• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.469-474
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• 2002

The Field Robot means the machinery applied for outdoor tasks in construction, agriculture and undersea etc. In this study, to field-robotize a hydraulic excavator that is mostly used in construction working, we have developed an automatic excavation system and adaptive control system. A model- reference adaptive controller has been designed on the model that is obtained through off-line System Identification. It is illustrated by computer simulations that the proposed control system gives good performances in the trajectory tracking control and adaptation to parameter variation.

• Journal of the Society of Naval Architects of Korea
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• v.34 no.3
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• pp.19-26
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• 1997

This paper is concerned with the design of neural-network based autopilot control system. The back-propagation neural network introduced in the previous paper by authors is applied to the autopilot control system. As a result, two neural-network controllers are developed, which are the model reference adaptive neural controller and the instantaneous optimal neural controller. The model reference adaptive neural controller is the control technique that the heading angle and angular velocity are controlled by the rudder angle to follow the output of the reference model. The instantaneous optimal neural controller optimizes the transition from one state to the next state. These control techniques are applied to a simple ship maneuvering model and their effectiveness is proved by numerical examples.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.786-791
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• 2003

This paper proposes an adaptive control algorithm for nonholonomic mobile robots with unknown parameters and the proposed control method is used in numerical simulations for applying to a practical twowheeled welding mobile robot(WMR). The proposed adaptive controller to track an arbitrary given welding path is designed by using back-stepping technique and is derived for a nonlinear model under the assumption such that the system parameters are partially known. Moreover, the proposed adaptive control system is stable in the sense of Lyapunov stability. Inertia moments of system are considered to be unknown parameters and their values can be estimated simply by using update laws proposed in an adaptive control scheme of this research. The simulation results are provided to show the effectiveness of the accurate tracking capability of the proposed controller for two-wheeled welding mobile robot with a smooth curved reference welding path.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.2
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• pp.1044-1050
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• 2014

Maximum torque per ampere vector controller is widely used to control permanent magnet synchronous motors. For the controller to work properly, it is important to know the exact values of motor parameters such as a stator resistance, inductances, and the flux linkage of the permanent magnet. In this paper, an adaptive control algorithm is proposed to estimate these parameters using MRAS(Model Reference Adaptive System). Simulation results demonstrate the effectiveness of the proposed algorithm.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.6
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• pp.930-935
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• 1987

This paper presents a decentralized model reference adaptive control scheme for an interconnected continuous linear system composed of a number of single input single output subsystems. The scheme can treat the unknown strengh of interconnections as well as the uncertainty of subsystems. The scheme automatically adjusts the local feedback gains so that the output of each subsystem exponetially tracks that of the reference model.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.6
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• pp.89-96
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• 1985

A pole-placement control of discrete, deterministic, single-input single-output nonmini-mum phase systems is considered using a model reference type approach. The proposed pole-placement controller is designed in the parameter form to make the transfer function of the controller equal to that of the reference model with only single variable polynomial S(q-1). The proposed adaptive pole-placement controllr is designed with the true system para-meters by applying the adaptation method to the proposed pole-placement controller.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1688-1691
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• 1997

In the time-invarient system, the adaptive controller was designed for the non-tracking error in the 1980's. In this study, the Model Reference Adaptive Control using on-line processing method is used to identify the coefficients of the model, and the Robust Controller (H.inf.) is designed to stabilize the rigid body and the flexible body of satellite, which can be perturbed due to disturbance, etc. The result obtained by H.inf. controller is compared with that of the PI(Proportional and Intergation) controller which is commonly used for stabilizing satellite.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.872-877
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• 1990

Robustness of a model refernece direct adaptive pole placement control for not necessarily minimum phase systems is studied subject to unmodeled dynamics and bounded disturbances. The adaptive control scheme involves two estimators for the system and the controller parameter estimation, respectively. The robustness is obtaind under some weak assumptions and by using both a normalized least-squares algorithm with dead zone and an appropriate nonlinear feedback.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.32 no.11
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• pp.394-403
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• 1983

This paper discusses a model reference adaptive control for a multi-input multi-output continuos system in matrix fraction description. The controller is of Monopoli-Narendra type with a time-varying gain matrix in the parameter adaptation law. The transfer matrix of the given plant with an adjustable controller is made to approach to that of the reference model asymptotically. It is shown that, under some plausible assumptions such as on the knowlidge of an interactor matrix, the algorithm for a single-input single-output system can be appropriately extended to a multi-input multi-output system. The convergence of an adaptation law is estavlished with some stability theory and stability of the overall system is asserted by an analytical investigation.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.3
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• pp.301-311
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• 1990

A multiple controller structure consisting of a typical feedback controller and an additive redundant controller is proposed for enhancing the reliability of the control system. For the case where the main controller is chosen as a pole assignment controller with input/output measurements and the redundant controller as the Model Reference Adaptive Controller (MRAC) whose reference model is the closed-loop combination of the plant and the main controller, it is proven that the tracking error between the command input and plant output converges to zero under failure in one of the controllers or parameter perturbations of the plant, and further that the reliability measured by Mean Time To Failure (MTTF) is greater than that of the system with only a single main controller. A simulation Example is provided to illustrate reliable operation of the proposed control system against the controller failure.