This paper presents a novel mechatronic approach to modeling, control design, and experimental validation of a two-axis high-accuracy ball screw drive system. At first, a general mathematical model ...is developed by the Lagrange’s equation of Motion to characterize the dynamic behaviors of all the variables for an
N
-degrees of freedom system that includes electric behavior of the DC motors. Thus, the model provides a general framework for the control algorithm design. A robust PD-hyperbolic–type control strategy is proposed based on the representation of a nonlinear dynamic model for the trajectory tracking that solves the problem of regulation and position control. The stability method of Lyapunov is applied; in addition, the asymptotic stability of an equilibrium point is analyzed for the closed-loop dynamic model. The proposed control law ensures the dynamic performance of the closed-loop signals and desired tracking precision. On the other hand, the description of a new and original FPGA-based programmable microprocessor design is introduced which consists of its own design approaches of a hardware/software architecture. Finally, based on a built prototype of a ball screw drive system, experimental tests and simulations with motion trajectory tracking are conducted to verify the proposed general mathematical model and the control law. Experimental results demonstrate an excellent tracking trajectory and desired precision performance, which validates the feasibility and effectiveness of the proposal.
Buried plastic scintillator muon telescope (BATATA) Alfaro, R.; De Donato, C.; D’Olivo, J.C. ...
Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment,
05/2010, Letnik:
617, Številka:
1
Journal Article
Recenzirano
Muon telescopes have multiple applications in the area of cosmic ray research. We are currently building such a detector with the objective of comparing the ground penetration of muon vs. ...electron-gamma signals originated in cosmic ray showers. The detector is composed by a set of three parallel dual-layer scintillator planes, buried at fixed depths ranging from 120 to
600
g
/
cm
2
. Each layer is
4
m
2
and is composed by 49 rectangular strips of
4
cm
×
2
m
, oriented at a
90
∘
angle with respect to its companion layer, which gives an
xy
-coincidence
pixel of
4
×
4
cm
2
. The scintillators are MINOS extruded polystyrene strips, with an embedded Bicron BC92 wavelength shifting (WLS) fibers, of 1.5
mm in diameter. Light is collected by Hamamatsu H7546B multi-anode PMTs of 64 pixels. The front-end (FE) electronics works in counting mode and signals are transmitted to the surface DAQ stage using low-voltage differential signaling (LVDS). Any strip signal above threshold opens a GPS-tagged
2
μ
s
data collection window. Data, including signal and background, are acquired by a system of FPGA (Spartan 2E) boards and a single-board computer (TS7800).
Dynamic parameters are crucial in designing robotics systems because they reflect an actual robot. Conventional identification methods require that the robot execute the optimal motion; however, they ...spend time trying all possible trajectories in the robot. This article shows the identification of a robot arm of 2 degree-of-freedom with an algorithm based on a convolutional neural network (CNN) and their dynamic model. The proposal consists of a CNN that uses an image construct with a proposed conversion technique and the robot signals. The algorithm gets the parametric residuals from this signal image to find the parameters without trajectory optimization. An embedded system on a Field Programmable Gate Array (FPGA) has the classical controller Proportional-Derivative to execute a predefined trajectory for the identification. The identified parameters and the predefined motion rebuild the torque with the dynamic model. A proposed evaluation metric based on the discrete cosine transform evaluates the similarity of the actual and reconstructed torques. Four numeric tests verify the algorithm by torques created with the dynamic model, the predefined trajectory, and a parameter set. The similarity of numeric torques and their rebuilding overcomes 97.38%, and the experimental and rebuilt torque with the identified parameters is over 93.55%. The proposed algorithm is compared with least-squares, and the results show that the proposed method provides better identification of the experimental robot.
This article presents a software platform (SP) that helps generate convolutional and feed-forward neural networks and a parametric identification algorithm is proposed for a Cartesian robot using ...convolutional neural networks (CNN) generated and trained with the proposed SP. The user interface is friendly and aids in developing convolutional and feed-forward neural networks. The SP is made in LabVIEW®. The user does not need the complete knowledge of mathematics used to perform the training or execution of the network or the programming skills to perform the code that performs such tasks. The SP is designed to reduce the deployment time of neural networks, providing the user with a graphical interface that guides the user through the formation and development of the neural network, this is one of the main contributions. The SP interface is described in this article, showing all the options offered. Five neural networks are presented to prove and demonstrate the software platform's use. The dynamic models of the Cartesian robot are used; one has six parameters and the other ten parameters. The maximum similarity achieved by the identification algorithm with the six-parameter dynamic model was 99.15% and 99.92% for the ten-parameter model; both are numerical torque analyses. A real Cartesian robot was identified, and five experimental torques were reconstructed for each axis; the maximum similarity was 97.87%. The proposed algorithm is compared with least squares, which obtain 95.81%. Therefore, the results show that the proposed method generates better parametric identification.
