Learning Parametric Inverse Dynamics Models from multiple conditions for fast adaptive computed torque control

A development of a robot control system is a highly complex task due to nonlinear dynamic coupling between the robot links. Advanced robot control strategies often entail difficulties in implementation, and prospective benefits of their application need to be analyzed using simulation techniques. Computed torque control (CTC) is a feedforward control method used for tracking of robot’s time-varying trajectories in the presence of varying loads. For the implementation of CTC, the inverse dynamics model of the robot manipulator has to be developed. In this paper, the addition of CTC compensator to the feedback controller is considered for a Spatial disorientation trainer (SDT). This pilot training system is modeled as a 4DoF robot manipulator with revolute joints. For the designed mechanical structure, chosen actuators and considered motion of the SDT, CTC-based control system performance is compared with the traditional speed PI controller using the realistic simulation model. The simulation results, which showed significant improvement in the trajectory tracking for the designed SDT, can be used for the control system design purpose as well as within mechanical design verification.

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Computed Torque Control of Articulated Multibody Systems in the Generalized Divide and Conquer Algorithm Framework

Volume 8: 27th Conference on Mechanical Vibration and Noise ◽

10.1115/detc2015-46853 ◽

2015 ◽

Author(s):

Cameron Kingsley ◽

Mohammad Poursina

Keyword(s):

Multibody Systems ◽

Inverse Dynamics ◽

Equations Of Motion ◽

Torque Control ◽

Divide And Conquer ◽

Controlled System ◽

Divide And Conquer Algorithm ◽

Computed Torque Control ◽

And Control ◽

Computed Torque

An extension to the Generalized-Divide-and-Conquer Algorithm (GDCA) is presented in this paper in conjunction with the Computed-Torque-Control-Law (CTCL) to model and control fully actuated multibody systems. CTCL uses the inverse dynamics to provide control inputs to the system while, the dynamics of the system must be formed and solved in each iteration. Herein, the GDCA is extended to form and solve the inverse dynamics to find control torques. Further, this method is also extended to efficiently solve the equations of motion of the controlled system. This significantly reduces the complexity of modeling, simulating, and controlling the fully actuated multibody systems to O(n) or O(logn) operations in each iteration in the serial and parallel implementations, respectively.

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A PD Computed Torque Control Method with Online Self-gain Tuning for a 3UPS-PS Parallel Robot

Robotica ◽

10.1017/s0263574720001368 ◽

2021 ◽

pp. 1-13

Author(s):

Xiaogang Song ◽

Yongjie Zhao ◽

Chengwei Chen ◽

Liang’an Zhang ◽

Xinjian Lu

Keyword(s):

Feedback Loop ◽

Control Method ◽

Virtual Work ◽

Parallel Robot ◽

Torque Control ◽

Virtual Work Principle ◽

Tuning Method ◽

Computed Torque Control ◽

Control Feedback ◽

Computed Torque

SUMMARY In this paper, an online self-gain tuning method of a PD computed torque control (CTC) is used for a 3UPS-PS parallel robot. The CTC is applied to the 3UPS-PS parallel robot based on the robot dynamic model which is established via a virtual work principle. The control system of the robot comprises a nonlinear feed-forward loop and a PD control feedback loop. To implement real-time online self-gain tuning, an adjustment method based on the genetic algorithm (GA) is proposed. Compared with the traditional CTC, the simulation results indicate that the control algorithm proposed in this study can not only enhance the anti-interference ability of the system but also improve the trajectory tracking speed and the accuracy of the 3UPS-PS parallel robot.

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