Ultra-precision measurement and control of angle motion in piezo-based platforms using strain gauge sensors and a robust composite controller.

The measurement and control strategy of a piezo-based platform by using strain gauge sensors (SGS) and a robust composite controller is investigated in this paper. First, the experimental setup is constructed by using a piezo-based platform, SGS sensors, an AD5435 platform and two voltage amplifiers. Then, the measurement strategy to measure the tip/tilt angles accurately in the order of sub-µrad is presented. A comprehensive composite control strategy design to enhance the tracking accuracy with a novel driving principle is also proposed. Finally, an experiment is presented to validate the measurement and control strategy. The experimental results demonstrate that the proposed measurement and control strategy provides accurate angle motion with a root mean square (RMS) error of 0.21 µrad, which is approximately equal to the noise level.

Experimental studies on model reference adaptive control with integral action employing a rotary encoder and tachometer sensors.

In this paper, an adaptive law with an integral action is designed and implemented on a DC motor by employing a rotary encoder and tachometer sensors. The stability is proved by using the Lyapunov function. The tracking errors asymptotically converge to zero according to the Barbalat lemma. The tracking performance is specified by a reference model, the convergence rate of Lyapunov function is specified by the matrix Q and the control action and the state weighting are restricted by the matrix Γ. The experimental results demonstrate the effectiveness of the proposed control. The maximum errors of the position and velocity with the integral action are reduced from 0.4 V and 1.5 V to 0.2 V and 0.4 V, respectively. The adaptive control with the integral action gives satisfactory performance, even when it suffers from input disturbance.