Robust simultaneous stabilization of multiple n ‐degree‐of‐freedom robot systems

2021 ◽  
Author(s):  
Haiying Zhang ◽  
Renming Yang
Keyword(s):  
Degree Of Freedom ◽  
Simultaneous Stabilization ◽  
Robot Systems

Simultaneous stabilization of multiple n-degree-of-freedom robot systems

2021 ◽  
Author(s):  
Haiying Zhang ◽  
Renming Yang ◽  
Chunfu Zhang ◽  
Qi Li ◽  
Xin Shi
Keyword(s):  
Degree Of Freedom ◽  
Simultaneous Stabilization ◽  
Robot Systems

scholarly journals Control of Robot Arm Motion Using Trapezoid Fuzzy Two-Degree-of-Freedom PID Algorithm

Symmetry ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 665 ◽  
Author(s):  
Meng Bi
Keyword(s):  
Degree Of Freedom ◽  
Robot Arm ◽  
Pid Algorithm ◽  
Symmetry Principles ◽  
Model Control ◽  
Robot Systems ◽  
Arm Motion ◽  
Non Linear System ◽  
The Mathematical Model ◽  
Two Degree Of Freedom

Symmetries play very important in the dynamics of robot systems. The relevant control of robot arm motion with fault diagnosis including the optimized fuzzy algorithm based on the error rate adjustment P, I, D value (Fuzzy PID algorithm) model relies on symmetry principles. A robot is a kind of mechanical device that can program and perform certain operations and mobile tasks under automatic control. The manipulator is a very complex multi-input multi-output non-linear system and the main actuator of the robot. This paper focuses on the design of a control algorithm for a two-degree-of-freedom (2-DOF) manipulator. First, the mathematical model of a 2-DOF articulated manipulator is established, that is, the functional relationship between the input driving force vector and the output rotation angle vector of a 2-DOF manipulator. Then, a set of trajectory planning algorithms are designed by using gradient model control, which can calculate the trajectory of the end-effector of a 2-DOF manipulator according to the user’s task requirements. The experimental results verify the effectiveness of the proposed algorithm.

Approximating power for significance tests with one degree of freedom.

1997 ◽  
Vol 2 (2) ◽  
pp. 186-191 ◽  
Author(s):  
William P. Dunlap ◽  
Leann Myers
Keyword(s):  
Degree Of Freedom ◽  
Significance Tests

Performance analysis of global local mean square error criterion of stochastic linearization for nonlinear oscillator

2019 ◽  
Author(s):  
Nguyen Cao Thang ◽  
Luu Xuan Hung
Keyword(s):  
Performance Analysis ◽  
Mean Square Error ◽  
Nonlinear Oscillators ◽  
Degree Of Freedom ◽  
Equivalent Linearization ◽  
Mean Square ◽  
Error Criterion ◽  
Stochastic Linearization ◽  
Local Mean ◽  
Mean Square Error Criterion

The paper presents a performance analysis of global-local mean square error criterion of stochastic linearization for some nonlinear oscillators. This criterion of stochastic linearization for nonlinear oscillators bases on dual conception to the local mean square error criterion (LOMSEC). The algorithm is generally built to multi degree of freedom (MDOF) nonlinear oscillators. Then, the performance analysis is carried out for two applications which comprise a rolling ship oscillation and two degree of freedom one. The improvement on accuracy of the proposed criterion has been shown in comparison with the conventional Gaussian equivalent linearization (GEL).

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