The phenomenon of non-linearity is the main problem of a DC motor and optimum performance cannot be obtained by the calculation of the controller's parameters using conventional methods. However, a ...DC motor is considered an extremely common device by the low-cost and effective dynamic response in various applications. Thus, it has been a subject for research studies to take advantage of its maximum performance. This manuscript proposes an experimental methodology that consists of the following: The DC motor's characterization method for finding the ideal frequency. The design of the Firmware-based Pulse Width Modulation (PWM) generating module and the P, PD, PID controller's implementation in an own FPGA-based programmable microprocessor to obtain almost the same performance as a servo-amplifier commercial of direct-drive. The PWM is a technique widely used to regulate the speed of rotation of a DC motor, in this case, the duty cycle of the PWM is used to provide the torque necessary to the mechanics of the system in order to look for a linear relationship but using the right frequency of the characterized DC motor. Finally, based on a built prototype of a micro-positioning system using the characterized motors, and the mathematical model, in both cases the three controllers were applied in order to establish the comparison between the responses, seeking to observe if the experimental results show a great difference with respect to the simulation results. The main aim of this study is to show that the proposed methodology works. However, since there was no significant difference in both results, motors used in the closed-loop control present approximately the same linear response as that of the motor model used in the simulation.
Multicavity fiber laser Gomez-Pavona, L.C.; Ortega Mendoza, J.G.; Berrospe-Rodriguez, C. ...
2008 Digest of the IEEE/LEOS Summer Topical Meetings,
2008-July
Conference Proceeding
We report the experimental study of a multicavity fiber laser system conformed by an array of three erbium-doped fibers laser cavities. We have demonstrated that through the nonlinear interaction of ...evanescent fields among one cavity with active modulation and all the others it is possible to accomplish the mode-locking for all the laser cavities. Moreover, both temporal and spectral synchronous pulse generation between cavities is obtained with an appropriate selection of pump intensity, frequency modulation and coupling ratio.
This paper presents a novel methodology to identify the dynamic parameters of a real robot with a convolutional neural network (CNN). Conventional identification methodologies use continuous motion ...signals. However, these signals are quantized in their amplitude and are discrete in time. Therefore, the time required to identify the parameters of a robot with a limited measurement system is related to an optimized motion trajectory performed by the robot. The proposed methodology consists of an algorithm that uses a trained CNN with the data created by the dynamical model of the case study robot. A processing technique is proposed to transform the position, velocity, acceleration, and torque robot signals into an image whose characteristics are extracted by the CNN to determine their dynamic parameters. The proposed algorithm does not require any optimal trajectory to find the dynamic parameters. A proposed time-spectral evaluation metric is used to validate the robot data and the identification data. The validation results show that the proposed methodology identifies the parameters of a Cartesian robot in less than 1 second, exceeding 90% of the proposed evaluation metric and 98% for the simulation results.
In this article, we present a system to measure current in the range of 0 to 10 μA with high-voltage isolation up to 5 kV. This current monitor consists of three ammeters connected in series, to ...improve the resolution in the measurement. The design features several innovative elements such as using low voltage to provide power to the devices to measure the current and digitize it with a sampling frequency of 1 KHz, it is generated based on a DC-DC converter that produces three voltages, +12 V, −12 V, and 5 V, from a conventional 10 V source. The three voltages are referenced to the same floating ground. The DC-DC converter has a high voltage insulation up to 5 kV and four optocouplers with an insulation up to 20 kV are used to read the digitized data. The introduction of a DC-DC converter contributed to reduce the noise level in the analog part of the circuit which has been resolved implementing shields inside the board. In particle physics, several systems are used to detect particles in high-energy physics experiments such as Gas Electron Multiplier (GEM), micromegas, etc. GEMs suffer small deteriorations due to discharges in constant operation and require monitoring the current consumption at high frequency (1 kHz). In this work, we present the design and operation of a 0 to 10 μA auto scale ammeter. The results obtained by monitoring the current in a 10 × 10 cm2 GEM are shown.
PDF
