• Journal of Mechanical Science and Technology
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• v.15 no.1
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• pp.66-80
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• 2001

In brake systems, a proportioning valve(P. V), which reduces the brake line pressure on each wheel cylinder for the anti-locking of rear wheels, is closely related to the safety of vehicles. However, it is impossible for current P. V. s to completely control brake line pressure because, mechanically, it is an open loop control system. In this paper we describe an electronic brake force distribution system using a direct adaptive fuzzy controller in order to completely control brake line pressure using a closed loop control system. The objective of the electronic brake force distribution system is to change the cut-in-pressure and the valve slop of the P. V in order to obtain better performance of the brake system than with mechanical systems.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.7
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• pp.533-538
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• 2002

We propose a direct adaptive controller for a class of nonlinearly parametrized systems. A normalized output error is added to the previous control law to construct the proposed adaptive controller. The transient performance of the resulting closed-loop system can be guaranteed by suitably choosing a novel kind of Lyapunov function while the tracking performance of the adaptive control system is improved using the proposed algorithm. Finally, the effectiveness of the proposed algorithm is illustrated with computer simulation.

• Proceedings of the KIEE Conference
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• 2002.04a
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• pp.79-81
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• 2002

This paper develops a adaptive fuzzy controller based fuzzy logic control for high performance speed controller in permanent magnet synchronous motor(PMSM) drives. In the proposed system, fuzzy control is used to implement the direct controller as well as the adaptation mechanism. The operation of the direct fuzzy controller and the fuzzy logic based adaptation mechanism is studied. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive fuzzy controller is evaluated by simulation for various operating conditions. The validity of the proposed adaptive fuzzy controller is confirmed by performance results for PMSM drive system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.249-257
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• 1995

In this paper, we demeonstrate that neural networks can be used effectively for the control of nonlinear dynamical system. To adaptively control a plant, there are two distinct approach. these are direct control and indirect control. Both direct and Indirect adaptive control are trained using static back propagation. In indirect, using the resulting identification model, which contains neural networks and linear dynamical elements as subsystems, the parameters of the controller are adjusted.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.4
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• pp.445-449
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• 1986

This paper presents a direct adaptive control scheme for nonminimum phase systems of which controller parameters are estimated from the least-squares algorithm, and some additional auxiliadry parameters are obtianed from the proposed polynomial identity equation. Integral action is incorporated into the adaptive controller to eliminate the steady-state error, and to satisfy a condition of the unique solution for the polynomial identity as well.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1155-1157
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• 1996

In this paper, the direct adaptive control using neural networks is presented for the control of chaotic nonlinear systems. The direct adaptive control method has an advantage that the additional system identification procedure is not necessary. Two direct adaptive control methods are applied to a Duffing's equation and the simulation results show the effectiveness of the controllers.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2001.11a
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• pp.181-185
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• 2001

This paper presents a digitally speed sensorless control system for induction motor with direct torque control (DTC). The drive is based on Mode1 Reference Adaptive System (MRAS) using state observer as a reference model fat flux estimation. The system are closed loop stator flux and torque observer for wide speed range that inputs are currents and voltages sensing of motor terminal, model reference adaptive control (MRAS) with rotor flux linkages for the speed turning aignal at low speed range, two hysteresis controllers. The Proposed system is verified through simulation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.44-49
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• 2001

For minimum phase systems, the conventional fuzzy logic controllers (FLCs) use the error and the change-of-error as fuzzy input variables. Then the control rule table is a skew symmetric type, that is, it has UNLP (Upper Negative and Lower Positive) or UPLN property. This property allowed to design a single-input FLC (SFLC) that has many advantages. But its control parameters are not automatically adjusted to the situation of the controlled plant. That is, the adaptability is still deficient. We here design a single-input direct adaptive FLC (SDAFLC). In the AFLC, some parameters of the membership functions characterizing the linguistic terms of the fuzzy rules are adjusted by an adaptive law. The SDAFLC is designed by a stable error dynamics. We prove that its closed-loop system is globally stable in the sense that all signals involved are bounded and its tracking error converges to zero asymptotically. We perform computer simulations using a nonlinear plant and compare the control performance between the SFLC and the SDAFLC.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.377-380
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• 1992

This paper proposes a novel direct adaptive pole placement control algorithm which can be applied to continuous time nonminimum phase systems. The algorithm is based on Lyapunov's direct method. By introducing an auxiliary signal, a minimal error model is constructed in state space. Using the error model an estimation law is obtained via Lyapunov's second stability theorem. The global stability of the overall system is established.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.69-71
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• 1997

The direct drive motor is directly coupled by load. So, it is directly affected by load and disturbances. To control the direct drive motor, a robust controller is need. The main feature of variable structure system is that system trajectories are robust and insensitive to parameter variations and disturbances in the sliding mode. In this paper, adaptive variable structure controller, is used for the BLDD SM(Brushless Direct Drive Servo Motor) control. The chattering problem is reduced by using the saturation function.