• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.680-684
• /
• 1998

This paper presents an efficient method which estimates the systems with unmodeled dynamics using D-L networks. This method is applied for estimating the system with unmodeled dynamics from only input-output information , so it can exclude additional procedure for system description and reduce the computational burden required for real-time estimation. Higher convergence speed is achieved in this manner in comparison with widely-used conventional methods.

• Proceedings of the KIEE Conference
• /
• 1997.11a
• /
• pp.113-115
• /
• 1997

This paper presents an efficient method which can estimate the system with unmodeled dynamics using D-L networks. The proposed method is to estimate system with unmodeled dynamics recursively from only input-output information, which can exclude additional procedure for system description and thus reduce the required computational burden for real-time estimation. Higher convergence speed is achieved with our manner when compared with widely-used conventional methods.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.66 no.1
• /
• pp.66-71
• /
• 2017

In this paper, we study the robustness of disturbance observer based controller for DC motor in the presence of unmodeled dynamics. It is well known that the robustness property usually becomes weaker as the control gain becomes larger. On the contrary to this expectation, it is shown that the phase margin of DOB controller remains quite a large value even though the time constant of Q-filter becomes smaller. The computer simulation results show that DOB controller is able to stabilize the motor system even in the presence of unmodeled dynamics. On the contrary, the unity-feedback system fails to maintain stability when a high gain feedback is employed for the purpose of achieving better disturbance attenuation performance.

• Journal of Institute of Control, Robotics and Systems
• /
• v.3 no.1
• /
• pp.9-16
• /
• 1997

The method of designing robust two degree of freedom(2 DOF) controllers for linear systems with parameter uncertainties and unmodeled dynamics is presented in this paper. Robust performance condition that accounts for robust model matching of closed loop system and disturbance rejection is derived. Using the robust performance condition, the feedback controller is designed to meet robust stability and disturbance rejection specifications, while prefilter is used to improve the robust model matching properties. The $H^{\infty}$ and $\mu$ controller for six degree of freedom vehicle with parameter variations are designed and compared. Simulations for hydrodynamic parameter variations and disturbance are presented to demonstrate the achievement of good robust performance.

• Proceedings of the KIEE Conference
• /
• 1991.11a
• /
• pp.353-356
• /
• 1991

This paper proposes a robust direct adaptive control system implementation using a 80286 microprocessor-based system for controlling the speed of a DC servo motor. In this paper, assuming that the unmodeled dynamics of the plant are sufficiently small in the low-frequency range, the plant as linear time-invariant system is the second relative degree, we construct the direct adaptive control system with the algorithm considering plant unmodeled dynamics and execute the experiment, and compare the characteristics with those of PI algorithm's. It shows that an easy implementation of the built controller is due to the usage of software for the algorithm.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.33B no.6
• /
• pp.208-216
• /
• 1996

This paper presents a decentralized control scheme for interconnected systems with unmodeled nonlinearities and interactions using a neural coordinator. The interactions due to the interconnection and the unmodeled nonlinearity associated with each subsystem are represented by the deviations from linearized states of decomposed subsystems. the decentralized controller is composed of local controllers and a neural coordinator. The local controller for each subsystem is derived from linearized local system parameters y linear optimal control theory. the neural cooridnator generates a corrective control signal to cancel the effect of deviation sthrough the backpropagation learning with the rrors obtained form the difference of the local system outputs and reference model outputs. the reference model consists of the part of local system without deviations. The effectiveness of the proposed control scheme is demonstrated by simulation studies.

• Journal of Ocean Engineering and Technology
• /
• v.14 no.2
• /
• pp.7-12
• /
• 2000

This paper presents a non-regressor based adaptive control scheme for the trajectory tracking of underwater vehicle-mounted manipulator systems(UVMS). The adaptive control system includes a class of unmodeled effects is applied to the trajectory control of an UVMS. The only information required to implement this scheme ios the upper bound and lowe bound of the system parameter matrices the upper bound of unmodeled effects the number of joints the position and attitude of the vehicle and trajectory commands. The adaptive control law estimates control gains defined by the combinations of the bounded constants of system parameter matrices and of a filtered error equation. To evaluate the performance of the non-regressor based adaptive controller computer simulation was performed with a two-link planar robot model mounted on an underwater vehicle. The hydrodynamic effects acting on the manipulator are included. It is assumed that the vehicle's motion is slow and can be predicted with a proper compensator.

• Proceedings of the KIEE Conference
• /
• 1993.07a
• /
• pp.373-375
• /
• 1993

In this paper we deal with the design and implementation problem of a robust adaptive controller for a direct drive manipulator with unmodeled dynamics. The proposed controller ensures that the closed loop system is stable and output errors are converged to some boundary. To validate the improved performance of the proposed controller experimental results are presented in this paper.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.54.2-54
• /
• 2001

In this paper two control strategies, command shaping control and optimal control, which aim to the reduction of the residual vibrations of the payload in a container crane system are investigated. Both control methods are open loop control. Due to unmodeled dynamics of the plant and disturbances like initial sway and wind, some residual sway always exists at the end of trolley movement. Command inputs are designed to achieve the control objectives including minimal residual vibration and robustness in the presence of unmodeled dynamics. Simulation results of various command inputs are compared in terms of arrival time, residual sway angle, robustness, and maximum sway distance during the traveling. Command shaping method provides a more competent tool than optimal control.

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.40.1-40
• /
• 2002

1. Introduction 2. Vehicle Equations of Motion 3. Discrete Model of the Plant with an Unmodeled Dynamics 4. Design of an Adaptive Control 5. Parameter Adjustment Law 6. Numerical Simulations 7. Summary