Parallel Dynamics Computation and H∞ Acceleration Control of Parallel Manipulators for Acceleration Display

Abstract

In this paper, we propose a control scheme of parallel manipulators focusing on the accuracy of acceleration on the end plate, an important factor when parallel manipulators are used as acceleration displays such as a driving simulator. In order to achieve a smooth and accurate acceleration on the end plate, we combine two controllers: A dynamic controller to achieve accuracy of the position and to stabilize the system, and an H∞ controller to feedback the acceleration of the end plate to cope with the unmodeled dynamics such as mechanical flexibility and friction. The main problem of dynamic control is computational complexity. We applied parallel processing to reduce the latency and realized real-time dynamic control. The designed H∞ controller is added outside the closed loop of dynamic control to remove the vibration of the structure and the influence of unmodeled dynamics.

Robust decentralized joint control of a 3-PRS parallel mechanism based on a simplified model

“…Equation (4) indicates that the distance between each tip of the fingers is constrained be constant and it could be used to specify the coupling relationship between the joint coordinates. Assume that i S Q is the externally applied force between the slider and their corresponding ball screw as shown in Fig.…”

Dynamics and control of a planar 3-DOF parallel manipulator with actuation redundancy

“…In order to apply the vast control literature developed for the serial counterparts to redundantly actuated parallel manipulators, it is necessary to develop an efficient dynamic model. There are many papers on dynamics and control of parallel manipulators with non-redundant actuation [16][17][18][19]. However, research on dynamics and control of redundantly actuated parallel manipulators is relatively fewer.…”

Dynamic modeling and computational efficiency analysis for a spatial 6-DOF parallel motion system

“…The efficiency of the simplified model neglecting leg inertia can be improved, but the accuracy may be reduced greatly. To shorten the execution time of full dynamic model of general parallel manipulator, Li et al [18] used 32 CPUs to do the parallel computation of the dynamics within 0.25 ms. Yamane et al [19] applied 4 CPUs and multi-thread programming to implement parallel processing of the dynamics. The parallel algorithm can improve the computational efficiency of the dynamics without losing accuracy, yet it needs complicated software and hardware which limit the application of the algorithm.…”