Industrial Servomotor Research Articles

Development and Performance Evaluation of Integrated Hybrid Power Module for Three-Phase Servo Motor Applications.

This study aims to develop a 30 kHz/12 kW silicon carbide (SiC)/Si integrated hybrid power module (iHPM) for variable frequency drive applications, particularly industrial servo motor control, and, additionally, to theoretically and experimentally assess its dynamic characteristics and efficiency during operation. This iHPM integrates a brake circuit, a three-phase Si rectifier, and a three-phase SiC inverter within a single package to achieve a minimal current path. A space-vector pulse width modulation (SVPWM) scheme is used to control the inverter power switches. In order to reduce parasitic inductance and power loss, an inductance cancellation design is implemented in the Si rectifier and SiC inverter. The switching transients and their parasitic effects during a three-phase operation are assessed through an electromagnetic-circuit co-simulation model, by which the power loss and efficiency of the iHPM are estimated. The modeled parasitic inductance of the inverter is validated through inductance measurement, and the effectiveness of the simulated results in terms of switching transients and efficiency is verified using the experimental results of the double pulse test and open-loop inverter operation, respectively. In addition, the power loss and efficiency of the SiC MOSFET inverter are experimentally compared against those of a commercial Si IGBT inverter.

High-precision magnetic encoder module design based on real-time error compensation algorithm

The continuous development of industrial automation requires more and more control precision for automated control systems. As a key component of the servo motor control system, the encoder has a great influence on the accuracy of the control system. Although the common photoelectric encoder has relatively high precision, its control structure is limited by these unfavorable external environments due to its complicated structure, difficulty in integration, and vulnerability to external environments such as dust, oil, water vapor, and vibration. A high-precision magnetic encoder design based on error compensation algorithm proposed in this paper can not only effectively overcomes the influence of these unfavorable conditions, but also introduces an error compensation algorithm based on ordinary magnetic encoder, which can be compared with ordinary magnetic encoder. The encoder has higher position feedback accuracy and greater stability. it can provide position information with real-time error not exceeding 0.2° within general industrial servo motor speed range. The high-precision magnetic encoder module has low cost, simple structure and easy integration, and also has considerable practical value in the field of industrial automation.

Controlador de servomotores industriales mediante un microcontrolador utilizando MicroPython

Electrical motors are indispensable machines in the industry, thus it is necessary to ensure that engineering students can develop speed and torque controllers, in a fast and efficient manner. One of the most commonly used motor control strategies is Field Oriented Control; however it’s implementation requieres highly-intensive math processing and a fast processor with robust hardware resources. Several related works have been published, but they are hard to replicate and use due to the aforementioned problems. In this article, the author presents a torque and speed controller for industrial servomotors by means of Direct Torque Control which is known for its speed and ease of implementation compared to Field Oriented Control. In addition, the MicroPython programming language is used on the new and novel ESP32 microcontroller, which allows greater design simplicity. Results were validated using simulations and a physical implementation, thus achieving adequate motor funcionality. This work will provide students and researchers interested in industrial motor control, a fast and effective implementation tool.

Real-Time Implementation of a Neural Integrator Backstepping Control via Recurrent Wavelet First Order Neural Network

Wavelets are designed to have compact support in both time and frequency, giving them the ability to represent a signal in the two-dimensional time–frequency plane. The Gaussian, the Mexican hat, and the Morlet wavelets are crude wavelets that can be used only in continuous decomposition. The Morlet wavelet is complex-valued and suitable for feature extraction using continuous wavelet transform. Continuous wavelets are favoured when a high temporal resolution is required at all scales. In this paper, considering the properties from the Morlet wavelet and based on the structure of a recurrent high-order neural network model, a novel wavelet neural network structure, here called recurrent wavelet first-order neural network, is proposed in order to achieve a better identification of the behavior of dynamic systems. The effectiveness of our proposal is explored through the design of a centralized neural integrator backstepping control scheme for a two degree-of-freedom robot manipulator evolving in the vertical plane. The performance of the overall neural identification and control scheme is verified through numerical simulation using the mathematical model for a benchmark prototype. Moreover, real-time results validate the effectiveness of our proposal when using a robotic arm, of our own design, powered by industrial servomotors.

Neural Block Control via Integrator Backstepping for a Robotic Arm in Real-Time

This paper presents an online neural identification and control scheme in continuous-time for trajectory tracking of a robotic arm evolving in the vertical plane. A recurrent high-order neural network (RHONN) structure in a block strict-feedback form is proposed to identify online in a series-parallel configuration, using the filtered error learning law, the dynamics of the plant. Based on the RHONN identifier structure, a stabilizing controller is derived via integrator backstepping procedure. The performance of the neural control scheme proposed is tested on a two degrees of freedom robotic arm, of our own design and unknown parameters, powered by industrial servomotors.

