Due to the demands from the robotic industry, robot structures have evolved from serial to parallel. The control of parallel robots for high performance and high speed tasks has always been a challenge to control engineers. Following traditional control engineering approaches, it is possible to design advanced algorithms for parallel robot control. These approaches, however, may encounter problems such as heavy computational load and modeling errors, to name it a few. To avoid heavy computation, simplified dynamic models can be obtained by applying approximation techniques, nevertheless, performance accuracy will suffer due to modeling errors. This paper suggests applying an integrated design and control approach, i.e., the Design For Control (DFC) approach, to handle this problem. The underlying idea of the DFC approach can be illustrated as follows: Intuitively, a simple control algorithm can control a structure with a simple dynamic model quite well. Therefore, no matter how sophisticate a desired motion task is, if the mechanical structure is designed such that it results in a simple dynamic model, then, to design a controller for this system will not be a difficult issue. As such, complicated control design can be avoided, on-line computation load can be reduced and better control performance can be achieved. Through out the discussion in the paper, a 2 DOF parallel robot is redesigned based on the DFC concept in order to obtain a simpler dynamic model based on a mass-balancing method. Then a simple PD controller can drive the robot to achieve accurate point-to-point tracking tasks. Theoretical analysis has proven that the simple PD control can guarantee a stable system. Experimental results have successfully demonstrated the effectiveness of this integrated design and control approach.
Contribution to generic modeling and vision-based control of a broad class of fully parallel robots
