Feedback linearization control of a two-link robot using a multi-crossover genetic algorithm

In this paper, we propose a novel multi-crossover genetic algorithm (GA) to identify the system parameters of a two-link robot. The resulted system model by the proposed GA is then applied to the feedback linearization control such that the two-link robot system can be transferred to a linear model with a nonlinear bounded time-varying uncertainty. To deal with the uncertainty, a sliding mode control approach is designed to achieve the tracking control. Finally, some simulation results are demonstrated to show the utility of our proposed method.