A model predictive control-based motion cueing algorithm with consideration of joints' limitations for hexapod motion platform

© 2019 IEEE. The regeneration of the motion signals of a real vehicle is not physically possible because of the workspace limitations of the platforms. The motion cueing algorithms (MCAs) are in charge of reproduction of the motion sensation for the drivers of simulation platforms as realistic as possible to the real vehicles. The model predictive control-based motion cueing algorithms (MPC-based MCAs) are recently used to find the optimal value of the input signals with consideration of the linear constraints of the platform in the Cartesian coordinate system of the mechanism. A new time-varying MPC-based MCA is introduced for the first time in this research by considering the joints' limitations of the mechanism inside the MPC model for longitudinal channel. The proposed model can consider the physical limitation of the active joints instead of substituting the limitation in the Cartesian coordinate system. The validation of the proposed model is performed using MATLAB software and the results prove that the proposed time-varying MPC-based MCA leads better motion sensation compared with the existing MPC-based MCA.