Industrial Motion Control Research Articles

Automatic control strategy of electronic and electrical engineering based on FPGA

Field Programmable Gate Array (FPGA) have demonstrated significant potential in the field of automation control due to their flexibility, programmability, and high performance. This study designs an FPGA-based automation control strategy for motor control systems, encompassing four core modules: signal acquisition, signal processing, control algorithm, and output drive. The signal acquisition module employs the AD9280 high-speed, high-precision ADC chip to achieve rapid and accurate signal acquisition. The signal processing module utilizes digital filtering and FFT analysis within the FPGA to extract key information such as motor speed. The control algorithm module adopts an adaptive fuzzy control strategy that fine-tunes control rules in real-time to ensure precise control. The output drive module generates PWM signals via the FPGA to drive the motor, guaranteeing efficient and stable operation. Experimental results indicate that the FPGA-based control strategy significantly outperforms traditional methods in terms of response speed and stability, capable of meeting the high-performance requirements of modern industrial motor control systems. This research provides new technical insights and practical references for the field of automation control in electrical and electronic engineering.

Design and Development of an RTC Based Relay Board for Precision Control of Industrial Motors

An Arduino-based time-regulated electrical apparatus control mechanism undertakes the responsibility of activating and deactivating electric equipment as per a pre-set timetable. This exploration introduces an option to manual switching by elevating technology in a manner that is more secure and more user-efficient. It showcases an integrated clock that updates in real-time, turning the associated device on or off when real-time aligns with the scheduled time. The input control panel enables users to alter the switching schedule at their convenience, while the numeric display illustrates the current time. Key Word: Arduino, Liquid Crystal Display (LCD), Temporal clock, Relay unit, control inputs.

Incremental Stability of Discrete-Time First-Order Projection Elements

In this paper, we present and analyze a class of discrete-time and sampled-data controllers named first-order projection elements (FOPEs). FOPEs form a class of hybrid controllers that have an underlying linear base dynamics, which are combined with a projection operator that ensures that the input-output (I/O) pair is contained in a well-designed sector. The I/O sector-constraint enables performance benefits in various application domains including motion control of high-precision machines. After the introduction of FOPEs, we focus on incremental stability analysis of these hybrid controllers. We show that the properties of the projection operator ensure incremental stability of the open-loop FOPE dynamics in case of an underlying linear dynamics that is exponentially stable. In this case, we compute tight bounds on the incremental gain. Under an appropriate small-gain condition, we show incremental input-to-state stability of the sampled-data interconnection of a FOPE with a continuous-time linear time-invariant plant. For the case of projected integrator dynamics, we provide a counterexample showing that incremental stability can be compromised. We provide additional, necessary and sufficient conditions under which FOPEs with integrator dynamics are incrementally asymptotically stable. Numerical simulations provide a practical example of the established incremental properties for the trajectories of a dynamical system coming from an industrial motion control application.

Quadrature Sinusoidal Signals Correction of Magnetic Encoders via Radial Basis Function Neural Network and Adaptive Loop Shaping

Magnetic encoders are widely used in industrial motion control, due to their low-cost, simple structures and low environmental requirements. However, the obtained quadrature sinusoidal signals suffer from various disturbances, which affects the accuracy of the magnetic encoders. The current methods which combine the neural network with phase-locked loop (PLL) typically require the knowledge of harmonic orders in advance and use a proportional-integral controller as loop filter of the PLL. In this paper, we propose a new method, in which a radial basis function neural network (RBFNN)-based PLL is combined with adaptive loop shaping. In this method, with the incorporation of RBFNN into PLL, the disturbances could be readily eliminated, thus avoiding additional parameter identification. Furthermore, the adaptive loop shaping served to redesign the PLL's loop filter, aiming to strengthen the high-frequency noise attenuation capability. The method has been validated both theoretically and experimentally, confirming that it is an effective method to improve the accuracy of the magnetic encoders.

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.

