• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.578-581
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• 2001

In this paper, the development of a new group controller for high-speed elevator is carried out utilizing approach of an adaptive dual fuzzy logic. A goals of control are the minimization of waiting time, mean-waiting time and long-waiting time in a building. when a new hall call is generated, adaptive dual fuzzy controller evaluate traffic pattern and change appropriately the membership function of fuzzy rule base. Control for co-operation among elevators in group control algorithm are essential, and the most critical control function in group controller is a effective and proper hall call assignment of elevators. Thy group elevator system utilizing adaptive dual fuzzy control reveals a great deal of improvement on its performance.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.157-160
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• 2000

In this paper, the development of a new group controller for high-speed elevator is carried out utilizing approach of an adaptive dual fuzzy logic. A goals of control are the minimization of waiting time, mean-waiting time and long-waiting time in a high building, when a new hall call is generated, adaptive dual fuzzy controller evaluate traffic pattern and change appropriately the membership function of fuzzy rule, base. Control for co-operation among elevators in group control algorithm are essential , and the most critical control function in group controller is a effective and proper hall call assignment of elevators. The group elevator system utilizing adaptive dual fuzzy control reveals a great deal of improvement on its performance.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.596-606
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• 2008

In this paper, we present a co-design methodology of dynamic optimal network-bandwidth allocation (ONBA) and adaptive control for networked control systems (NCSs) to optimize overall control performance and reduce total network-bandwidth usage. The proposed dynamic co-design strategy integrates adaptive feedback control with real-time scheduling. As part of this co-design methodology, a "closed-loop" ONBA algorithm for NCSs with communication constraints is presented. Network-bandwidth is dynamically assigned to each control loop according to the quality of performance (QoP) information of each control loop. As another part of the co-design methodology, a network quality of service (QoS)-adaptive control design approach is also presented. The idea is based on calculating new control values with reference to the network QoS parameters such as time delays and packet losses measured online. Simulation results show that this co-design approach significantly improves overall control performance and utilizes less bandwidth compared to static strategies.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.4
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• pp.312-316
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• 2004

In this paper, it is presented an adaptive robust control system to implement real-time control of a robot manipulator. There are Quantitative or qualitative differences between a real robot manipulator and a robot modeling. In order to compensate these differences, uncertain factors are added to a robot modeling. The uncertain factors come from imperfect knowledge of system parameters, payload change, friction, external disturbance, etc. Also, uncertainty is often nonlinear and time-varying. In the proceeding work, we proposed a class of robust control of a robot manipulator and provided the stability analysis. In the work, we propose a class of adaptive robust control of robot manipulator with bound estimation. Through experiments, the proposed adaptive robust control scheme is proved to be an efficient control technique for real-time control of a robot system using DSP.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.378-384
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• 1993

In this paper, an intelligent adaptive controller is proposed for the process with unmodelled dynamics. The intelligent adaptive controller consists of the numeric adaptive controller and the intelligent tuning part. The continuous scheme is used for the numeric adaptive controller to avoid the problems occurred in the discrete time schemes. The adaptive controller is adopted to the process with time delay. It is an implicit adaptive algorithm based on GMV using the emulator. The tuning part changes the design parameters in the control algorithm. It is a multilayer neural network trained by robustness analysis data. The proposed method can improve the robustness of the adaptive control system because the design parameters are tuned according to the operating points of the process. Through the simulation, robustnesses are shown for intelligent adaptive controller. Finally, the proposed algorithms are implemented on the electric furnace temperature control system. The effectiveness of the proposed algorithm is shown from experiments.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.330-335
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• 1994

In this paper, adaprive control and sliding mode control are combined to implement the proposed adaptive sliding mode control(ASMC) algorithm which is new approach to the control of industrial robot manipulator with external disturbances and parameter uncertainties. Adaptive control algorithm is designed by using the principle of the model reference adaptive control method based upon the hyperstability theory. The contribution of this method is that the parameters of the sliding surface are replaced by time varying parameters whose are calculated by an adaptation algorithm, which forces the errors to follow the behavior of a reference error model. Simulation results show that the proposed method not only improves the performance of the system but also reduces the chattering problem of sliding mode control. Consequently, it is expected that the new adaptive sliding mode control algorithm will be suited for various practical applications.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.337-340
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• 1997

In this paper we propose direct and indirect adaptive controllers for a nonlinear multivariable steam generating unit(200MW). In the direct adaptive scheme the estimation of the controller parameter are achieved from tracking error, while in the indirect approach the unknown parameter of the boiler system is estimated by the Hopfield network-based identifier. The performance of two proposed adaptive controllers is shown through simulations.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.7
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• pp.791-799
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• 2006

The aim of this paper is to design an adaptive speed control system of a marine diesel engine by fusion of hard computing based proportional integral derivative (PID) control and soft computing based fuzzy control methods. The model of a marine diesel engine is considered as a typical non oscillatory second order system. When its model and the actual marine diesel engine ate not matched, it is hard to control the speed of the marine diesel engine. Therefore, this paper proposes two methods in order to obtain the speed control characteristics of a marine diesel engine. One is an efficient method to determine the PID control parameters of the nominal model of a marine diesel engine. Second is a reference adaptive speed control method that uses a fuzzy controller and derivative operator for tracking the nominal model of the marine diesel engine. It was found that the proposed PID parameters adjustment method is better than the Ziegler & Nichols' method, and that a model reference adaptive control is superior to using only PID controller. The improved control method proposed here, could be applied to other systems when a model of a system does not match the actual system.

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

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.5
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• pp.977-983
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• 2011

This paper proposes a new adaptive speed controller to achieve a robust speed control of a permanent magnet synchronous motor(PMSM). The proposed adaptive regulator does not require any information on the motor parameter and load torque values, so it is very insensitive to model parameter and load torque variations. Also, the stability of the proposed adaptive control system is proven. To validate the robustness of the proposed adaptive speed controller, both simulation and experimental results are provided under motor parameter and load torque variations. It is clearly demonstrated that the proposed adaptive regulator can accurately control the speed of permanent magnet synchronous motors.