Adaptation-Oriented Near-Optimal Control and Robust Synthesis of an Overhead Crane System

In this paper, we develop an adaptation-oriented approximate optimal control strategy and apply it to perform robust stabilization of an overhead crane system including complex nonlinearity. Via employing a novel updating rule to the adaptive critic structure, the near-optimal control law can be learnt based on the converged weight vector. By further considering the dynamical uncertainties, it is proven that the developed near-optimal control law can achieve uniform ultimate boundedness of the closed-loop state vector, thereby guaranteeing a certain extent of robustness for the uncertain nonlinear plant. An experimental simulation with respect to the overhead crane system is also conducted to verify the performance of the present control method.