A motion cueing model for mining and forestry simulator platforms based on Model Predictive Control

Sammanfattning: Oryx Simulations produce simulators for mining and forestry machinery used for educational and promotional purposes. The simulators use motion platforms to reflect how the vehicle moves within the simulator. This platform tilts and accelerates the driver in order to enhance the experience. Previously a classical washout filter algorithm has been used to control the platform which leaves something to be desired regarding how well it reflects the vehicles movement, how easy it is to tune and how it handles the limits of the platform. This thesis aims to produce a model that accurately reflects angles, velocities and accelerations while in the mean time respecting the limits of the platform. In addition to this the developed model should be easy to modify and tune. This is achieved using so-called Model Predictive Control which achieves the wanted behaviour by predicting how the platform will move based on its current state while implementing the constraints of the platform directly into the model. Since all of the parameters in the model are actual physical quantities, this makes the model easier to tune. A key component in this solution is the so-called tilt coordination which consists of substituting a lateral/longitudinal acceleration with the acceleration of gravity by tilting the driver. Constructing and implementing this model in Matlab we verify it by using data extracted from the simulator environment. We see that the parameters consisting of angles, rotational velocities and linear accelerations are tracked very well while respecting the constraints for the platform, constraints that can be easily changed to fit the current simulator.We also see that the model successfully implements tilt coordination into the behaviour of the platform. This model performs extraordinarily well in theory, what remains is to implement this to the motion platform and fine-tune it.