Position Tracking of a Pneumatic-Muscle-Driven Rehabilitation Robot by a Single Neuron Tuned PID Controller

Zhong, Jun; Zhu, Yue; Zhao, Chun; Zhen-feng, Han; Zhang, Xin

doi:10.1155/2020/1438391

Cited by 8 publications

(4 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Comparing these results with the study by Bucca et al [31] we can see that the currents are similar. Comparison of the rotation angle error with the study of Zhong et al [32] shows that our device gives better results (1 • compared to 4.5 • ). In addition, the device has a more straightforward structure and its cost is lower [31,32]; the total cost of the device is $400.…”

Section: Experiments Resultssupporting

confidence: 47%

Archive of Mechanical Engineering

Duc Dao,

Tran,

Pham

et al. 2021

View full text Add to dashboard Cite

This study developed an ankle rehabilitation device for post-stroke patients. First, the research models and dynamic equations of the device are addressed. Second, the Sliding Mode Controller for the ankle rehabilitation device is designed, and the device's response is simulated on the software MATLAB. Third, the ankle rehabilitation device is successfully manufactured from aluminum and uses linear actuators to emulate dorsiflexion and plantarflexion exercises for humans. The advantages of the device are a simple design, low cost, and mounts onto rehabilitative equipment. The device can operate fast through experiments, has a foot drive mechanism overshoot of 0 • , and a maximum angle error of 1 • . Moreover, the rehabilitation robot can operate consistently and is comfortable for stroke patients to use. Finally, we will fully develop the device and proceed to clinical implementation.

show abstract

Section: Experiments Resultssupporting

confidence: 47%

Archive of Mechanical Engineering

Duc Dao,

Tran,

Pham

et al. 2021

View full text Add to dashboard Cite

show abstract

“…However, both SVM and BP neural network have shortcomings. On the one hand, SVM is difficult to solve the fundamental zero and nonzero problems; on the other hand, BP neural network is difficult to avoid the overfitting problem, which seriously restricts the application of neural network [21,22].…”

Section: Artificial Intelligence-based Fault Diagnosis Methodsmentioning

confidence: 99%

Real-Time Leak Detection in High Frequency Hydraulic Cylinder Based on Intelligent Control

Gao

Tian

2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

Most of the existing hydraulic cylinder internal leakage detection methods are laboratory testing methods, mainly the pressure-holding method, measurement of hydraulic cylinder settlement method, and measuring cup measurement method. The internal leakage of the hydraulic cylinder affects the damping characteristics of the control system. Therefore, real-time internal leakage detection plays an important role in the control characteristics. This paper first proposes a wavelet analysis-based extraction of hydraulic cylinder internal leakage fault eigenvalues for analysis, that is, data processing. A convolutional neural network-based detection method is also proposed, in which the pressure signal of a chamber of a hydraulic cylinder is first obtained through simulation under four operating conditions: no leakage, small leakage, medium leakage, and large leakage. Compared to traditional modelling methods, the method overcomes the difficulties in modelling nonlinear hydraulic systems, requires only pressure signal acquisition, is simple and reliable, and is compared with traditional BP neural networks to demonstrate its superiority.

show abstract

“…Though the traditional PID controller is easily used to implement the control of the quad rotor UAV, the fixed PID parameters cannot adapt to the changes of external conditions and control object parameters, which makes it difficult to achieve the desired control effect. However, single neuron PID method has been applied to some control systems and has achieved good control results (Feng 2022;Yanjun et al 2018;Zhong et al 2020). Single neuron has a strong self-learning ability, and its nonlinear mapping function can solve the nonlinear problems.…”

Section: Introductionmentioning

confidence: 99%

Position and Attitude Control Based on Single Neuron PID With Gravity Compensation for Quad Rotor UAV

Hai-tao

Yang

2023

J. Aerosp. Technol. Manag.

View full text Add to dashboard Cite

Aimed at the deficiency of existing PID controller for quad rotor UAV, a single neuron PID controller with gravity compensation is presented. After using feed forward control to compensate gravity, the position loop adopts PID control to ensure control accuracy, while the attitude loop adopts single neuron control to increase adaptive ability. Then, by using Matlab/simulink simulation software, the position control of quad rotor UAV is carried out, and the simulation result shows, compared with the traditional double closed loop PID controller, the control algorithm based on the Single Neuron adaptive PID with gravity compensation can effectively improve the robustness and adaptability of the quad rotor UAV system.

show abstract

Position Tracking of a Pneumatic-Muscle-Driven Rehabilitation Robot by a Single Neuron Tuned PID Controller

Cited by 8 publications

References 31 publications

Archive of Mechanical Engineering

Archive of Mechanical Engineering

Real-Time Leak Detection in High Frequency Hydraulic Cylinder Based on Intelligent Control

Position and Attitude Control Based on Single Neuron PID With Gravity Compensation for Quad Rotor UAV

Contact Info

Product

Resources

About