Use of load-side MEMS accelerometers in servo positioning of two-mass-spring systems

In many industrial applications, servo-positioning devices are composed of an electric motor, connected to the mechanical load through elastic elements. The problem of two-mass resonant systems has been studied for long time, and the main issue targeted has been the development of accurate and robust servo positioning devices, without making use of a load-side position sensor. Indeed, by using properly designed observers, it is possible to obtain accurate information on the load position, but the robustness of control laws based on this solution is known to be rather weak. In this paper, we explore the feasibility, the performance and the robustness of a an optimal feedback control, in which the full state of the system is obtained by a Kalman Filter (KF), which process not only the position measurement of the motor, but also the acceleration measurement of the load, obtained by using a low-cost MEMS sensor. The experimental results confirm that by using this additional sensor, the robustness of the control is greatly improved, thanks to the higher accuracy of the estimate of the load side variables.