Sistem Monitoring Dan Kontrol Motor Listrik Industri Menggunakan Internet Of Things (IoT)

The electric motor plays an important role in an industry as a driver in a particular system, for example, rotating a pump impeller, fan or blower, moving a compressor, and lifting materials. The electric motor is sometimes called the "work horse" of industry. It is estimated that motors use about 70% of the total electrical energy in the industry. In making industrial motor monitoring and control systems using IoT with the blynk application, it works in showing the parameters of voltage, current, temperature, and RPM. The module consists of an electric motor, a DHT11 sensor, a PZEM004T sensor, an RPM sensor, and an ESP 8266 microcontroller. In the research conducted, the system made is capable of monitoring and controlling many modules. So that the overall monitoring and control system of electric motors in the company can be integrated into a system. In testing the voltage sensor with a measuring instrument there is an error value of 0.04%, while the current sensor has an error of 2.5%, followed by temperature testing there is an error of 1.8%. the RPM sensor parameter has a value of 1.17%. Remote manual control can be controlled using a smartphone with the blynk application so that the operator can immediately turn off the motor remotely if there is a problem or damage to the electric motor.

CLB-Based Development of BiSS-C Interface Master for Motor Encoders

Encoder interfaces should be operated in real time with high precision and fast processing for industrial motor control systems. The continuous bidirectional serial synchronous (BiSS-C) interface is an open-source serial communication protocol designed for motor encoders and is suitable for industrial purposes because of its fast serial communication speed. In this study, we propose a method for developing a BiSS-C interface master for a motor encoder slave, using only the configurable logic block (CLB) peripheral integrated into TI microcontroller units. By analyzing the detailed operation protocol of the BiSS-C interface, we create the truth and state tables for logic circuits and finite state machines, which are required for the BiSS-C interface master. Then, by programming the CLB based on the created truth and state tables, we implement the master clock, serial peripheral interface (SPI) clock, and operational process for the master. This approach is cost-efficient because additional hardware components, such as a field-programmable gate array or a complex programmable logic device, are not required for the master implementations. The developed method can be immediately applied to developing the masters for other BiSS-C encoders with different specifications, which is certainly necessary for a motor drive development and test. By building an AC motor control system with the developed master and performing various experiments, we verify the performance and practical usefulness of the developed BiSS-C interface master. The maximum master clock frequency without any CRC errors is achieved by 6.25 MHz, which can cope with more than 20 kHz motor control cycle frequency. The usefulness is demonstrated by showing the motor speed and position control performance that are acceptable in real applications.

MODELLING AND SIMULATION OF THREE-PHASE FOUR-SWITCH VOLTAGE SOURCE INVERTER WITH SPACE VECTOR MODULATION

The three-phase six-switches voltage source inverter is usually used for industrial motor control and renewable energy systems. However, in order to decrease to size and cost of the drive systems, the three-phase four-switch voltage source inverter has been applied to low-cost motor control and renewable energy system. The fundamental concepts and principles of the three-phase four-switch voltage source inverter are discussed. The mathematical model and space vector modulation of the three-phase four-switch voltage source inverter are proposed. The work is demonstrated by simulation results.

Design of Smart Solar based Industrial Motor Monitoring and Control using Internet of Things

Design of Smart Solar based Industrial Motor Monitoring and Control using Internet of Things

Adaptive Control of a Mechatronic System Using Constrained Residual Reinforcement Learning

In this article, we propose a simple, practical, and intuitive approach to improve the performance of a conventional controller in uncertain environments using deep reinforcement learning while maintaining safe operation. Our approach is motivated by the observation that conventional controllers in industrial motion control value robustness over adaptivity to deal with different operating conditions and are suboptimal as a consequence. Reinforcement learning, on the other hand, can optimize a control signal directly from input–output data and thus adapts to operational conditions but lacks safety guarantees, impeding its use in industrial environments. To realize adaptive control using reinforcement learning in such conditions, we follow a residual learning methodology, where a reinforcement learning algorithm learns corrective adaptations to a base controller’s output to increase optimality. We investigate how constraining the residual agent’s actions enables to leverage the base controller’s robustness to guarantee safe operation. We detail the algorithmic design and propose to constrain the residual actions relative to the base controller to increase the method’s robustness. Building on Lyapunov stability theory, we prove stability for a broad class of mechatronic closed-loop systems. We validate our method experimentally on a slider crank setup and investigate how the constraints affect the safety during learning and optimality after convergence.

