• Journal of Drive and Control
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• v.14 no.4
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• pp.37-44
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• 2017

This paper introduces a control algorithm for trajectory control of an electro-hydrostatic rotary actuator. A key feature of this paper is that an adaptive PID based on sliding mode is used to control the nonlinearity and uncertainty factor of single input/output system. Accurate knowledge of rotary actuator angle can result in high-performance and efficiency of electro hydraulic system. First, the position control is formulated using the adaptive PID with sliding mode technique and uncertainties in the hydraulic system. Second, the controller can update the PID gains on-line based on error caused by external disturbance and uncertain factors in the system. Finally, three experimental cases were studied to evaluate the proposed control method.

• Journal of Drive and Control
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• v.15 no.4
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• pp.74-80
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• 2018

A damper is a hydraulic device designed to absorb or eliminate shock impulses which is acting on the sprung mass of vehicle. It converting the kinetic energy of the shock into another form of energy, typically heat. In a vehicle, a damper reduce vibration of car, leading to improved ride comfort and running stability. Therefore, a damper is one of the most important components in a vehicle suspension system. Conventionally, the design process of vehicle suspensions has been based on trial and error approaches, where designers iteratively change the values of the design variables and reanalyze the system until acceptable design criteria are achieved. Therefore, the ability to tune a damper properly without trial and error is of great interest in suspension system design to reduce time and effort. For this reason, a many previous researches have been done on modeling and simulation of the damper. In this paper, we have conducted optimal design process to find optimal design parameters of damping force which minimize a acceleration of sprung mass for a given suspension system using genetic algorithm.

• Journal of IKEEE
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• v.23 no.3
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• pp.1068-1076
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• 2019

Most of the electronics we use today have built-in microcontrollers, which are called embedded systems. In such a small environment, responsiveness is very important for the microcontroller. In this paper, the basic input/output control, timer/counter interrupt operation principle, and understanding of the microcontroller are described. Program logic is proposed to improve throughput and latency by controlling characteristics of service routine and program execution order. The hardware simulations in this paper were verified using ATmega128 and PIC16F877A from Atmel and Microchip.

• Journal of Drive and Control
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• v.18 no.2
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• pp.9-19
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• 2021

The spool displacement signal of a directional control valve, including the servo valve, can be considered as the standard signal to measure dynamic characteristics. When the spool displacement signal is not available, the velocity signal of a metering cylinder piston can be used. In this study, the frequency response characteristics of the metering cylinder are investigated for the spool displacement input. The transfer functions of the servo valve-metering system are derived taking into consideration the oil inertia effect in the transmission lines. The theoretical results of the transfer functions are verified through computer simulations and experiments. The oil inertia effect in the transmission lines was found to have a very significant effect on the bandwidth frequency of the servo valve-metering cylinder system. In order to more precisely measure the dynamic characteristics of a servo valve, the metering cylinder should be set up to minimize the oil inertia effect by increasing the inner diameters of the transmission lines or shortening their lengths.

• Journal of Drive and Control
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• v.18 no.1
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• pp.24-30
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• 2021

There is an increasing interest in condition-based maintenance for the prevention of economic loss due to failure. Moreover, immense research is being carried out in related technologies in the field of construction machinery. In particular, data-based failure diagnosis methods that employ AI (machine & deep learning) algorithms are in the spotlight. In this study, we have focused on the failure diagnosis and mode classification of reduction gear of excavator's travel device by using the AI algorithm. In addition, a remote monitoring system has been developed that can monitor the status of the reduction gear by using the developed diagnosis algorithm. The failure diagnosis algorithm was performed in the process of data acquisition of normal and abnormal under various operating conditions, data processing and analysis by the wavelet transformation, and learning. The developed algorithm was verified based on three-evaluation conditions. Finally, we have built a system that can check the status of the reduction gear of travel devices on the web using the Edge platform, which is embedded with the failure diagnosis algorithm and cloud.

