High-fidelity hexarot simulation-based motion platform using fuzzy incremental controller and model predictive control-based motion cueing algorithm

The real vehicle motion signals cannot be applied for the simulation-based motion platforms (SBMPs) due to the restricted workspace of the SBMPs. The motion cueing algorithms (MCAs) have been used to regenerate the same motion feeling of the real vehicle with consideration of the SBMP's limited workspace. The idea of the model predictive control (MPC) is used recently to find the optimal value of the input signal with consideration of the SBMPs’ limitations. The hexarot manipulator is developed as a mid-sized SBMP with high capability of generating the angular displacement compared to hexapod SBMP. It is the first time that hexarot manipulator is employed as an SBMP with controller unit due to its high workspace limitation, especially in roll angle. In addition, the main contribution of this research is to design and develop a fuzzy incremental controller to configurate the hexarot SBMP using MPC-based MCA to improve the motion feeling of the high-frequency signals compared with the traditional PID controller. The proposed method is verified using MATLAB software. Finally, the results demonstrate the right follow of the motion signals using MPC-based MCA, which is not possible using the common hexapod manipulators.