Output regulation and the identification of plant parameters are generally conflicting objectives. However, over-actuated systems provide an opportunity to achieve identification and control objectives simultaneously, with minimal compromise. This paper presents an optimization-based simultaneous identification and control (SIC) methodology for permanent magnet synchronous machines (PMSMs) which exploits the over-actuated nature of the machine. A receding horizon control allocation (RHCA) approach is used which includes a metric for maximizing the excitation characteristics of the generated reference current trajectories. The reference currents produced by the RHCA are fed to a lower-level adaptive current regulator which ensures asymptotic tracking of a reference model. The importance of reformulating the RHCA problem to include past input and state data, in addition to predicting future input and state trajectories, is discussed. Simulation results demonstrating the effectiveness of the proposed RHCA-SIC methodology, as well as the effects of neglecting past input and state data, are presented.
['David M. Reed', 'Jing Sun', 'Heath Hofmann']
A receding horizon approach to simultaneous identification and torque control of permanent magnet synchronous machines