Parallel structure robots have been receiving growing attention from both academia and industry in recent years. This is due to their advantages over serial structure robots, such as high stiffness, high motion accuracy and a high load-structure ratio. Control of parallel robots, however, produces difficulties to control engineers due to the modelling errors arising from the highly non-linear and complex structures. This paper proposes a dual-model-based structure for error attenuation in the trajectory-tracking control of a parallel robot manipulator. In this design, a conventional model-based control algorithm employing an estimated robot dynamic model is first implemented in the inner loop of the control structure. Then, in order to reduce the unwanted effects caused by modelling erros, another model-based structure, developed based on the concept of the internal model control, is appended in the outer loop of the control structure as a compensator. A combination of these two model-based components results in a novel dual-model-based structure for parallel robot control. Sensitivity analyses show that the effects due to modelling errors and external disturbances can be significantly reduced by applying this new control structure without relying on a high-gain control solution. The effectiveness of this control design is successfully demonstrated by numerical studies on a planar parallel robot with 2 degrees of freedom.
“Low-rank + dual” model based dimensionality reduction