فهرست مطالب h. salarieh

The problem of tracking control is addressed for rigid bodies with interior shallow-water sloshing. The liquid motion is modeled by the Saint-Venant equations, coupled with the ODE of the rigid body, leading to a global system with an ODE-hyperbolic PDE cascade structure. The paper aims to design an innovative boundary feedback framework for a pre-specified position to deal with rigid body tracking errors. Using only one control force applied to the rigid body, the formulated strategy efficiently stabilizes both the finite- and infinite-dimensional states. The main complexity lies in the fact that no sensor can be implemented in the liquid domain. Indeed, the proposed stabilizing feedback law simply requires measurements of (i) the rigid body position error and velocity and (ii) the liquid pressure at the cavity walls (liquid boundary). The asymptotic stability of the closed-loop system is analyzed using the Lyapunov direct method and LaSalle’s invariance principle without any discretization, reduction, and linearization. Additional controller features are highlighted by simulation results, including its benefits in contrast to the corresponding PD controller and its robustness to time delay and system uncertainty.

This paper presents a novel method for observation of the stage position in a 2D Nano-positioning system based on a hybrid Kalman filter. In the proposed method, there is no need to measure the stage position directly using complex and costly capacity sensors. Instead, by using traditional piezo actuators equipped with strain gauge sensors, the deflection of the magnification system at the position of actuators is measured. Then, by employing a powerful estimation algorithm named as Kalman filter, the displacements of the stage are observed. The designed hybrid Kalman filter uses dynamical equations of motion in the prediction step. The piezo actuators deflections are measured and exploited to correct the predicted values for the system state variables. In order to simulate realistic conditions, a relatively exact COMSOL model has been developed for the nano-positioner where noise has been added to the piezo displacements obtained by simulating this model and these noisy data are used as measurements in the Kalman filter algorithm. The designed hybrid Kalman filter is examined for three different updating time steps. The results show that the designed Kalman filter appropriately estimates the stage displacements, and its accuracy is improved when the filter time step reduces.