In this article, the ultrahigh-precision planar motion control problem is investigated for a novel long-stroke multileaf spring based microstage, by considering the cross-axial coupling-induced varying stiffness. In particular, a discrete-time dynamical model with the stress stiffening effect is presented in a parameter varying form, where a discrete-time adaptive extended state observer (ESO) with exponential forgetting factor is developed based on Kalman-like observer method, and a synergetic control theory (SCT) approach is further proposed combining the observer structure to achieve microscale multiaxis motion control. The conditions on the convergence of the adaptive ESO and the robust stability of the closed-loop system are also derived with a theoretical analysis. Finally, the proposed control architecture is implemented (in real time) on a designed microstage, demonstrating significant performance improvement over existing results such as proportional-integral-derivative (PID) control and conventional active disturbance rejection controllers control methods.

Detection of structural changes in machine state attracts increasing attention for the monitoring and prognosis of rotating machinery. Very recently, the graph model has been introduced and adopted for modeling of normal machine state so as to investigate the likelihood of potential changes by the use of Martingale-test. This paper expands the potential of the graph model toward correlation-analysis-based monitoring applications, where the problem of measuring graph similarity is the main challenge due to domain specificity. We first investigated six typical schemes taken from other areas for this purpose, and found that they show discriminative capacities when dealing with changes with different types in the machine condition monitoring scenarios. Subsequently, based on a procedure called “method of ranks,” we have chosen four schemes among them which are potentially promising for our usage. Meanwhile, based on these metrics, two machine learning based similarity metrics are proposed to further improve their practical values by combining them. At last, comprehensive theoretical interpretations and comparisons of presented methods are made both in simulated scenarios and real-engineering monitoring applications.

In this paper, we consider the design and analysis of an X–Y parallel piezoelectric-actuator-driven nanopositioner with a novel two-stage amplifying mechanism, where the mechanical design is optimized to achieve a large stroke and high-natural frequency for the purpose of high-performance servomechanism. The parallel kinematic X–Y flexure mechanism provides good geometric decoupling. The kinematic and dynamic analysis shows that the proposed design has a large work space and high bandwidth, which is further verified by finite-element analysis. The analysis results demonstrate that the designed nanopositioner has a large workspace more than 200 µm and a high-natural frequency at about 760 Hz. Furthermore, the dynamical model of the nanopositioner, including the dynamics of the PZT actuators, is also generated from the perspective of input/output transfer functions, and the parameters are identified by frequency-response experiments, which can be used for nano precision servomechanism.