An Adaptive Backstepping Control Method for Lower-Limb Exoskeleton Robot

2020 ◽  
Author(s):  
Jianhua Wang ◽  
Pinghua Ai ◽  
Jianbin Zhang ◽  
Weihai Chen ◽  
Wenjie Chen
Keyword(s):  
Lower Limb ◽  
Control Method ◽  
Backstepping Control ◽  
Adaptive Backstepping ◽  
Adaptive Backstepping Control ◽  
Lower Limb Exoskeleton ◽  
Exoskeleton Robot

Trajectory following control of lower limb exoskeleton robot based on Udwadia–Kalaba theory

2021 ◽  
pp. 107754632110317
Author(s):  
Jin Tian ◽  
Liang Yuan ◽  
Wendong Xiao ◽  
Teng Ran ◽  
Li He
Keyword(s):  
Lower Limb ◽  
Control Method ◽  
Uniform Boundedness ◽  
Adaptive Robust Control ◽  
Structural Vibration ◽  
Control Approach ◽  
Lower Limb Exoskeleton ◽  
Exoskeleton Robot ◽  
Constraint Problem ◽  
Trajectory Following

The main objective of this article is to solve the trajectory following problem for lower limb exoskeleton robot by using a novel adaptive robust control method. The uncertainties are considered in lower limb exoskeleton robot system which include initial condition offset, joint resistance, structural vibration, and environmental interferences. They are time-varying and have unknown boundaries. We express the trajectory following problem as a servo constraint problem. In contrast to conventional control methods, Udwadia–Kalaba theory does not make any linearization or approximations. Udwadia–Kalaba theory is adopted to derive the closed-form constrained equation of motion and design the proposed control. We also put forward an adaptive law as a performance index whose type is leakage. The proposed control approach ensures the uniform boundedness and uniform ultimate boundedness of the lower limb exoskeleton robot which are demonstrated via the Lyapunov method. Finally, simulation results have shown the tracking effect of the approach presented in this article.

scholarly journals Multiobjective Trajectory Optimization and Adaptive Backstepping Control for Rubber Unstacking Robot Based on RFWNN Method

2018 ◽  
Vol 2018 ◽  
pp. 1-19
Author(s):  
Le Liang ◽  
Yanjie Liu ◽  
Hao Xu
Keyword(s):  
Trajectory Optimization ◽  
Control Method ◽  
External Disturbance ◽  
Backstepping Control ◽  
Adaptive Robust Control ◽  
Robot Dynamics ◽  
Adaptive Backstepping ◽  
Recycling Process ◽  
Adaptive Backstepping Control ◽  
Modeling Uncertainties

Multiobjective trajectory optimization and adaptive backstepping control method based on recursive fuzzy wavelet neural network (RFWNN) are proposed to solve the problem of dynamic modeling uncertainties and strong external disturbance of the rubber unstacking robot during recycling process. First, according to the rubber viscoelastic properties, the Hunt-Crossley nonlinear model is used to construct the robot dynamics model. Then, combined with the dynamic model and the recycling process characteristics, the multiobjective trajectory optimization of the rubber unstacking robot is carried out for the operational efficiency, the running trajectory smoothness, and the energy consumption. Based on the trajectory optimization results, the adaptive backstepping control method based on RFWNN is adopted. The RFWNN method is applied in the main controller to cope with time-varying uncertainties of the robot dynamic system. Simultaneously, an adaptive robust control law is developed to eliminate inevitable approximation errors and unknown disturbances and relax the requirement for prior knowledge of the controlled system. Finally, the validity of the proposed control strategy is verified by experiment.

scholarly journals Adaptive Backstepping Control with Online Parameter Estimator for a Plug-and-Play Parallel Converter System in a Power Switcher

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3528 ◽  
Author(s):  
Chujia Guo ◽  
Aimin Zhang ◽  
Hang Zhang ◽  
Lei Zhang
Keyword(s):  
Control Method ◽  
Optimal Algorithm ◽  
Weighted Least Squares ◽  
Backstepping Control ◽  
Parallel Structure ◽  
Adaptive Backstepping ◽  
Parameter Estimator ◽  
Plug And Play ◽  
Adaptive Backstepping Control ◽  
Circulating Current

