• 제어로봇시스템학회논문지
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• 제7권12호
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• pp.967-972
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• 2001

In this paper, an adaptive robust nonlinear predictive controller is developed for the continuous time nonlinear systems whose control objective is composed of the system output and its desired value. The basic control law is derived from the continuous time prediction model and its feedback dynamcis shows another from if input and output linearization. In order to cope with the parameter uncertainty, robust control is incorporated into the basic control law and the asymptotic convergence of tracking error to a certain bounded region is guaranteed. For stability and performance improvement within the bounded region, an adaptive control is introduced. Simulation tests for the motion control of an underwater wall-ranging robot confirm the performance improvement and the robustness of this controller.

• 한국군사과학기술학회지
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• 제10권3호
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• pp.161-172
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• 2007

This article suggests an inverse kinematics analysis of a two degree of freedom spatial parallel motion simulator and design methodology of the robust PID controller. The parallel motion simulator consists of a fixed base and a moving frame connected by two serial chains, with each serial chain containing one revolute joint and two passive spherical joint. First, an inverse kinematics problems are solved in order to find the joint variable necessary to bring the end effector to track the desired trajectory. Second, an inverse optimal PID controller is proposed to track trajectories in the face of uncertainty. And the $H_{\infty}$ optimality and robust stability of the closed-loop system is acquired through the PID controller. Finally numerical results show the effectiveness of the PID controller that is designed by square/linear tuning laws.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제7권2호
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• pp.96-101
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• 2007

Neural networks are known as kinds of intelligent strategies since they have learning capability. There are various their applications from intelligent control fields; however, their applications have limits from the point that the stability of the intelligent control systems is not usually guaranteed. In this paper we propose an adaptive tracking control for robot manipulators using the radial basis function network (RBFN) that is e. kind of neural networks. Adaptation laws for parameters of the RBFN are developed based on the Lyapunov stability theory to guarantee the stability of the overall control scheme. Filtered tracking errors between actual outputs and desired outputs are discussed in the sense of the uniformly ultimately boundedness(UUB). Additionally, it is also shown that parameters of the RBFN are bounded. Experimental results for a SCARA-type robot manipulator show that the proposed adaptive tracking controller is adaptable to the environment changes and is more robust than the conventional PID controller and the neuro-controller based on the multilayer perceptron.

• ETRI Journal
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• 제30권2호
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• pp.338-340
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• 2008

In this letter, we propose a novel approach to detecting and tracking apartment buildings for the development of a video-based navigation system that provides augmented reality representation of guidance information on live video sequences. For this, we propose a building detector and tracker. The detector is based on the AdaBoost classifier followed by hierarchical clustering. The classifier uses modified Haar-like features as the primitives. The tracker is a motion-adjusted tracker based on pyramid implementation of the Lukas-Kanade tracker, which periodically confirms and consistently adjusts the tracking region. Experiments show that the proposed approach yields robust and reliable results and is far superior to conventional approaches.

• 제어로봇시스템학회논문지
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• 제9권6호
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• pp.466-472
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• 2003

This paper describes a tracking control for the mobile robot based on fuzzy systems. Since the mobile robot has the nonholonomic constraints, these constraints should be considered to design a tracking controller for the mobile robot. One of the well-known tracking controllers for the mobile robot is the back-stepping controller. The conventional back-stepping controller includes the dynamics and kinematics of the mobile robot. The conventional back-stepping controller is affected by the derived velocity reference by a kinematic controller. To improve the performance of the conventional back-stepping controller, this paper uses the fuzzy systems known as the nonlinear controller. The new velocity reference for the back-stepping controller is derived through the fuzzy inference. Fuzzy rules are selected for gains of the kinematic controller. The produced velocity reference has properly considered the varying reference trajectories. Simulation results show that the proposed controller is more robust than the conventional back-stepping controller.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.1211-1212
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• 2008

In this paper, we propose image process modeling as a part of location based surveillance system for unauthorized target recognition and tracking in harbor, airport, military zone. For this, we compress and store background image in lower resolution and perform object extraction and motion tracking by using sobel edge detection and difference picture method between real images and a background image. In addition to, we use Independent Component Analysis Neural Network for moving target recognition. Experiments are performed for object extraction and tracking of moving targets on road by using static camera in 20m height building and it shows the robust results.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.167.2-167
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• 2001

This paper presents guidance and control laws which guarantee a minimum fuel consumption and have obustness against various disturbances during a terminal-landing phase on the lunar surface. The nonlinear robust tracking control system is designed to track the reference profiles, which are expressed by exponential functions. An adjustment law in the tracking controller is given in the form of the differential equations with respect to the controller´s variable gains. Computer simulations are performed to examine the tracking accuracy, the robustness in a thrust failure mode, and the vertical soft landing at a pre-assigned point on the lunar surface. The results of numerical simulation show the effectiveness of the present control law.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.120-124
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• 1991

In this paper, we consider the maneuvering detection and target tracking problem in uncertain linear discrete-time systems. The maneuvering detection is based on X$^{2}$ test[2,71, where Kalman filters have been utilized so far. The target tracking is performed by the maneuvering input compensation based on a maximum likelihood estimator. KF has been known to diverge when some modelling errors exist and fail to detect the maneuvering and to track the target in uncertain systems. Thus this paper adopt the FIR filter[l], which is known to be robust to modelling errors, for maneuvering detection and target tracking problem. Various computer simulations show the superior performance of the FIR filter in this problem.

• Journal of Positioning, Navigation, and Timing
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• 제7권3호
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• pp.113-125
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• 2018

Since the global positioning system receivers on the surface of the Earth use satellite signals sent from a remote distance and the intensity of received signals is weak, they are vulnerable to jamming. This paper implements a vector-tracking loop (VTL)-based global navigation satellite system (GNSS) receiver algorithm as an anti-jamming technique and compares the performance of VTL-based receivers with that of scalar-tracking loop (STL) that is used in general GNSS receivers at various jamming environments and a vehicle's dynamics. The simulation results shows that VTL is more robust against jamming than STL in all operating environments.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 춘계학술대회
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• pp.893-898
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• 2003

Coulomb friction is an important factor for precise position tracking control systems. The control systems with friction causes the steady state error because of being sensitive to the change of system condition and highly nonlinear characteristics. To overcome these problems, we use an estimation scheme of Coulomb friction to experiment for it's compensating. The estimated factor for Coulomb friction is used as a feed-forward compensator to improve the tracking performance of ball-screw systems. The tracking performance was improved by compensating the estimated friction torque in the feed-forward term. And, the sliding mode control which is derived from the Lyapunov stability theorem is applied for robust stability and reducing chattering. The experimental results show that the sliding mode controller with adaptive friction compensator has a good tracking performance compared with the friction uncompensated controller.