The Iterative Learning Control of a Stewart Platform System
摘要
The real-time path-tracking control of Stewart platform (SP) is very difficult, because the six links must be actuated and controlled simultaneously to track the desired trajectory. The desired length trajectory of the six actuators is obtained using inverse kinematic mechanism. To achieve the precise spatial motion of SP, there is a limitation on the permissible tracking error for each actuator. This paper presents a real-time implementation of iterative learning control (ILC) for a Stewart platform manipulator. A PD-type ILC algorithm with time delay parameters are studied to control the upper plate of the Stewart platform to track a desired trajectory. Two real-time experiments validate the proposed method with the permissible tracking errors.