• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.74.3-74
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• 2001

This paper proposes a nonlinear adaptive controller based on back-stepping method for tracking reference substrate concentration by manipulating dilution rate in a continuous baker´s yeast cultivating process in stirred tank bioreactor. Control law is obtained from Lyapunov control function to ensure asymptotical stability of the system. The Haldane model for the specific growth rate depending on only substrate concentration is used in this paper. Due to the uncertainty of specific growth rate, it has been modified as a function including the unknown parameter with known bounded values. The substrate concentration in the bioreactor and feed line are measured. The deviation from the reference is observed when the external disturbance such as the change of the feed is introduced to the system ...

• Proceedings of the KIPE Conference
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• 1997.07a
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• pp.89-96
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• 1997

A robust speed control scheme for a brushless DC(BLDC) motor using an adaptive input-output linearization technique is presented. By using this technique, the nonlinear motor model can be linearized in Brunovski canonical form, and the desired speed dynamics can be obtained based on the linearized model. This control technique, however, gives an undesirable output performance under the mismatch of the system parameters and load conditions. For the robust output response, the controller parameters will be estimated by a model reference adaptive technique where the disturbance torque and flux linkage are estimated. The adaptation laws are derived by the Popov's hyperstability theory and positivity concept. The proposed control scheme is implemented on a BLDC motor using the software of DSP TMS320C30 and the effectiveness is verified through the comparative experiments.

• Journal of Electrical Engineering and information Science
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• v.2 no.3
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• pp.113-122
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• 1997

An adaptive input-output linearization technique for a robust speed control of a brushless C(BLDC) motor is presented. By using this technique, the nonlinear moro model can be effectively linearized in Brunovski canonical form, an the desired speed dynamics can be obtained based on the linearized model. This control technique, however, gives an undesirable output performance under the mismatch of the system parameters and load conditions caused by the incomplete linearization. for the robust output response, the controller parameters will be estimated by a model reference adaptive technique where the disturbance torque and flux linkage are estimated. The adaptation laws are derived by the Popov's hyperstability theory nd positivity concept. The proposed control scheme is implemented on a BLDC motor using the software of DSP TMS320C30 and the effectiveness is verified through the comparative simualtions and experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1478-1481
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• 2005

As the model of most practical system cannot be obtained, the practice of typical control method is limited. Accordingly, numerous artificial intelligence control methods have been used widely. Fuzzy control and neural network control have been an important point in the developing process of the field. This paper is proposed adaptive fuzzy-neural network based on the vector controlled interior permanent magnet synchronous motor drive system. The fuzzy-neural network is first utilized for the speed control. A model reference adaptive scheme is then proposed in which the adaptation mechanism is executed using fuzzy-neural network. Also, this paper is proposed estimation of speed of interior permanent magnet synchronous motor using artificial neural network controller. The back-propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back-propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the analysis results to verify the effectiveness of the new method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.12
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• pp.535-541
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• 2002

This paper proposes an adaptive fuzzy controller based fuzzy logic control for high performance of permanent magnet synchronous motor(PMSM) drive. In the proposed system, fuzzy control is sued to implement the direct controller as well as the adaptation mechanism. 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 adaptive fuzzy controller is evaluated by simulation for various operating conditions. The validity of the proposed controller is confirmed by performance results for PMSM drive system.

• Proceedings of the KIPE Conference
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• 1997.07a
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• pp.97-100
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• 1997

A new control method for the robust position control of a brushless DC(BLDC) motor using the asymptotically stable adaptive load torque observer is presented. A precision position control is obtained for the BLDC motor system approximately linearized using the field-orientation method. And the application of the load torque observer is published in [1] using fixed gain. However, the flux linkage is not exactly known for a load torque observer. Therefore, a model reference adaptive observer is considered to overcome the problem of the unknown parameter in this paper. And stability analysis is carried out using Liapunov stability theorem. As a result, asymptotically stable observer gain can be obtained without affecting the overall system response. The load disturbance detected by the asymptotically stable adaptive observer is compensated by feedforwarding the equivalent current having the fast response.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.5
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• pp.794-803
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• 2016

This paper propose a sensorless control system of IPMSM with a adaptive back-EMF estimator and improved instantaneous reactive power compensator. A saliency-based back-EMF is estimated by using the adaptive algorithm. The estimated back-EMF is inputted to the phase locked loop(PLL) and the improved instantaneous reactive power(IRP) compensator for estimating the position/speed of the rotor and compensating the error components between the estimated and the actual position, respectively. The stability of the proposed system is achieved through Popov's hyper stability criteria. The validity of proposed algorithm is verified by the simulations and experiments.

• The Transactions of the Korean Institute of Power Electronics
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• v.19 no.1
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• pp.71-79
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• 2014

In this paper, a new grid voltage estimation algorithm without voltage sensors is proposed for the three-phase vienna rectifier. Generally, input voltage sensor circuits increase size and cost of the PWM rectifier In order to reduce the cost and size and in order to increase reliability from the electrical noise, grid voltage estimation scheme without input voltage sensor is highly required. In this paper, the grid voltage estimation algorithm is proposed by a simple MRAS(Model Reference Adaptive System) observer without input voltage sensors. The validity of the proposed method is proven by simulation and experiment on the three-phase vienna rectifier system.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.2
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• pp.463-477
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• 1991

This study proposed a new method to design a robot manipulator control system capable of tracking the trajectories of joint angles in a reasonable accuracy to cover with actual situation of varying payload, uncertain parameters, and time delay. The direct adaptive model following control method has been used to improve existing industrial robot manipulator control system design. The proposed robot manipulator controller is operated by adjusting its gains based on the response of the manipulator in such a way that the manipulator closely matches the reference model trajectories predefined by the designer. The manipulator control system studied has two loops: they are an inner loop on adaptive model following controller to compensate nonlinearity in the manipulator dynamic equation and to decouple the coupling terms and an outer loop of state feedback controller with integral action to guarantee the stability of the adaptive scheme. This adaptation algorithm is based on the hyperstability approach with an improved Lyapunov function. The coupling among joints and the nonlinearity in the dynamic equation are explicitly considered. The designed manipulator controller shows good tracking performance in various cases, load variation, parameter uncertainties. and time delay. Since the proposed adaptive control method requires only a small number of parameters to be estimated, the controller has a relatively simple structure compared to the other adaptive manipulator controllers. Therefore, the method used is expected to be well suited for a high performance robot controller under practical operation environments.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2424-2426
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• 2002

This paper proposes an adaptive control method of partially known system and shows its application result to control for two-wheeled WMR. The controlled system is stable in the sense of Lyapunov stability. To design a tracking controller for welding path reference, an error configuration is defined and the controller is designed to drive the error to zero as fast as desired. Moments of inertia of system are considered to be unknown system parameters. Their values are estimated using update laws in adaptive control scheme. The effectiveness of the proposed controller is shown through simulation results.