The continuous trend towards miniaturization and multi-functionality embedded in products and processes calls for an ever-increasing research and innovation effort in the development of micro components and related micro manufacturing technologies [...]

https://www.mdpi.com/2072-666X/10/5/340/pdf

Product/Process Fingerprint in Micro Manufacturing.

This paper proposes a method for learning the process of curve fitting through a general class of totally positive rational bases. The approximation is achieved by finding suitable weights and control points to fit the given set of data points using a neural network and a training algorithm, called AdaMax algorithm, which is a first-order gradient-based stochastic optimization. The neural network presented in this paper is novel and based on a recent generalization of rational curves which inherit geometric properties and algorithms of the traditional rational Bezier curves. The neural network has been applied to different kinds of datasets and it has been compared with the traditional least-squares method to test its performance. The obtained results show that our method can generate a satisfactory approximation.

https://www.mdpi.com/2227-7390/8/12/2197/pdf

Neural-Network-Based Curve Fitting Using Totally Positive Rational Bases

A novel nanopositioning platform (referred as NanoPla) in development has been designed to achieve nanometre resolution in a large working range of 50 mm × 50 mm. Two-dimensional (2D) movement is performed by four custom-made Halbach linear motors, and a 2D laser system provides positioning feedback, while the moving part of the platform is levitating and unguided. For control hardware, this work proposes the use of a commercial generic solution, in contrast to other systems where the control hardware and software are specifically designed for that purpose. In a previous paper based on this research, the control system of one linear motor implemented in selected commercial hardware was presented. In this study, the developed control system is extended to the four motors of the nanopositioning platform to generate 2D planar movement in the whole working range of the nanopositioning platform. In addition, the positioning uncertainty of the control system is assessed. The obtained results satisfy the working requirements of the NanoPla, achieving a positioning uncertainty of ±0.5 µm along the whole working range.

2D Positioning Control System for the Planar Motion of a Nanopositioning Platform

This paper focuses at charge estimators of piezoelectric actuators with a sensing capacitor. They have been claimed in the literature to be outperformed by their newly emerged competitors, charge estimators with a sensing resistor, widely known as digital charge estimators. This paper proposes a digital implementation of capacitor-based estimators and compares them with resistor-based ones both analytically and experimentally. Although, the sensing capacitors are normally bulkier than the sensing resistors used in newer resistor-based estimators; a resistor-based estimator needs to have a variable resistance to deal with different excitation frequencies satisfactorily; this is a major drawback which does not exist in capacitor-based estimators. Both capacitor-based and resistor-based estimators, if designed appropriately, are quite comparable in terms of voltage drop and range of measurable charge. This research concludes that capacitor-based estimators, with right design and implementation, can be still of wide use in nanopositioning.

/pdf/assessment-of-capacitor-based-charge-estimators-for-16xet9ds6h.pdf

Assessment of Capacitor-based Charge Estimators for Piezoelectric Actuators

Owing to the benefits of programmable and parallel processing of the field programmable gate arrays (FPGAs), they have been widely used to the realization of digital controllers and motor drive systems. In this study, we adopt the FPGA chip to realize the Linear Shaft Motor (LSM) drive system which includes the position, speed and current vector controls. Linear shaft motor is a special motor which has the magnet as the shaft and stator coils are on the forcer. Thus, it reveals a small mechanical time constant. In addition, the electrical side can be looked as a general three-phase Alternating Current (AC) system which can be powered by inverter and vector control technique can be applied to the system. The designed system needs high performance calculation ability about position/speed control and vector current control loops. The mathematical model of linear shaft motor drive system is first built and simulated by MATLAB/Simulink and the accuracy about the effect from the speed estimation method is proposed. The resulting digital model of the drive system is stored into Verilog Hardware Description Language (Verilog HDL) codes and realized by FPGA. At last, the hardware circuits as well as the power module are used to test the performance of the developed hardware system in terms of the trapezoidal velocity profile. The experimental results show that the designed system realized by FPGA has attained the desired performance.

https://www.mdpi.com/2075-1702/7/3/59/pdf

Field Programmable Gate Array-Based Linear Shaft Motor Drive System Design in Terms of the Trapezoidal Velocity Profile Consideration

A two-dimensional (2D) nanopositioning platform stage (NanoPla) is in development at the University of Zaragoza. To provide a long travel range, the actuators of the NanoPla are four Halbach linear motors. These motors present many advantages in precision engineering, and they are custom made for this application. In this work, a one-dimensional (1D) control strategy for positioning a Halbach linear motor has been developed, implemented, and experimentally validated. The chosen control hardware is a commercial Digital Motor Control (DMC) Kit from Texas Instruments that has been designed to control the torque or the rotational speed of rotative motors. Using a commercial control hardware facilitates the applicability of the developed control system. Nevertheless, it constrains the design, which needs to be adapted to the hardware and optimized. Firstly, a dynamic characterization of the linear motor has been performed. By leveraging the dynamic properties of the motor, a sensorless controller is proposed. Then, a closed-loop control strategy is developed. Finally, this control strategy is implemented in the control hardware. It was verified that the control system achieves the working requirements of the NanoPla. It is able to work in a range of 50 mm and perform a minimum incremental motion of 1 μm.

https://www.mdpi.com/2072-666X/9/9/421/pdf

One-Dimensional Control System for a Linear Motor of a Two-Dimensional Nanopositioning Stage Using Commercial Control Hardware.

Nanotechnology applications demand high accuracy positioning systems. Therefore, in order to achieve sub-micrometer accuracy, positioning uncertainty contributions must be minimized by implementing precision positioning control strategies. The positioning control system accuracy must be analyzed and optimized, especially when the system is required to follow a predefined trajectory. In this line of research, this work studies the contribution of the trajectory definition errors to the final positioning uncertainty of a large-range 2D nanopositioning stage. The curve trajectory is defined by curve fitting using two methods: traditional CAD/CAM systems and novel algorithms for accurate curve fitting. This novel method has an interest in computer-aided geometric design and approximation theory, and allows high relative accuracy (HRA) in the computation of the representations of parametric curves while minimizing the numerical errors. It is verified that the HRA method offers better positioning accuracy than commonly used CAD/CAM methods when defining a trajectory by curve fitting: When fitting a curve by interpolation with the HRA method, fewer data points are required to achieve the precision requirements. Similarly, when fitting a curve by a least-squares approximation, for the same set of given data points, the HRA method is capable of obtaining an accurate approximation curve with fewer control points.

https://www.mdpi.com/2072-666X/10/9/597/pdf

Marta Torralba Gracia

Papers

One-Dimensional Control System for a Linear Motor of a Two-Dimensional Nanopositioning Stage Using Commercial Control Hardware.

Trajectory Definition with High Relative Accuracy (HRA) by Parametric Representation of Curves in Nano-Positioning Systems.