Efficient Modeling Method of Vehicle Dynamics Operating at a Low Speed and Its Application to Non-Linear Optimal Controller Design

In this paper, we propose a non-analytical but effective self-organizing modeling method, where system dynamics of interest are constructed in a polynomial affine formation with high granularity. The conventional data mining technique has the assessment scheme for representativeness of the developed model. However, if the model is applied to extract the desired values without considering the structural peculiarities such as input pattern used for constructing the dynamics, hardware specification used for data acquisition, and so on, it possibly shows substantial margin of modeling error. In order to correspond this type of control paradigm, we define the permissible set of state and input variables in order to characterize the data used for developing the model. The developed model is then applied to the programming based optimal control scheme where the optimal inputs are selected among the permissible set of the input variable, considering all the limitations specified by linear inequalities.