Inverse Optimal Control Based on Improved Grey Wolf Optimization Algorithm

This study demonstrates the integration of Improved Grey Wolf Optimization (IGWO) Algorithm with Inverse Optimal Control Methodology. In inverse optimal control technique, a parametric Lyapunov function is defined and then the optimal values of the parameters are determined. In this work, the optimization problem is formulated with two objective functions to be simultaneously minimized. These objective functions are combined with scaling factors and IGWO is implemented to obtain the optimal values of the parameter matrix. The performance of the proposed method is evaluated with simulations on a discrete, nonlinear benchmark problem. After the optimal values of the parameter matrix are obtained, system states and control input signal are illustrated.