Global fast non-singular terminal sliding-mode control for high-speed nanopositioning

Peer reviewedPostprin

High-precision Control of a Piezo-driven Nanopositioner Using Fuzzy Logic Controllers

Acknowledgments: The authors would like to thank Douglas Russell for the technical help and Andres San-Millan for data measurements. Financial support via the Elphinstone Research Scholarship, provided by the School of Engineering, University of Aberdeen, to fund Mohammed Altaher’s Ph.D. work is highly appreciated.Peer reviewedPublisher PD

Single-molecule imaging to characterise the transport mechanism of the Nuclear Pore Complex

In the eukaryotic cell, a large macromolecular channel, known as the Nuclear Pore Complex (NPC), mediates all molecular transport between the nucleus and cytoplasm. In recent years, single-molecule fluorescence (SMF) imaging has emerged as a powerful tool to study the molecular mechanism of transport through the NPC. More recently, techniques such as Single-Molecule Localisation Microscopy (SMLM) have enabled the spatial and temporal distribution of cargos, transport receptors and even structural components of the NPC to be determined with nanometre accuracy. In this protocol, we describe a method to study the position and/or motion of individual molecules transiting through the NPC with high spatial and temporal precision

Single-Molecule Imaging to Characterize the Transport Mechanism of the Nuclear Pore Complex

In the eukaryotic cell, a large macromolecular channel, known as the Nuclear Pore Complex (NPC), mediates all molecular transport between the nucleus and cytoplasm. In recent years, single-molecule fluorescence (SMF) imaging has emerged as a powerful tool to study the molecular mechanism of transport through the NPC. More recently, techniques such as single-molecule localization microscopy (SMLM) have enabled the spatial and temporal distribution of cargos, transport receptors and even structural components of the NPC to be determined with nanometre accuracy. In this protocol, we describe a method to study the position and/or motion of individual molecules transiting through the NPC with high spatial and temporal precision

An improved adaptive genetic algorithm for image segmentation and vision alignment used in microelectronic bonding

In order to improve the precision and efficiency of microelectronic bonding, this paper presents an improved adaptive genetic algorithm (IAGA) for the image segmentation and vision alignment of the solder joints in the microelectronic chips. The maximum between-cluster variance (OTSU) threshold segmentation method was adopted for the image segmentation of microchips, and the IAGA was introduced to the threshold segmentation considering the features of the images. The performance of the image segmentation was investigated by computational and experimental tests. The results show that the IAGA has faster convergence and better global optimality compared with standard genetic algorithm (SGA), and the quality of the segmented images becomes better by using the OTSU threshold segmentation method based on IAGA. On the basis of moment invariant approach, the microvision alignment was realized. Experiments were carried out to implement the microvision alignment of the solder joints in the microelectronic chips, and the results indicate that there are no alignment failures using the OTSU threshold segmentation method based on IAGA, which is superior to the OTSU method based on SGA in improving the precision and speed of the vision alignments

An Integrated Design Optimization for Monolithic Mechanical Amplifier in PZT Nano-Positioning Stage

[[abstract]]In order to satisfy the accelerating nanotechnology of high-tech precision manufacturing, it is essential to develop the efficient integration of amplifying device producing very fine resolution. This paper proposes such a development using topological optimal synthesis to design a monolithic mechanical amplifying lever actuated by a PZT in single-axis nano-positioning stage. This one-piece compound compliant mechanism consists of an amplifier and nano-motion bed. The resultant amplifier yields to a larger magnification factor than that in original design. The completed design implementation shows that the presenting design optimization is practical to apply. In addition, it provides a creative computational aided design (CAD) environment and integrated design process for mechanical amplifier and nano-positioning stage.[[notice]]補正完畢[[booktype]]紙

