• Proceedings of the KIEE Conference
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• 1993.07b
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• pp.892-894
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• 1993

In this paper, a new control for the robust position control of a brushless direct drive(BLDD) motor using fuzzy logic controller(FLC) is presented. The integral-proportional(IP) position with speed FLC is employed to obtain the robust BLDD motor system, which is approximately linearized using the field-orientation method for an AC servo. The speed FLC for a BLDD motor has the two rule tables. One is the coarse rule table for the transient state and another is the fine rule table for the steady state. The overall system is controlled by using the microprossor in IBMPC 486 and the the robustness is also obtained.

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.2
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• pp.138-143
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• 1999

A new control method for the precision robust position control of a brushless DC(BLDC) motor for direct drive m motor(BLDDM) system using the asymptotically stable adaptive load torque observer is presented. A precision position c control is obtained for the BLDD motor system appro성mately linearized using the fieldlongrightarroworientation method. Many of t these motor systems have BLDD motor to obtain no backlashes. On the other hand, it has disadvantages such as the h high cost and more complex controller caused by the nonlinear characteristics. And the load torque disturbance is d directly affected to a motor shaft. To r밍ect this problem, stability analysis is calTied out using Lyapunov stability t theorem. Using this results, the stability is proved and load disturbance detected by the asymptotically stable adaptive observer is compensated by feedforwarding the equivalent CUlTent having the fast response.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.3
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• pp.214-221
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• 1998

A new control approach using neural network for the robust position control of a BRUSHLESS direct drive(BLDD) motor is presented. The linear quadratic controller plus feedforward neural network is employed to obtain the robust BLDD motor system approximately linearized using field-orientation method for an AC servo. The neural network is trained in on-line phases and this neural network is composed by a feedforward recall and error back-propagation training. Since the total number of nodes are only eight, this system will be easily realized by the general microprocessor. During the normal operation, the input-output response is sampled and the weighting value is trained by error back-propagation at each sample period to accommodate the possible variations in the parameters or load torque. And the state space analysis is performed to obtain the state feedback gains systematically. In addition, the robustness is also obtained without affecting overall system response.

• Journal of IKEEE
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• v.9 no.1 s.16
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• pp.47-56
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• 2005

A new improved robust variable structure tracking controller is presented to provide an accurately prescribed tracking performance for brushless direct drive(BLDD) servo motors(SM) under uncertainties and load variations. A special integral sliding surface suggested for removing the reaching phase problems can define its ideal sliding mode and virtual ideal sliding trajectory from an initial position of SM. The tracking error caused by the nonzero value of the sliding surface is derived. A corresponding continuous control input with the disturbance observer is suggested to track a predetermined virtual ideal sliding trajectory within a prescribed value under all the uncertainties and load variations. The usefulness of the proposed algorithm is demonstrated through the comparative simulations for a BLDD SM under load variations.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.714-716
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• 1995

This Paper presents a novel and systematic approach to a self-learning controller. The proposed controller is built on a neural network consisting of a standard back propagation (BNN) and approxinate reasoning (AR). The fuzzy inference and knowledge representation are carried out by the neural network structure and computing, instead of logic inference. An architecture similar to that used by traditional model reference adaptive control system (MRAC) is employed.

• 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.