Iterative Controller Parameters Tuning Using Gradient Estimate of Variance Evaluation

Author(s):  
Shiro Masuda
Robotica ◽  
2007 ◽  
Vol 25 (4) ◽  
pp. 467-477 ◽  
Author(s):  
J. Lin ◽  
Z.-Z. Huang

SUMMARYThis research focuses on the issue of dynamic modeling and controlling a robotic manipulator attached to a compliant base. Such a system is known under the name macro–micro system, characterized by the number of control actuators being less than the number of state variables. The equations of motion for a two-link planar elbow arm mounted on an oscillatory base has been presented in this investigation. In order to study the sensitivity of tuning the PID parameters to achieve the desired performance, the Grey relational analysis has first been proposed. Therefore, the aim of this work is to apply Grey theory to optimize parameters for partial states feedback of a PID controller for such a structure. The experimental results of the proposed methodology also show that it is technically and economically feasible to develop a low-cost, reliable, automatic, less time-consuming controller for robotics mounted on oscillatory bases.


2019 ◽  
Vol 55 (5) ◽  
pp. 2347-2358 ◽  
Author(s):  
Haibin Duan ◽  
Mengzhen Huo ◽  
Zhiyuan Yang ◽  
Yuhui Shi ◽  
Qinan Luo

Author(s):  
Zhengsheng Chen ◽  
Minxiu Kong

To obtain excellent comprehensive performances of the planar parallel manipulator for the high-speed application, an integrated optimal design method, which integrated dimensional synthesis, motors/reducers selection, and control parameters tuning, is proposed, and the 3RRR parallel manipulator was taken as the example. The kinematic and dynamic performances of condition number, velocity index, acceleration capability, and low-order frequency are taken into accounts for the dimensional synthesis. Then, to match motors/reducers parameters and keep an economical cost, the constraint equations and the parameters library are built, and the cost is chosen as one of the optimization objectives. Also, to get high tracking accuracy, the dynamic forward plus proportional–derivative control scheme is introduced, and the tracking error is chosen as one of the optimization objectives. Hence, the optimization model including dimensional synthesis, motors/reducers selection and controller parameters tuning is established, which is solved by the genetic algorithm II (NSGA-II). The result shows that comprehensive performances can be effectively promoted through the proposed integrated optimal design, and the prototype was constructed according to the Pareto-optimal front.


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