Internal Model Control and Experimental Study of Ankle Rehabilitation Robot

Robotica ◽  
2020 ◽  
Vol 38 (5) ◽  
pp. 940-956
Author(s):  
Lan Wang ◽  
Ying Chang ◽  
Haitao Zhu
Keyword(s):  
Active Control ◽  
Internal Model ◽  
Dynamic Models ◽  
Friction Model ◽  
Internal Model Control ◽  
Control Mode ◽  
Rehabilitation Robot ◽  
Model Control ◽  
Ankle Rehabilitation ◽  
Passive Training

SUMMARYIn the present work, the ankle rehabilitation robot (ARR) dynamic model that implements a new series of connection control strategies is introduced. The dynamic models are presented in this regard. This model analyzes the robot LuGre friction model and the nonlinear disturbance model. To improve the ARR system’s rapidity and robustness, a composite 2-degree of freedom (2-DOF) internal model control (IMC) controller is presented. The control performance of the compound 2-DOF IMC controller is simulated and analyzed in the present work. The simulation shows that the composite 2-DOF IMC controller has high following performance. For practical testing purposes, 1-DOF passive training and predetermined trajectory following have been completed for different swing amplitudes and frequencies. Moreover, the thrust and tension torque of the robotic dynamic and static loading characteristics are studied in active control mode. The experimental results show the effectiveness of passive training of the given trajectory and impedance training active control strategy. This paper gives the specific functions of ARR.

Internal Model Control Using EWMA for a Wedge-Type Piezoelectric Motor

2007 ◽  
Author(s):  
Yung Ting ◽  
Hui-Yi Feng ◽  
Han-Chih Hsieh ◽  
Li-Yen Wang ◽  
Chun-Chung Li ◽  
...  
Keyword(s):  
Internal Model ◽  
Dead Zone ◽  
Friction Model ◽  
Internal Model Control ◽  
Nonlinear Phenomenon ◽  
Piezoelectric Motor ◽  
Time Operation ◽  
Control Command ◽  
Model Control ◽  
Feedforward Controller

Wedge-type piezoelectric motor is easily subject to disturbance such as friction, preload and temperature change, which influences the performance significantly and reduces the positioning accuracy and reliability. In this study, Exponentially Weighted Moving Average (EWMA) method is considered to use for the velocity-feedback loop, which is included in an Internal Model Control (IMC) to achieve a Run-to-Run IMC (RtR-IMC) control structure. Such control scheme is able to adapt the control command following a changing system dynamics so that it can improve the tracking accuracy and robustness. Friction is also a problem of generating dead-zone area and causes serious nonlinear phenomenon especially while moving direction is changed. A feedforward controller is designed based on the friction model. Moreover, temperature increase appears in long-time operation, which is another factor influential to piezoelectric motor’ performance. Instead of using the Single EWMA method, which cannot efficiently deal with such environmental drift problem, a Double EWMA algorithm is developed. Practical experiment is carried out to verify the performance by using these proposed methods. It concludes that the Double EWMA associated with the friction-model-based feedforward controller is superior to the other methods.

A novel IMC-FOF design for four wheel steering systems of distributed drive electric vehicles

2021 ◽  
pp. 095440702110314
Author(s):  
Yan Ti ◽  
Kangcheng Zheng ◽  
Wanzhong Zhao ◽  
Tinglun Song
Keyword(s):  
Fractional Order ◽  
Electric Vehicles ◽  
Internal Model ◽  
Rear Wheel ◽  
Internal Model Control ◽  
Steering Angle ◽  
Comparison Results ◽  
Model Control ◽  
Tracking Ability ◽  
Internal Model Controller

To improve handling and stability for distributed drive electric vehicles (DDEV), the study on four wheel steering (4WS) systems can improve the vehicle driving performance through enhancing the tracking capability to desired vehicle state. Most previous controllers are either a large amount of calculation, or requires a lot of experimental data, these are relatively time-consuming and laborious. According to the front and rear wheel steering angle of DDEV can be distributed independently, a novel controller named internal model controller with fractional-order filter (IMC-FOF) for 4WS systems is proposed and studied in this paper. The IMC-FOF is designed using the internal model control theory and compared with IMC and PID controller. The influence of time constant and fractional-order parameters which is optimized using quantum genetic algorithms (QGA) on tracking ability of vehicle state are also analyzed. Using a production vehicle as an example, the simulation is performed combining Matlab/Simulink and CarSim. The comparison results indicated that the proposed controller presents performance to distribute the front and rear wheel steering angle for ensuring better tracking capability to desired vehicle state, meanwhile it possesses strong robustness.

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