This study aims to address the inherent uncertainty in plug loads and load extraction, distributed generation, and the inevitable circulating current in a parallel structure. Therefore, in this paper, an adaptive backstepping control scheme with an online parameter estimator (OPE) for a plug-and-play parallel converter system in a four-port power switcher is proposed. The adaptive backstepping control method was designed in the dq0 coordinate system to suppress the circulating current in the zero-component; the circulating current can be suppressed by using an embedded algorithm and omitting the extra controller. An adaptive update law was designed to weaken the influence of the arbitrary plug and extraction operations in the DC and AC buses to realize the plug-and-play function. The transient tracking performance is governed by the limitation of maximum total errors in the voltage and current. As a result, the settling times of the voltage, current, and power decreased. Additionally, to further improve the system robustness, an online inductance and resistance estimator was established using an optimal algorithm that solves the weighted least squares problem. In the estimator, there are no additional voltage and current sensors needed, and the mean squared error (MSE) of the estimation can be minimized. Simulation studies on a two-converter parallel system with a plug-and-play function were conducted using MATLAB/SIMULINK (R2018b, MathWorks, Natick, MA, USA) to verify the effectiveness of the proposed adaptive backstepping control strategy. The results show that this strategy improves system performance over that of a system with unbalanced parameters among a parallel structure with AC and DC system disturbances caused by arbitrary plug and extraction operations.

scholarly journals Design on electrohydraulic servo driving system with walking assisting control for lower limb exoskeleton robot

2021 ◽  
Vol 18 (1) ◽  
pp. 172988142199228
Author(s):  
Buyun Wang ◽  
Yi Liang ◽  
Dezhang Xu ◽  
Zhihong Wang ◽  
Jing Ji
Keyword(s):  
Pid Control ◽  
Lower Limb ◽  
Control Method ◽  
Human Gait ◽  
Tracking Accuracy ◽  
Driving System ◽  
Lower Limb Exoskeleton ◽  
Exoskeleton Robot ◽  
Pressure Compensation ◽  
Power Assistance

According to the characteristics of human gait and the requirements of power assistance, locomotive mechanisms and electrohydraulic servo driving are designed on a lower limb exoskeleton robot, in which the miniaturization and lightweight of driving system are realized. The kinematics of the robot is analyzed and verified via the typical movements of the exoskeleton. In this article, the simulation on the power of joints during level walking was analyzed in ADAMS 2016, which is a multibody simulation and motion analysis software. Motion ranges and driving strokes are then optimized. A proportional integral derivative (PID) control method with error estimation and pressure compensation is proposed to satisfy the requirements of joints power assistance and comply with the motion of human lower limb. The proposed method is implemented into the exoskeleton for assisted walking and is verified by experimental results. Finally, experiments show that the tracking accuracy and power-assisted performance of exoskeleton robot joints are improved.

scholarly journals Position Output Adaptive Backstepping Control of Electro-Hydraulic Servo Closed-Pump Control System

Processes ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 2209
Author(s):  
Gexin Chen ◽  
Huilong Liu ◽  
Pengshuo Jia ◽  
Gengting Qiu ◽  
Haohui Yu ◽  
...  
Keyword(s):  
Control System ◽  
Control Strategy ◽  
Parameter Uncertainty ◽  
Position Control ◽  
Control Method ◽  
Backstepping Control ◽  
Adaptive Backstepping ◽  
Control Effect ◽  
Adaptive Backstepping Control ◽  
Hydraulic Servo

A nonlinear adaptive backstepping control method was proposed to address the system parameter uncertainty problem in the position control process of an electro-hydraulic servo closed-pump control system. This control strategy fully considers the parameter uncertainty of the nonlinear system and establishes the adaptive rate of the uncertain parameter to adjust the parameter disturbance online in real time, thereby improving the accuracy and robustness of the control system. A pump control system experiment platform was used to verify the feasibility of the controller. The experimental results showed that the proposed control strategy provided a good control effect. The pump control system can be controlled with high precision, with a steady-state control accuracy of ±0.02 mm, which serves as a good foundation for the engineering application and promotion of the pump control system.

Adaptive Backstepping Control Based upon DRFNN for RCRBV

2011 ◽  
Vol 403-408 ◽  
pp. 5082-5087
Author(s):  
Ping Jun Zhang ◽  
Xin Hua Jiang
Keyword(s):  
Control Method ◽  
Mathematic Model ◽  
Fuzzy Neural Networks ◽  
Backstepping Control ◽  
Lyapunov Theory ◽  
Uncertain Parameters ◽  
Adaptive Backstepping ◽  
Adaptive Backstepping Control ◽  
Fuzzy Neural ◽  
Uncertainty Parameters

For the nonliear and uncertainty parameters of the running driving component of Resonant cement-road breaking vehicle (RCRBV), the mathematic model of the speed Control is established, a adaptive backstepping control method based upon the dynamic recurrent fuzzy neural networks (DRFNN) is presented. The adaptive backstepping controlling arithmetic is designed firstly in transportational status without regard to the uncertain parameters. The convergence based on Lyapunov theory for the closed loop system is also analysised. secondly, the uncertain parameters of the Electro-hydraulic propotional system which affect the running speed controlling performances are defined as items to be estimated by DRFNN in breaking status to meet the high precision and stability requires, the parameter adjustment law is given based upon DRFNN. Finally, the results of the simulation show that the scheme is robust with respect to plant parameter variations and load disturbances.

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