jian Huang
Keyword(s):  
Control Method ◽  
Experimental Studies ◽  
State Observer ◽  
Extended State Observer ◽  
Extended State ◽  
Pneumatic Muscle ◽  
System States ◽  
The Stability ◽  
Twisting Control ◽  
Muscle Actuators

This paper presents a tracking control method for pneumatic muscle actuators (PMAs). Considering that the PMA platform only feedbacks position, and the velocity and disturbances cannot be observed directly, we use the extended-state-observer (ESO) for simultaneously estimating the system states and disturbances by using measurable variables. Integrated with the ESO, a super twisting controller (STC) is design based on estimated states to realize the high-precision tracking. According to the Lyapunov theorem, the stability of the closed-loop system is ensured. Simulation and experimental studies are conducted, and the results show the convergence of the ESO and the effectiveness of the proposed method.

scholarly journals Active Motion Control of a Knee Exoskeleton Driven by Antagonistic Pneumatic Muscle Actuators

Actuators ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 134
Author(s):  
Wei Zhao ◽  
Aiguo Song
Keyword(s):  
Sliding Mode ◽  
Weight Ratio ◽  
Practical Application ◽  
Active Motion ◽  
Pneumatic Muscle ◽  
The Past ◽  
Robotic Devices ◽  
Muscle Actuators ◽  
Further Development ◽  
Rehabilitation Robotic

The pneumatic muscle actuator (PMA) has been widely applied in the researches of rehabilitation robotic devices for its high power to weight ratio and intrinsic compliance in the past decade. However, the high nonlinearity and hysteresis behavior of PMA limit its practical application. Hence, the control strategy plays an important role in improving the performance of PMA for the effectiveness of rehabilitation devices. In this paper, a PMA-based knee exoskeleton based on ergonomics is proposed. Based on the designed knee exoskeleton, a novel proxy-based sliding mode control (PSMC) is introduced to obtain the accurate trajectory tracking. Compared with conventional control approaches, this new PSMC can obtain better performance for the designed PMA-based exoskeleton. Experimental results indicate good tracking performance of this controller, which provides a good foundation for the further development of assist-as-needed training strategies in gait rehabilitation.

scholarly journals A New Approach to Modeling and Controlling a Pneumatic Muscle Actuator-Driven Setup Using Back Propagation Neural Networks

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Jun Zhong ◽  
Xu Zhou ◽  
Minzhou Luo
Keyword(s):  
Back Propagation ◽  
Weight Ratio ◽  
Adaptive Controller ◽  
Back Propagation Neural Network ◽  
Sampled Data ◽  
Nonlinear Characteristics ◽  
New Approach ◽  
Pneumatic Muscle ◽  
Muscle Actuators

Pneumatic muscle actuators (PMAs) own excellent compliance and a high power-to-weight ratio and have been widely used in bionic robots and rehabilitated robots. However, the high nonlinear characteristics of PMAs due to inherent construction and pneumatic driving principle bring great challenges in applications acquired accurately modeling and controlling. To tackle the tricky problem, a single PMA mass setup is constructed, and a back propagation neural network (BPNN) is employed to identify the dynamics of the setup. An offline model is built up using sampled data, and online modifications are performed to further improve the quality of the model. An adaptive controller based on BPNN is designed using gradient descent information of the built-up model. Experiments of identifying the PMA setup using BPNN and position tracking by adaptive BPNN controller are performed, and results demonstrate the good capacity in accurate controlling of the PMA setup.

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