• Smart Structures and Systems
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• v.29 no.4
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• pp.617-624
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• 2022

A new intelligent adaptive control scheme was proposed that combines the control based on interference observer and fuzzy adaptive s-curve for flight path tracking control of unmanned aerial vehicle (UAV). The most important contribution is that the control configurations don't need to know the uncertainty limit of the vehicle and the influence of interference is removed. The proposed control law is an integration of fuzzy control estimator and adaptive proportional integral (PI) compensator with input. The rated feedback drive specifies the desired dynamic properties of the closed control loop based on the known properties of the preferred acceleration vector. At the same time, the adaptive PI control compensate for the unknown of perturbation. Additional terms such as s-surface control can ensure rapid convergence due to the non-linear representation on the surface and also improve the stability. In addition, the observer improves the robustness of the adaptive fuzzy system. It has been proven that the stability of the regulatory system can be ensured according to linear matrix equality based Lyapunov's theory. In summary, the numerical simulation results show the efficiency and the feasibility by the use of the robust control methodology.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.1
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• pp.45-55
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• 1998

In this paper, a robust path tracker and depth controller of Autonomous Underwater Vehicle based on sliding mode control is presented. We have also designed augmented equivalent control inputs by analyzing the sliding mode with the reaching mode. This can enhance the reaching rate, and improve chattering problems, that is, noise caused by the control plane actuator of the vehicle, which is one of the problems that occur when sliding mode control is used. Also to resolve the steady state error generated in the path tracker under current effect, a modified sliding plane is constructed. Also a redesigned sliding plane and control input using transformation matrix is proposed to do easy design of MIMO depth controller. For state variables that cannot be measured directly, reduced order sliding mode control is used to design an observer. The performance of designed path tracker and depth controller is investigated by computer simulation. The results show that the proposed control system has robust performance to parameter variation, modelling error and disturbance.

• Journal of Drive and Control
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• v.14 no.2
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• pp.16-22
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• 2017

This paper presents the algorithm of an adaptive model-free-control-based steering control for multi-axle all-terrain cranes for which the recursive least squares with forgetting are applied. To optimally control the actual system in the real world, the linear or nonlinear mathematical model of the system should be given for the determination of the optimal control inputs; however, it is difficult to derive the mathematical model due to the actual system's complexity and nonlinearity. To address this problem, the proposed adaptive model-free controller is used to control the steering angle of a multi-axle crane. The proposed model-free control algorithm uses only the input and output signals of the system to determine the optimal inputs. The recursive least-squares algorithm identifies first-order systems. The uncertainty between the identified system and the actual system was estimated based on the disturbance observer. The proposed control algorithm was used for the steering control of a multi-axle crane, where only the steering input and the desired yaw rate were employed, to track the reference path. The controller and performance evaluations were constructed and conducted in the Matlab/Simulink environment. The evaluation results show that the proposed adaptive model-free-control-based steering-control algorithm produces a sound path-tracking performance.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.4
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• pp.422-427
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• 2014

This study provides a method to detect blood vessels shape using image processing techniques with the help of fluoroscopy equipments, providing high precision information about vessels' location and shape of inner path. It will assist for checking and monitoring the position of operating tools during vascular interventional treatment. The blood vessels shapes are gathered with X-ray images when a fluorescent medications are injected into patient's vessel and those images are processed for getting the boundaries of vessels. Then these data are merged with real-time CT-images. These image processing systems and procedures recognize the catheter, though continued computing algorithms are very useful for observer part on the automatic control system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.7
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• pp.599-605
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• 2017

For an unmanned vehicle to be driven on the off-road terrain, it is necessary to consider the vehicle's stability. This paper suggests a path tracking controller for simulation of real-time vehicle stability analysis. The path tracking controller uses the preview distance to track the given trajectory. The disturbance moment is estimated using the yaw moment observer, and this information is used for compensation in the yaw moment control. On a curved path, the vehicle's desired velocity is determined from the curvature of the path. Because the vehicle is equipped with six independent motor driven wheels, the driving torques are distributed on all the wheels. The effectiveness of the path tracking controller is verified using ADAMS/MATLAB co-simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1249-1253
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• 2004

