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정슬 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.2
Neural network control for robot manipulators is aimed to compensate for uncertainties in the robotdynamics. The location of a compensating point differentiates the control scheme into two categories, the feedbackerror learning (FEL) scheme and the reference compensation technique (RCT). The RCT scheme is relatively lessused although it has several structural advantages. In this paper, the global stability of the RCT scheme is analyzedon the basis of Lyapunov function. The analysis turns out that the stability depends upon the magnitude of thecontroller gains. Simulation studies of controlling the position of a two-link robot manipulator are conducted.
Guidance Control of a Wheeled Mobile Robot with Human Interaction Based on Force Control
정슬,이형직 제어·로봇·시스템학회 2010 International Journal of Control, Automation, and Vol.8 No.2
This paper presents a mobile robot carrier designed to carry a person using two modes: a mechanism with full support and another with partial support. The carrier is driven through guided control from an operator. Applied force is sensed by a force sensor mounted on the bottom of the handle. The measured force is filtered by the impedance function that generates the desired velocity to drive the motors. The inner loop PID controller is then required to follow the desired velocity, which is the reference input to the system. The impedance function is designed to make the driving condition comfortable for the driver by smoothing out abrupt starts and stops. Feasibility tests on the application of the impedance force control method to the carrier robot have been performed through experimental case studies aimed at evaluating the comfort level of prospective users: one is on a full support case when a user is riding on the carrier and another on a partial support case where the user is pushing the carrier.
Development of a Creative Robot School Program for Motivating Elementary School Students
정슬 한국공학교육학회 2011 공학교육연구 Vol.14 No.3
This article presents program development and analysis of a creative robot school for elementary school at the local university. The purpose of opening the creative robot school is to give motivation to children for having interests in science and engineering at their young ages. The creative robot school program is developed by using facilities of a local university to spread scientific knowledge to young children in their communities to draw their interests in science as well as an engineering field for future careers. Since the robot system is a popular subject to draw attention of children and has a relation with Mechatronics Engineering, a program related with robots is selected for educating children. College students are also involved in helping children to build robots within a given time. Experiences and self-evaluations from the previously held creative robot schools at Chungnam National University(CNU) are presented to share with.
정슬,T. C. Hsia 대한임베디드공학회 2011 대한임베디드공학회논문지 Vol.6 No.3
This paper presents an intelligent control approach for lateral position control of an autonomous four wheel steered snowplowing robotic vehicle. The vehicle is built for removing snow on the highway. Dynamics of the vehicle is derived and linearized for LQR control. Lateral position is controlled by the LQR method first, then the neural network control technique is introduced to improve tracking performances under the presence of load. The feasibility of using four wheel steering control is investigated by simulation studies of lateral position tracking of the Ford F-250 truck model. Performances of a LQR control method and a neural network control method under virtual snowplowing situation are compared.
카테시안 공간에서 시간 지연제어기의 구현에 대한 튜토리얼
정슬 제어·로봇·시스템학회 2021 제어·로봇·시스템학회 논문지 Vol.27 No.6
This paper presents a tutorial on the implementation of the time-delayed controller in the Cartesian space for robot manipulators. Although the Cartesian space position is actually controlled in the joint space through the inverse kinematics, the direct control of the Cartesian position is required for force control applications. For the implementation of Cartesian space controllers, there are several schemes due to the requirement of the transformation from the Cartesian space to the joint space. One is to use the acceleration relation between the joint space and the Cartesian space, which requires the inverse and the derivative of the Jacobian. Another is to use the transpose of the Jacobian. Accordingly, the time-delayed controller can be constructed in either the joint space or the Cartesian space for the Cartesian space control. Advantages of each implementation of the time-delayed controller for the Cartesian space are discussed. Extensive simulation studies for a robot manipulator to follow a circular trajectory are performed to explain the advantages of implementation of the time-delayed controller in the Cartesian space. .
정슬 제어·로봇·시스템학회 2018 International Journal of Control, Automation, and Vol.16 No.2
This article presents a neural network control technique to improve the tracking performance of a robot manipulator controlled by the sliding mode control method in a non-model-based framework. The sliding mode controller is a typical nonlinear controller that has been well developed in theory and used in many applications due to its simplicity and practicality. Selection of the gain of the nonlinear function plays an important role in performance as well as stability. When the sliding mode controller is used for the non model-based configuration in robot control, the nonlinear gain should be selected large enough to guarantee the stability. Since the appropriate selection of the gain value is essential and difficult in the sliding mode control framework, a neural network compensator is introduced at the trajectory level to help the fixed gain deal with the stability and performance more intelligently. Stability of the proposed control scheme is analyzed. Simulation studies of following the Cartesian trajectory for a three-link rotary robot manipulator are conducted to confirm the control improvement by the neural network.