Design, modelling and characterization of a 2-DOF precision positioning platform

This paper presents the mechanical design, parameter optimization and experimental tests of a 2-degree-of-freedom (DOF) flexure-based precision positioning platform, which has great potential application in many scientific and engineering fields. During the mechanical design, the leaf parallelogram structures provide the functions of joint mechanisms and transmission mechanisms with excellent decoupling properties. The dynamic model of the developed positioning platform is established and analysed using pseudo rigid body model methodology. A particle swarm algorithm optimization approach is utilized to perform the parameter optimization and thus improve the static and dynamic characteristics of the positioning platform. The prototype of the developed 2-DOF positioning platform has been fabricated using a wire electric discharge machining technique. A number of experimental tests have been conducted to investigate the performance of the platform and verify the established models and optimization methodologies. The experimental results show that the platform has a workspace range in excess of 8.0×8.0 μm with a stiffness of 4.97 N/µm and first-order natural frequency of 231 Hz. The cross-axis coupling ratio is less than 0.6%, verifying the excellent decoupling performance

Design and computational optimization of a flexure-based XY nano-positioning stage

This thesis presents the design and computational optimization of a two-axis nano-positioning stage. The devised stage relies on double parallelogram flexure bearings with under-constraint eliminating linkages to enable motion in the primary degrees-of-freedom. The structural parameters of the underlying flexures were optimized to provide a large-range and high bandwidth with sub-micron resolution while maintaining a compact size. A finite element model was created to establish a functional relationship between the geometry of the flexure elements and the stiffness behavior. Then, a neural network was trained from the simulation results to explore the design space with a low computational expense. The neural net was integrated with a genetic algorithm to optimize the design of the flexures for compactness and dynamic performance. The optimal solutions resulted in a reduction of stage footprint by 14% and an increase in the first natural frequency by 75% relative to a baseline design, all while preserving the same 50mm range in each axis with a factor of safety of 2. This confirms the efficacy of the proposed approach in improving stage performance through an optimization of its constituent flexures.Mechanical Engineerin

Multi-objective optimization design of parallel manipulators using a neural network and principal component analysis

In this work, a multi-objective optimization design method is proposed based on principal component analysis (PCA) and a neural network to obtain a mechanism's optimal comprehensive performance. First, multi-objective optimization mathematical modeling, including design parameters, objective functions, and constraint functions, is established. Second, the sample data are obtained through the design of the experiment (DOE) and are then standardized to eliminate the adverse effects of a non-uniform dimension of objective functions. Third, the first k principal components are established for p performance indices (k&lt;p) using the variance-based PCA method, and then the factor analysis method is employed to define its physical meaning. Fourth, the overall comprehensive performance evaluation index is established by objectively determining weight factors. Finally, the computational cost of the modeling is improved by combining the neural network and a particle swarm optimization (PSO) algorithm. Dimensional synthesis of a Sprint (3RPS) parallel manipulator (PM) is taken as a case study to implement the proposed method, and the optimization results are verified by a comprehensive performance comparison of robots before and after optimization.</p

An enhanced physics-based model to estimate the displacement of piezoelectric actuators

Piezoelectric actuators are the foremost actuators in the area of nanopositioning. However, the sensors employed to measure the actuator displacement are expensive and difficult, if not impossible, to use. Mathematical models can map the easy-to-measure electrical signals to the displacements of the actuators as the displacement sensors are replaced with the models. In addition, these models can be used in model-based control system design. Two main groups of mathematical models are used for this purpose: black box and physics-based models. As an advantage, the latter has a much smaller number of parameters reducing computational demand in real-time applications. However, physics-based models suffer from (1) the relatively low accuracy of the models and (2) non-standard and ad-hoc parameter identification methods. In this research, to improve the model accuracy, mathematical structure of a well-known physics-based model, the Voigt model, is enhanced by adding two complementary terms inspired by another model, the Preisach model. Then, a standard method based on the evolutionary algorithms is proposed to identify the model’s parameters. The proposed ideas are substantiated to increase the applicability and accuracy of the model, and they are easily extendable to other physics-based models of piezoelectric actuators. The newly proposed enhanced structure of the Voigt model doubles the estimation accuracy of the original model and results in accuracies comparable with black box models.Narges Miri, Morteza Mohammadzaheri and Lei Che