A robust input modification approach to the control of flexible joint robot is presented. In our previous study, we developed an observer based state feedback control for the suppression of residual vibration of a robot. The control was very effective in suppressing the inherent vibration of a flexible joint robot. However it did not meet high performance requirements under high speed motion and model uncertainties. As a solution of the problem, we present an input modification method with robustness against parametric uncertainties. The main idea of the proposed input modification method is to generate a modified reference position command for fast and accurate motion of the robot. Using this proposed method we can reduce the servo delay and settling time by about 60% and substantially improve the path accuracy.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.214-230
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• 2014

This paper presents a high performance sensor less control four motorized wheels for electric vehicle. Firstly, we applied a sensor less master-slave DTC based control to both the two in wheel motors by using sliding mode observer for its quick response and its high reliability in electric vehicle application. Secondly, to overcome the possible loss of adherence of one of the four wheels which is likely to destabilize the vehicle a solution is proposed in this paper. Thirdly, a Fuzzy logic anti-skid control structure well adapted to the non-linear system is used to overcome the main problem of power train system in the wheel road adhesion characteristic. Various Simulation results have been include in this paper to show that the proposed control strategy can prevent vehicle sliding and show good vehicle stability on a curved path.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.3
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• pp.228-235
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• 2010

This paper deals with an autonomous flight controller design problem for a tilt-rotor aircraft in rotary-wing mode. The inner-loop algorithm is designed using the output-based approximate feedback linearization. The model error originated from the feedback linearization is cancelled within allowable tolerance by using single-hidden-layer neural network. According to Lyapunov direct stability theory, the adaptive update law is derived to run the neural network on-line, which is based on the linear observer dynamics. Moreover, the outer-loop algorithm is designed to track the trajectory generated from way-point guidance. Especially, heading and flight-path angle line-of-sight guidance are applied to the outer-loop to improve accuracy of the landing tracking performance. The 6-DOF nonlinear simulation shows that the overall performance of the flight control algorithm is satisfactory even though the collective input response shows instantaneous actuator saturation for a short time due to the lack of the neural network and the saturation protection logic in that loop.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.6
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• pp.549-559
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• 2015

In this paper, an efficient dynamic reactive motion planning method for an autonomous vehicle in a dynamic environment is proposed. The purpose of the proposed method is to improve the robustness of autonomous robot motion planning capabilities within dynamic, uncertain environments by integrating a virtual plane-based reactive motion planning technique with a sensor fusion-based obstacle detection approach. The dynamic reactive motion planning method assumes a local observer in the virtual plane, which allows the effective transformation of complex dynamic planning problems into simple stationary ones proving the speed and orientation information between the robot and obstacles. In addition, the sensor fusion-based obstacle detection technique allows the pose estimation of moving obstacles using a Kinect sensor and sonar sensors, thus improving the accuracy and robustness of the reactive motion planning approach. The performance of the proposed method was demonstrated through not only simulation studies but also field experiments using multiple moving obstacles in hostile dynamic environments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.10
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• pp.1915-1923
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• 2011

For automated guidance control of a magnetically guided-all wheel steered vehicle, it is necessary to have information about position and orientation of the vehicle, and deviations from the reference path in real time. The magnet reference system considered here consists of three magnetic sensors mounted on the vehicle and magnetic markers, which are non-equidistantly buried in the road. This paper presents an observer to estimate such position and orientation at the center of gravity of the vehicle. This algorithm is based on the simple kinematic model of vehicle and uses the data of wheel velocity, steering angle, and the discrete measurements of marker positions. Since this algorithm requires the exact values of initial states, we have also proposed an algorithm of determining the initial position and orientation from the 16 successive magnet pole data, which are given by the magnetic measurement system(MMS). The proposed algorithm is capable of continuing to estimate for the case that the magnetic sensor fail to measure up to three successive magnets. It is shown through experimental data that the proposed algorithm works well within permissible error range.