Adaptive robust control for a lower limbs rehabilitation robot running under passive training mode

2019 ◽  
Vol 6 (2) ◽  
pp. 493-502 ◽  
Author(s):  
Xiaolong Chen ◽  
Han Zhao ◽  
Shengchao Zhen ◽  
Hao Sun
Keyword(s):  
Robust Control ◽  
Adaptive Robust Control ◽  
Lower Limbs ◽  
Rehabilitation Robot ◽  
Training Mode ◽  
Robot Running ◽  
Passive Training

scholarly journals Design and Passive Training Control of Elbow Rehabilitation Robot

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1147
Author(s):  
Xiaohong Cui ◽  
Binrui Wang ◽  
Han Lu ◽  
Jiayu Chen
Keyword(s):  
Disturbance Rejection ◽  
Position Control ◽  
Rehabilitation Robot ◽  
Rehabilitation Robots ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control ◽  
Training Mode ◽  
Training Control ◽  
Expected Signal ◽  
Passive Training

In this paper, a rehabilitation robot driven by multifilament muscles is designed based on the rehabilitation robot motion model and a system elbow joint model. The passive training mode of rehabilitation robots were researched, and active disturbance rejection control (ADRC) leveraged to improve the tracking angle of robot joints. In the no-load motion simulation of rehabilitation robots, disturbances are added to the control variables to complete the ADRC and Proportional Integral Differential (PID) position control simulation. The simulation results indicate that the auto disturbance rejection control can quickly keep up the expected signal without overshoot, solve the contradiction between the system rapidity and overshoot. Moreover, it can better suppress the interference even if the external load changes. The upper limbs of the human body are used as the load on the robot body to complete the simulation of ADRC and PID position control objects of different weights. Finally, a passive rehabilitation training experiment was conducted to verify the safety of the rehabilitation robot, the rationality, comfort, and robustness of the mechanism design, and the effectiveness and feasibility of the ADRC.

Constraint-oriented integrated longitudinal and lateral robust control for connected and automated vehicle platoons

2021 ◽  
pp. 107754632110026
Author(s):  
Zeyu Yang ◽  
Jin Huang ◽  
Zhanyi Hu ◽  
Diange Yang ◽  
Zhihua Zhong
Keyword(s):  
Robust Control ◽  
Estimation Error ◽  
Uniform Boundedness ◽  
Path Tracking ◽  
Adaptive Robust Control ◽  
Connected Vehicle ◽  
Vehicle Platoon ◽  
Tracking Model ◽  
Vehicle Platoons ◽  
Following Error

The coupling, nonlinearity, and uncertainty characteristics of vehicle dynamics make the accurate longitudinal and lateral control of an automated and connected vehicle platoon a tough task. Little research has been conducted to fully address the characteristics. By using the ideology of constraint-following control this article proposes an integrated longitudinal and lateral adaptive robust control methodology for a vehicle platoon with a bidirectional communication topology. The platoon control objectives contain the path tracking stability, the platoon internal stability, and the string stability. First, we establish the nonlinear kinematics path tracking model and the coupled vehicle longitudinal and lateral dynamical model that contains time-varying uncertainties. Second, we design a series of nonlinear equality constraints that directly guarantee the control objectives based on the kinematic relations. On this basis, an adaptive robust constraint-following control is proposed. It is shown that the control guarantees the uniform boundedness and the uniform ultimate boundedness of the constraint-following error and the uncertainty estimation error. Finally, simulation results are provided to validate the effectiveness of the proposed methodology.

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