Neural network-based adaptive command filtering control for pneumatic artificial muscle robots with input uncertainties

2022 ◽  
Vol 118 ◽  
pp. 104960
Author(s):  
Gendi Liu ◽  
Ning Sun ◽  
Dingkun Liang ◽  
Yiheng Chen ◽  
Tong Yang ◽  
...  
2019 ◽  
Vol 12 (4) ◽  
pp. 357-366
Author(s):  
Yong Song ◽  
Shichuang Liu ◽  
Jiangxuan Che ◽  
Jinyi Lian ◽  
Zhanlong Li ◽  
...  

Background: Vehicles generally travel on different road conditions, and withstand strong shock and vibration. In order to reduce or isolate the strong shock and vibration, it is necessary to propose and develop a high-performance vehicle suspension system. Objective: This study aims to report a pneumatic artificial muscle bionic kangaroo leg suspension to improve the comfort performance of vehicle suspension system. Methods: In summarizing the existing vehicle suspension systems and analyzing their advantages and disadvantages, this paper introduces a new patent of vehicle suspension system based on the excellent damping and buffering performance of kangaroo leg, A Pneumatic Artificial Muscle Bionic Kangaroo Leg Suspension. According to the biomimetic principle, the pneumatic artificial muscles bionic kangaroo leg suspension with equal bone ratio is constructed on the basis of the kangaroo leg crural index, and two working modes (passive and active modes) are designed for the suspension. Moreover, the working principle of the suspension system is introduced, and the rod system equations for the suspension structure are built up. The characteristic simulation model of this bionic suspension is established in Adams, and the vertical performance is analysed. Results: It is found that the largest deformation happens in the bionic heel spring and the largest angle change occurs in the bionic ankle joint under impulse road excitation, which is similar to the dynamic characteristics of kangaroo leg. Furthermore, the dynamic displacement and the acceleration of the vehicle body are both sharply reduced. Conclusion: The simulation results show that the comfort performance of this bionic suspension is excellent under the impulse road excitation, which indicates the bionic suspension structure is feasible and reasonable to be applied to vehicle suspensions.


2021 ◽  
Vol 11 (5) ◽  
pp. 2312
Author(s):  
Dengguo Xu ◽  
Qinglin Wang ◽  
Yuan Li

In this study, based on the policy iteration (PI) in reinforcement learning (RL), an optimal adaptive control approach is established to solve robust control problems of nonlinear systems with internal and input uncertainties. First, the robust control is converted into solving an optimal control containing a nominal or auxiliary system with a predefined performance index. It is demonstrated that the optimal control law enables the considered system globally asymptotically stable for all admissible uncertainties. Second, based on the Bellman optimality principle, the online PI algorithms are proposed to calculate robust controllers for the matched and the mismatched uncertain systems. The approximate structure of the robust control law is obtained by approximating the optimal cost function with neural network in PI algorithms. Finally, in order to illustrate the availability of the proposed algorithm and theoretical results, some numerical examples are provided.


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