• Journal of Drive and Control
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• v.17 no.4
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• pp.103-112
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• 2020

Field robots are used in various fields, such as agriculture, forestry, manufacturing, and construction; their use has recently expanded to include submarine areas. Field robots can aid in various tasks, such as soil transport, ground clearance, and dismantling of buildings. As field robots are used in a variety of different areas, the difficulty of the work is also quite varied. Increased difficulty is associated with an increased risk of accidents involving the field robot. In order to reduce the accident rate of field robot workers, the need for digitalization and automation of field robots is becoming more of an issue. To this end, it is necessary to study a system that enables workers to do their work without directly contacting a field robot. Therefore, in this paper, we introduce a control system for wireless remote control of a small field robot. The field robot can be wirelessly controlled by a worker in a remote location if the worker cannot be present at the work site. The implemented remote system is tested according to the type of work, and the operating characteristics of the remote system are assessed.

• Journal of Drive and Control
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• v.18 no.4
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• pp.9-18
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• 2021

This study proposes a method for creating learning datasets to recognize obstacles using deep learning algorithms in automated construction machinery or an autonomous vehicle. Recently, many researchers and engineers have developed various recognition algorithms based on deep learning following an increase in computing power. In particular, the image classification technology and image segmentation technology represent deep learning recognition algorithms. They are used to identify obstacles that interfere with the driving situation of an autonomous vehicle. Therefore, various organizations and companies have started distributing open datasets, but there is a remote possibility that they will perfectly match the user's desired environment. In this study, we created an interface of the virtual simulator such that users can easily create their desired training dataset. In addition, the customized dataset was further advanced by using the RDBMS system, and the recognition rate was improved.

• Journal of Drive and Control
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• v.19 no.4
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• pp.62-69
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• 2022

Construction machinery is exposed to accidents such as collisions, narrowness, and overturns during operation. In particular, mobile crane is operated only with the driver's vision and limited information of the assistant worker. Thus, there is a high risk of an accident. Recently, some collision avoidance device using sensors such as cameras and LiDAR have been applied. However, they are still insufficient to prevent collisions in the omnidirectional 3D space. In this study, a rotating LiDAR device was developed and applied to a 250-ton crane to obtain a full-space point cloud. An algorithm that could provide distance information and safety status to the driver was developed. Also, deep-learning segmentation algorithm was used to classify human-worker. The developed device could recognize obstacles within 100m of a 360-degree range. In the experiment, a safety distance was calculated with an error of 10.3cm at 30m to give the operator an accurate distance and collision alarm.

• Journal of Drive and Control
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• v.19 no.4
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• pp.97-103
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• 2022

Low fertility rates and increased life expectancy further exacerbate the process of an aging society. This is also reflected in the gradual increase in the proportion of vulnerable groups in the social population. The demand for improved mobility among vulnerable groups such as the elderly or the disabled has greatly driven the growth of the electric-assisted mobility device market. However, such mobile devices generally require a certain operating capability, which limits the range of vulnerable groups who can use the device and increases the cost of learning. Therefore, autonomous driving technology needs to be introduced to make mobility easier for a wider range of vulnerable groups to meet their needs of work and leisure in different environments. This study uses mini PC Odyssey, Velodyne Lidar VLP-16, electronic device and Linux-based ROS program to realize the functions of working environment recognition, simultaneous localization, map generation and navigation of electric powered mobile devices for vulnerable groups. This autonomous driving mobility device is expected to be of great help to the vulnerable who lack the immediate response in dangerous situations.

• Journal of Drive and Control
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• v.19 no.4
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• pp.29-35
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• 2022

In this paper, we developed a workload index for monitoring the durability test using operation information of an excavator. First, the acceleration and cylinder pressure were selected as load factors by analyzing operation data. Through load correlation analysis according to each load factor, Root Mean Square (RMS) and Work Load Range (WLR) were respectively derived as a load feature representing mechanical load. In addition, the workload index was used to quantify load features. For applying the workload index to monitoring, a real-time monitoring system consisting of sensors and embedded controller was installed on the excavator and the system was integrated with a remote monitoring environment using a wireless network. Results of load monitoring and analysis verified that the developed workload index was effective from the viewpoint of the relative comparison of the workload.