Real-Time Decentralized Neural Control via Backstepping for a Robotic Arm Powered by Industrial Servomotors

This paper presents a continuous-time decentralized neural control scheme for trajectory tracking of a two degrees of freedom direct drive vertical robotic arm. A decentralized recurrent high-order neural network (RHONN) structure is proposed to identify online, in a series-parallel configuration and using the filtered error learning law, the dynamics of the plant. Based on the RHONN subsystems, a local neural controller is derived via backstepping approach. The effectiveness of the decentralized neural controller is validated on a robotic arm platform, of our own design and unknown parameters, which uses industrial servomotors to drive the joints.

Position Sensorless Control of PM Synchronous Motors Based on Zero-Sequence Carrier Injection

A position sensorless control method for PM synchronous motors is proposed in this paper. It relies on the magnetic saliencies to estimate the position of the rotor. In usual sensorless methods, a signal is injected in the <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$\alpha\beta$</tex></formula> or <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$dq$</tex> </formula> components. In the proposed method, the signal is injected in the zero-sequence component. The high-frequency inherent zero-sequence component produced by a space-vector pulsewidth modulator (PWM) is used. In this way, no modification is required in the PWM, even at zero voltage, and the injected signal does not interact with the current controller. The response to the injected signal is obtained by a simple current derivative sensor. With this method, the position can be evaluated with high dynamics and with a high signal-to-noise ratio. The performance of the proposed method is evaluated with an experimental setup, using standard industrial servomotors with surface-mounted magnets.

Steering Force Feedback for Human–Machine-Interface Automotive Experiments

Driving-simulator fidelity is usually defined by the quality of its visual and motion cueing system. However, the quality of its haptic cues is also very important and is determined by both hardware and control properties. Most experiments with haptic steering systems employ commercially available systems and do not address the system's fidelity. The goal of this paper is to offer guidelines for the development of hardware, performance evaluation, and system control in order to engineer realistic haptic cues on the steering wheel. A relatively low-cost solution for hardware is deployed, consisting of a velocity-controlled three-phase brushless servomotor, of which its high-bandwidth control allows for a realistic representation of forces. A method is presented to overcome electromagnetic interference produced by the industrial servomotor and the controller through careful amplification and filtering. To test the system, different inertia-spring-damper systems were simulated and evaluated in time and frequency domain. In conclusion, the designed system allowed reproduction of a large range of steering-wheel dynamics and forces. As a result, the developed system constitutes an efficient haptic device for human-machine-interface automotive experiments.

Automated sizing of permanent magnet synchronous machines with respect to electromagnetic and thermal aspects

PurposeThe purpose of this paper is to consider thermal analysis as part of an automated sizing and design process. The temperature estimation at characteristic points of the machine, and in particular in permanent magnets, is essential to accurately simulate the electromagnetic behavior and avoid irreversible demagnetization.Design/methodology/approachIn this paper, an electromagnetic dimensioning model, parameterized by finite element analysis, is coupled to a thermal lumped‐parameter model to constitute a fast and efficient design tool for electrical machines.FindingsA parameterized and hybrid FE‐analytical electromagnetic model, which combines analytical and numerical advantages, to archive a fast and accurate electromagnetic simulation results is combined with a thermal lumped‐parameter model for water‐cooled and passive air‐cooled surface mounted permanent magnet synchronous machines (PMSM).Practical implicationsSizing, electromagnetic and thermal modeling aspects are integrated into an automated design process. The whole design process is demonstrated on two standard industrial servo motors for passive and active water cooling and afterwards compared with available measurements.Originality/valueThe proposed method allows considering thermal aspects during the iterative automated electromagnetic design process of PMSM.

Adaptive-backstepping-based design of a nonlinear position controller for an IPMSM servo drive

This paper presents the design of a novel nonlinear position controller for an interior permanent-magnet synchronous motor (IPMSM) servo drive. The motor model equations provide the basis for the proposed controller, which is designed with the adaptive backstepping technique. Various system uncertainties, particularly mechanical-parameter uncertainties, are incorporated in the design of the controller. Using Lyapunov's stability theory, it is verified that the control variables are asymptotically stable. The complete drive system is then simulated with MATLAB/Simulink software. Performance of the proposed adaptive-backstepping-based nonlinear position controller (ABNPC) is investigated under different dynamic operating conditions such as step changes in command positions, step changes in load, and parameter variations. The results indicate that the proposed ABNPC-based IPMSM drive could be a candidate for real-time industrial servo motor drive applications.