Speed Estimation of an Asynchronous Motor with Feed Forward Neural Network

Abstract: AC asynchronous motors are the most frequent motors used in industrial motion control systems as well as in mainpowered domestic appliances. AC asynchronous motors provide several advantages, including a simple and durable construction, low cost, low maintenance, and direct connection to an AC power source. On the market, there are many different types of AC asynchronous motors. Diverse motors are suitable for various applications. Like other motors, an AC asynchronous motor contains a stator that is fixed on the outside and a rotor that spins within, separated by a precisely designed air gap. Almost all electric motors use magnetic field rotation to spin their rotors. Asynchronous motors are the most commonly utilized electromechanical machinery in industrial applications. There have been several research on their control, as well as a variety of approaches for achieving high-performance speed drivers. The properties of asynchronous motors alter with time and under different operating situations. Even though much research has gone into developing artificial neural network techniques to estimate the speed of an asynchronous motor and some of the parameters such as flux and torque, there hasn't been much work done on asynchronous motor speed estimation using artificial neural networks. The main purpose of this paper is to build a speed estimator for an asynchronous motor using a feed-forward artificial neural network. A mathematical model for the asynchronous motor is developed and implemented in Matlab. A speed estimator is then developed using a feed-forward neural network and coupled to the asynchronous motor to estimate its speed. After that, simulations are done to see how well the proposed speed estimator performed. Keywords: Space Vector Modulation PWM (SVPWM), Artificial Neural Networks (ANN), magnet Permanent magnet Synchronous Motor (PMSM)

Space robot motion path planning based on fuzzy control algorithm

Path planning technology is one of the core technologies of intelligent space robot. Combining image recognition technology and artificial intelligence learning algorithm for robot path planning in unknown space environment has become one of the hot research issues. The purpose of this paper is to propose a spatial robot path planning method based on improved fuzzy control, aiming at the shortcomings of path planning in the current industrial space robot motion control process, and based on fuzzy control algorithm. This paper proposes a fuzzy obstacle avoidance method with speed feedback based on the original advantages of the fuzzy algorithm, which improves the obstacle avoidance performance of space robot under continuous obstacles. At the same time, we integrated the improved fuzzy obstacle avoidance strategy into the behavior-based control technology, making the avoidance become an independent behavioral unit. Divide the path planning into a series of relatively independent behaviors such as fuzzy obstacle avoidance, cruise, trend target, and deadlock by the behavior-based method. According to the interaction information between the space robot and the environment, each behavior acquires the dominance of the robot through the competition mechanism, making the robot complete the specific behavior at a certain moment, and finally realize the path planning. Furthermore, to improve the overall fault tolerance of the space, robot we introduced an elegant downgrade strategy, so that the robot can successfully complete the established task in the case of control command deterioration or failure of important information, avoiding the overall performance deterioration effectively. Therefore, through the simulation experiment of the virtual environment platform, MobotSim concluded that the improved algorithm has high efficiency, high security, and the planned path is more in line with the actual situation, and the method proposed in this paper can make the space robot successfully reach the target position and optimize the spatial path, it also has good robustness and effectiveness.

Tracking Control of Single-Axis Feed Drives Based on ADRC and Feedback Linearisation

The accuracy of manufacturing highly characterises the performance of industrial motion control. However, detrimental effects such as nonlinear coupling, model uncertainty and unknown external disturbances severely affect trajectory tracking performance. In this paper, we proposed an ADRC and feedback linearisation-based control algorithm for the high-precision trajectory tracking of feed drives. The controller was rigorously designed to ensure the convergence of observer states and tracking error. The applicability of the proposed approach was successfully demonstrated via high-fidelity simulation, and the numerical results based on different tracking methods were compared.

