• Proceedings of the KIEE Conference
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• 1995.07a
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• pp.234-236
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• 1995

A robust nonlinear speed control of a permanent magnet synchronous motor(PMSM) is presented. A perturbed dynamic model including the influence of parameter variations and speed measurement error on the nonlinear speed control of a PMSM is derived. Based on this model, a boundary layer integral sliding mode controller to improve the robustness and performance of the nonlinear speed control of a PMSM is proposed and compared with the conventional controller.

• The Journal of Korea Robotics Society
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• v.18 no.2
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• pp.155-163
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• 2023

Auto Guided Vehicle (AGV) equipped with mecanum wheels can move in all directions, unlike ordinary wheeled AGVs. In this paper, we propose a robust trejectory tracking control method for the mecanum wheeled AGVs in the presence of disturbances. It is constructed by combining impedance control with Integral Sliding Mode Control (ISMC), which shows robust performance against disturbances, and adding a disturbance observer (DOB) that estimates and removes disturbances. Simulation result using MATLAB/SIMULINK shows that the proposed control method has robust performance in tracking the reference trajectory under the circumstance with disturbance. The control performance is further improved when the disturbance observer is additionally used. In addition, the performance of the proposed control method was verified through experiment. It shows the result of tracking the set trajectory well.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.38 no.2
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• pp.1-11
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• 2001

In this paper, a chattering alleviation VSS controller for the sinusoidal type BLDC motor is designed. Dead Zone function is proposed to change the chattering occurring in the transient state from high frequency to low frequency and time varying gains arc applied for the control input to eliminate the steady state excessive chattering in the conventional ISM. The proposed Dead Zone function represents the sliding layer composed of two switching surfaces and if a state vector exists in this layer, the chattering don't occur. Simulation and experimental results confirm the useful effects of the above algorithm.

• International Journal of Ocean System Engineering
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• v.1 no.3
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• pp.120-135
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• 2011

This paper proposes a model based trajectory tracking control scheme for under-actuated underwater robotic vehicles. The difficulty in stabilizing a non-linear system using smooth static state feedback law means that the design of a feedback controller for an under-actuated system is somewhat challenging. A necessary condition for the asymptotic stability of an under-actuated vehicle about a single equilibrium is that its gravitational field has nonzero elements corresponding to non-actuated dynamics. To overcome this condition, we propose a continuous time-varying control law based on the direct estimation of vehicle dynamic variables such as inertia, damping and Coriolis & centripetal terms. This can work satisfactorily under commonly encountered uncertainties such as an ocean current and parameter variations. The proposed control law cancels the non-linearities in the vehicle dynamics by introducing non-linear elements in the input side. Knowledge of the bounds on uncertain terms is not required and it is conceptually simple and easy to implement. The controller parameter values are designed using the Taguchi robust design approach and the control law is verified analytically to be robust under uncertainties, including external disturbances and current. A comparison of the controller performance with that of a linear proportional-integral-derivative (PID) controller and sliding mode controller are also provided.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1271-1279
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• 2017

A highly accurate model-free controller is proposed for trajectory tracking control of robot manipulators. The proposed controller incorporates time-delay estimation (TDE) to estimate and cancel continuous nonlinearities of robot dynamics, and exploits fuzzy logic systems to suppress the effect of the TDE error, which is due to discontinuous nonlinearities such as friction. To this end, integral sliding mode is defined using desired error dynamics, and a Mamdani-type fuzzy inference system is constructed. As a result, the proposed controller achieves the desired error dynamics well. Implementation of the proposed controller is easy because the design of the controller is intuitive and straightforward, and calculations of the complex robot dynamics are not required. The tracking performance of the proposed controller is verified experimentally using a 3-degree of freedom PUMA-type robot manipulator.

• Ocean Systems Engineering
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• v.10 no.4
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• pp.373-397
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• 2020

Heave compensation is a vital part of various marine and offshore operations. It is used in various applications, including the transfer of cargo between two vessels in the open ocean, installation of topsides of an offshore structure, offshore drilling and for surveillance, reconnaissance and monitoring. These applications typically involve a load suspended from a hydraulically powered winch that is connected to a vessel that is undergoing dynamic motion in the ocean environment. The goal in these applications is to design a winch controller to keep the load at a regulated height by rejecting the net heave motion of the winch arising from ship motions at sea. In this study, we analyze and compare the performance of various control algorithms in stabilizing a suspended load while the vessel is subjected to changing sea conditions. The KCS container ship is chosen as the vessel undergoing dynamic motion in the ocean. The negative of the net heave motion at the winch is provided as a reference signal to track. Various control strategies like Proportional-Derivative (PD) Control, Model Predictive Control (MPC), Linear Quadratic Integral Control (LQI), and Sliding Mode Control (SMC) are implemented and tuned for effective heave compensation. The performance of the controllers is compared with respect to heave compensation, disturbance rejection and noise attenuation.

• Journal of Drive and Control
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• v.21 no.3
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• pp.28-35
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• 2024

This study compared performances of PID (Proportional Integral Derivative), SMC (Sliding Mode Control), and MPC (Model Predictive Control) strategies applied to a 2DOF (Degree Of Freedom) drone tracking robot. The developed 2DOF robot utilized a depth camera with an IMU (Inertial Measurement Unit), laser pointers, and servo motors to rapidly detect and track objects. Image processing was conducted using the YOLO deep learning model. Through this setup, controllers were attached to the robot to track random drone movements, comparing performances in terms of accuracy and energy consumption. This study revealed that while SMC demonstrated precise tracking without deviating from the path, both PID and MPC controllers showed deviations. Performance-wise, SMC is superior. However, considering economic aspects, PID is more advantageous due to its lower power consumption and relatively minor tracking errors.