System identification of a pick-and-place mechanism driven by a permanent magnet synchronous motor

The main objective of this study is to utilize two dynamic models: a mathematical model and a simple model, to identify a pick-and-place mechanism (PPM) which is driven by a permanent magnet synchronous motor (PMSM). In this paper, Hamilton’s principle is employed to derive the mathematical model, which is a nonlinear differential equation, while Newton’s second law is utilized to derive the simple linear model. In system identification, we adopt the real-coded genetic algorithm (RGA) to find not only the parameters of the PPM, but also the PMSM simultaneously. From the identification simulations and experimental results, it is demonstrated that the identification results of the mathematical model present the better matching with the experimental results of the system.