Model Predictive Feedforward Compensation for Control of Multi Axes Hybrid Kinematics on PLC

Hybrid multi axes kinematics with kinematic redundancy have become more important in industrial applications since they offer a large workspace, high stiffness, and accuracy. However, the kinematic equations are complex because the number of solutions for the inverse kinematic problem is infinite. Therefore, a model predictive approach using optimization algorithms based on the (inverse) kinematic problem is beneficial since exisiting ambiguities can be exploited to achieve a certain goal, e.g. fast or smooth movement. However, in order to be used in an industrial context, it is crucial, that the approach is computationally efficient so that it can be implemented on a Programmable Logic Controller (PLC). This paper presents a computationally efficient model predictive feedforward compensation for position control of a multi axes hybrid kinematic. The simulative results show that a system with such a model predictive approach reaches set-points faster than current approaches. Furthermore, we focus on the future implementation of the algorithms on a PLC.