• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.8-15
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• 2024

This paper proposes a linear model predictive control of 6-DOF remotely operated underwater vehicles using nonlinear robust internal-loop compensator (NRIC). First, we design a integrator embedded linear model prediction controller for a linear nominal model, and then let the real model follow the values calculated through forward dynamics. This work is carried out through an NRIC and in this process, modeling errors and external disturbance are compensated. This concept is similar to disturbance observer-based control, but it has the difference that H_∞ optimality is guaranteed. Finally, tracking results at trajectory containing the velocity discontinuity point and the position tracking performance in the disturbance environment is confirmed through the comparative study with a traditional inverse dynamics PD controller.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.957-962
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• 2007

This paper describes a new mechanism for improving the force of actuators based on shape memory alloys (SMA) by increasing the number at which a coil pattern SMA spring can evenly be heated. This structure accomplishes a high efficient transformation between force and displacement overcoming the main mechanical drawback of shape memory alloys, that being the limit strain. A pantograph manipulator actuated by the introduced new mechanism has been designed for this research. Mechanical structure and driving mechanism of this manipulator are described in detail, and its control algorithm and current amplifier circuit in a position control system are designed.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.263-266
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• 1998

This paper propose a prefilter type inverse control algorithm using chaotic neural networks. Since the chaotic neural networks show robust characteristics in approximation and adaptive learning for nonlinear dynamic system, the chaotic neural networks are suitable for controlling robotic manipulators. The structure of the proposed prefilter type controller compensate velocity of the PD controller. To estimate the proposed controller, we implemented to the Cartesian space control of three-axis PUMA robot and compared the final result with recurrent neural network(RNN) controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.598-603
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• 2004

An optical head actuator of an optical disk drive consists of two servo mechanisms for the focusing and the tracking to acquire data from disk. As the rotational speed of the disk grows, the utilized lag-lead-lead compensator has known to be above its ability for precisely controlling the optical head actuator. To overcome the difficulty, this paper propose a new controller design method for optical head actuator based fuzzy proportional-integral-derivative (PID) control and the genetic algorithm(GA). It employs a two-stage control structure with a fuzzy PI and a fuzzy PD control and is optimized by the GA to yield the suboptimal fuzzy PID control performance. It is shown the feasibility of the proposed method through a numerical tracking actuator simulation.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.681-683
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• 2004

This paper describes the control of a geared DC motor having a backlash for implementation of a humanoid robot using disturbance observer. Critical problem of the humanoid robot is caused by the nonlinearity such as a backlash. To meet this problem, a control method using disturbance observer has been proposed. The disturbance observer is designed to estimate the effects of nonlinearities in the system, to make the nonlinear system behave linearly. To design the low-pass filter in the disturbance observer, cut-off frequency of the output should be found. The goal of this paper is the implementation of the proposed system, compensating the backlash effect. To accomplish the goat, PD control and disturbance observer are employed to the system with no load and full load. As a result, system stability can be guaranteed by compensating the effect of backlash. In addition, real experiment shows the proposed control methodology will satisfy the stable working of a humanoid type in the future.

• Journal of Advanced Research in Ocean Engineering
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• v.1 no.2
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• pp.85-93
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• 2015

The nonlinear time-domain analysis method was implemented to carry out a series of integrated simulations for a deep-water crane vessel system composed of four sub components, including a floating vessel, lifted equipment, hoisting cable and dynamic positioning (hereinafter DP) system. The analysis of the coupled dynamics consists of the crane vessel and equipment connected using the crane wire, and the DP is modeled according to the wind, wave and current conditions. The DP systems were numerically implemented using a classical PD feedback controller, and various simulations of the deepwater installation were conducted using different conditions in order to evaluate the global performance of the floating crane vessel combined with the DP system.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.11
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• pp.930-935
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• 2005

In this paper, position tracking control of an autonomous helicopter is presented. Combining an LQR method and a proportional control forms a simple PD control. Since LQR control gains are set for the velocity control of the helicopter, a position tracking error occurs. To minimize a position tracking error, neural network is introduced. Specially, in the frame of the reference compensation technique for teaming neural network compensator, a position tracking error of an autonomous helicopter can be compensated by neural network installed in the remotely located ground station. Considering time delay between an auto-helicopter and the ground station, simulation studies have been conducted. Simulation results show that the LQR with neural network performs better than that of LQR itself.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.330-333
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• 2005

In this study, a method of designing a neurointerface using neural network (NN) is proposed for controlling nonholonomic mobile robots. According to the concept of virtual master-slave robots, in particular, a partially stable inverse dynamic model of the master robot is acquired online through the NN by applying a feedback-error learning method, in which the feedback controller is assumed to be based on a PD compensator for such a nonholonomic robot. A tracking control problem is demonstrated by some simulations for a nonholonomic mobile robot with two-independent driving wheels.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.101.4-101
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• 2002

I. Introduction ▶The PID(Proportional-Integral-Derivative) controller is widely used in the industry it can be implemented easily for a typical second order plant. ▶The parameters of PID controller should be adapted complicatedly if a plant is various or the load is present. ▶For solving the problem, many control techniques have been developed. ▶A major method is a hybrid Fuzzy-PID controller. But, in case of using this method, we can not obtain characteristic of rapidly response and not achieved compensation on disturbance. ▶Therefore, we will use compensator fuzzy controller a front Hybrid type fuzzy-PID controller...

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.346-350
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• 1996

In optical disk drives, one of commonly used pickup actuator is a Sliding and rotary type of pickup actuator which is cheaper than other pickup actuators and has simple assembly. However, it reported that non-linearity due to friction between a shaft and a sleeve had to be considerably analyzed in design and servo system in employing this type of pickup actuator. In this paper, this friction is modeled as a Coulomb's friction and the effect of friction is examined in the simulation. A digital servo system is applied to pickup actuator with friction in order to have good focusing servo. To enhance focusing servo performance using digital servo merit, frist PD-controller is applied to have fast response performance, second lead-lag compensator is applied to have stable focusing performance.