• Proceedings of the KSME Conference
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• 2008.11a
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• pp.870-875
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• 2008

The main objective of this paper is to control a trajectory tracking of the fish-mimetic robot by CPG (Central Pattern Generator), which is biological approach. CPG is biological neural networks that generate rhythmic movements for locomotion of animals, such as walking, running, swimming and flying. Animals show marvelous ability of autonomous dynamic adaptation for an unsteady fluid dynamic environment or various environments. So, we propose the 3-DOF CPG controller to track the trajectory of the fish robot in plane motion. The conformity of the proposed control algorithm is validated by simulation for a fish robot model, which is made by a commercial dynamic package.

• Journal of Power System Engineering
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• v.7 no.3
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• pp.40-47
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• 2003

In this study, position and force simultaneous trajectory tracking control apparatus with pneumatic cylinder driving system is proposed. The pneumatic cylinder driving system that consists of two pneumatic cylinders constrained in series and two proportional flow control valves offers a considerable advantage as to non-interaction of the actuators because of the low stiffness of the pneumatic actuators. The controller applied to the driving system is composed of a non-interaction controller to compensate for interaction of two cylinders and a disturbance observer to reduce the effect of model discrepancy of the driving system in the low frequency range that cannot be suppressed by the non-interaction controller. The experimental results with the proposed control apparatus show that the interacting effects of two cylinders are eliminated remarkably and the proposed control apparatus tracks the given position and force trajectory accurately.

• The Journal of Korea Robotics Society
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• v.13 no.4
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• pp.256-264
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• 2018

Unlike normal wheels, the Mecanum wheel enables omni-directional movement regardless of the orientation of a mobile robot. In this paper, a robust trajectory tracking control method is developed based on the dynamic model of the Mecanum wheel mobile robot in order that the mobile robot can move along the given path in the environment with disturbance. The method is designed using the impedance control to make the mobile robot to track the path, and the integral sliding mode control for robustness to disturbance. The good performance of the proposed method is verified using the MATLAB /Simulink simulation and also through the experiment on an actual Mecanum wheel mobile robot. In both the simulation and the experimentation, we make the mobile robot move along a reference trajectory while maintaining the robot's orientation at a constant angle to see the characteristics of the Mecanum wheel.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.1
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• pp.42-54
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• 2009

Contrast to the 6-DOF nonlinear dynamic modeling of nonlinear tracking problem, 3-DOF point-mass modeling of flight mechanics is efficient and adequate for applying the trajectory optimization problem. There exist limitations to apply an optimal trajectory from point-mass modeling as a reference trajectory directly to conduct the nonlinear tracking control, In this paper, new matching trajectory optimization scheme is proposed to compensate those differences of mismatching. To verify performance of proposed method, full ascent three-dimensional flight trajectories are obtained by reflecting the real constraints of flight conditions and airship performance with and without jet stream condition. Then, they are compared with the optimal trajectories obtained from conventional method.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.582-590
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• 2007

Nonlinear adaptive control of overhead cranes is investigated for anti-sway trajectory tracking with high-speed hoisting motion. The sway dynamics of two dimensional underactuated overhead cranes is heavily coupled with the trolley acceleration, hoisting rope length, and the hoisting velocity which is an obstacle in the design of decoupling control based anti-sway trajectory tracking control law To cope with this obstacle. we propose a fuzzy nonlinear adaptive anti-sway trajectory tracking control law guaranteeing the uniform ultimate boundedness of the sway dynamics even in the presence of uncertainties in such a way that it cancels the effect of the trolley acceleration and hoisting velocity on the sway dynamics. In particular. system uncertainties, including system parameter uncertainty unmodelled dynamics, and external disturbances, are compensated in an adaptive manner by utilizing fuzzy uncertainty observers. Accordingly, the ultimate bound of the tracking errors and the sway angle decrease to zero when the fuzzy approximation errors decrease to zero. Finally, numerical simulations are performed to confirm the effectiveness of the proposed scheme.

• Journal of Advanced Navigation Technology
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• v.25 no.3
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• pp.217-222
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• 2021

EOTS(Electro-Optical Tracking System) is utilized in acquiring visual information to assess a guided missile's performance. As the missile travels so fast, it is almost impossible for operator to re-capture the lost target. The RADAR or telemetry data are used to re-capture the lost target however facilities to receive real time data is required, which constrains selection of tracking site. Unlike aforementioned data, pre-calculated nominal trajectory can be used without communication facility. This paper proposes a method to predict lost target's state by employing nominal trajectory. Firstly, observed trajectory and nominal trajectory are compared using DTW and current target's state is predicted. The predicted state is used as observation in Kalman filter's correction phase to predict target's next state. The plausibility of the proposed method is verified by applying on actual missile trajectory.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.10
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• pp.1303-1309
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• 2014

In this paper, we present an iterative learning control (ILC) framework for tracking problems with predefined data points that are desired points at certain time instants. To design ILC systems for such problems, a new ILC scheme is proposed to produce output curves that pass close to the desired points. Unlike traditional ILC approaches, an algorithm will be developed in which the control signals are generated by solving an optimal ILC problem with respect to the desired sampling points. In another word, it is a direct approach for the multiple points tracking ILC control problem where we do not need to divide the tracking problem into two steps separately as trajectory planning and ILC controller.The strength of the proposed formulation is the methodology to obtain a control signal through learning law only considering the given data points and dynamic system, instead of following the direction of tracking a prior identified trajectory. The key advantage of the proposed approach is to significantly reduce the computational cost. Finally, simulation results will be introduced to confirm the effectiveness of proposed scheme.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.8-11
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• 1996

In impedance control for contact force tracking it is well known that the reference trajectory of the robot is calculated from known environment stiffness. The accuracy of estimating the environment stiffness determines the performance of the resulting force tracking. Here we present a simple technique, called the trajectory modification technique(TMT), of determining the reference trajectory under the condition that the environment stiffness is unknown. Computer simulation studies have shown that force tracking using the proposed technique is excellent for unknown environment with time varying stiffness.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.3
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• pp.126-132
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• 2004

This paper proposed trajectory tracking control based on genetic algorithm. Trajectory tracking control scheme are real coding genetic algorithm(RCGA) and back-propagation algorithm(BPA). Control scheme ability experience proposed simulation. Stable tracking control problem of mobile robots have been studied in recent years. These studies have guaranteed stability of controller, but the performance of transient state has not been guaranteed. In some situations, constant gain controller shows overshoots and oscillations. So we introduce better control scheme using real coding genetic algorithm and neural network. Using RCGA, we can find proper gains in several situations and these gains are generalized by neural network. The generalization power of neural network will give proper gain in untrained situation. Performance of proposed controller will verity numerical simulations and the results show better performance than constant gain controller.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.6
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• pp.435-441
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• 2003

This paper addresses that an approximation and tracking control of realtime recurrent neural networks(RTRN) using two-dimensional iterative teaming algorithm for an electro-hydraulic servo system. Two dimensional learning rule is driven in the discrete system which consists of nonlinear output fuction and linear input. In order to control the trajectory of position, two RTRN with the same network architecture were used. Simulation results show that two RTRN using 2-D learning algorithm are able to approximate the plant output and desired trajectory to a very high degree of a accuracy respectively and the control algorithm using two identical RTRN was very effective to trajectory tracking of the electro-hydraulic servo system.