Implementasi Penggunaan Modul Praktek PLC CP1E Pada Pelajaran Produktif Kompetensi Pengontrolan Motor Listrik Pada Program Keahlian Teknik Ketenagalistrikan SMK Negeri 3 Sorong Provinsi Papua Barat

PLC control is basically a computer designed to replace a relay-based system. SMK Negeri 3 Sorong as one of the Vocational High Schools in Sorong-West Papua has an Electricity Engineering Expertise Program that studies PLC mastery competencies, but from observations made by researchers at SMK Negeri 3 Sorong it turns out that it does not have adequate practice modules in the subject of applying PLC to control of industrial electric motors and there are also difficulties for teachers in these schools in providing learning competency in electric motor control techniques, especially in terms of application or practice. The implementation of the module that will be designed and applied is a learning medium that will help the process of practicing skills in electric motor control engineering competencies automatically using the PLC Omron CP1E module. This module is designed to pay attention to several important things as follows: (1). Practice module in accordance with existing competency standards, (2). Easy to use, and (3). Helps the level of understanding of teachers and students in applying it. This practical module is also used to study the working principle parts of the up / down motor control system with the addition of a simulation module of the lift motor work system using a limit switch that detects the presence of the lift box. At the PLC output, a motor power window and lift indicator are used which indicate the lift box is automatically running.

Development and Acceptability of an Industrial Motor Control System Trainer

Development and Acceptability of an Industrial Motor Control System Trainer

Optimum operation of low voltage variable‐frequency drives to improve the performance of heating, ventilation, and air conditioning chiller system

A tremendous increase in the industrial and commercial applications of low voltage variable frequency drives (VFD) has been observed in the last decade. VFD are mainly used for energy saving and reliable speed control of industrial motors in an electrical system. However, power quality issues are becoming more apparent due to the installation of VFD. In this paper, a nonintrusive technique has been employed to determine the optimum operation of VFD system for improving the performance of heating, ventilation, and air conditioning centrifugal chiller system. The effect of load and speed ratios of VFD systems on total harmonic distortion (THD), power factor, distortion loss ratio, temperature, and efficiency has been investigated. The measurement of these parameters has been carried out by performing a series of experiments under variable operating conditions. The binomial relations have been developed between the various performance parameters and the operating conditions. Based on experimental results, optimum operating conditions have been proposed and implemented for the VFD system. Moreover, the results have been compared with the existing operating conditions and indicate a considerable improvement in THD, power factor, distortion loss ratio, efficiency, and the annual cost of energy consumed.

Microcontroller-Based Direct Torque Control Servodrive

Robot technology has become an integral part of the automotive industry in several tasks such as material handling, welding, painting, and part assembly. Therefore, the knowledge and skills to control the electric motors in these manipulators are essential for undergraduate electrical engineering students. Currently, the digital signal processor (DSP) is the core chip in industrial motor-control drives; however, the implementation of DSP control algorithms can be quite challenging for an experienced programmer, even more so for the novice. Considerable research has been done on this topic, although authors usually focus on DSP-based motor drives using popular control techniques such as field-oriented control (FOC). Although highly efficient, this approach is usually reserved for postgraduate education due to its complex structure and functionality. In this paper, the authors present a modular servodrive design on a low-cost, general-purpose microcontroller using the direct torque control (DTC) method, an alternative known for greater simplicity and torque response, compared with FOC. The system design was based on Micropython language allowing the software structure to be more manageable and the code to be more understandable. This design will be useful to undergraduates and researchers with interests in motor control design.

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.

An Optimization Algorithm for Direct Torque Control of Industrial Robot Servo Motors

An Optimization Algorithm for Direct Torque Control of Industrial Robot Servo Motors

Automated design and optimization of industrial motion control machines: verification and a case-study

Motion control is a form of automation which enables the position- or velocity-control of a machine using an actuator such as an electric motor. The selection of suitable components and actuators for complex mechanical structures requires significant engineering expertise and intelligence. In this work, a design expert system is presented to support the motion control system design process through optimization of mechanical components and accurate selection of an actuator-transmission combination for the system. Verification of the developed system is conducted on an industrial conveyor belt. A case study involving a heavy-weight industrial hoister driven by a DC motor is presented, where the developed automated system is found to consistently outpace human performance on the same design tasks.