Sliding Mode and Continuous Estimation Techniques for the Realization of Advanced Control Strategies for Parallel Kinematics

The realization of advanced control concepts for parallel kinematic machines (PKM) requires the knowledge of system states. Despite the fact that the direct kinematic problem (DKP) is not explicitly solvable for PKMs they need not to be measured directly. This can be achieved by the usage of state estimation techniques, which can also be extended for disturbance estimation and hence allow for disturbance compensation - a possibility that direct measurement devices or iterative algorithms to solve the DKP cannot provide for. Subsequently, two possibilities for the realization of adequate estimation are presented: a new approach for the state and disturbance estimation for PKMs via sliding mode techniques and a more classical approach based on continuous Kalman filtering. Their suitability for the usage within an advanced state control scheme is validated simulatively with models of different complexity of a hydraulically actuated hexapod intended to be used as a motion simulator for automotive testing purposes.