• Journal of Institute of Control, Robotics and Systems
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• v.4 no.1
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• pp.68-75
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• 1998

The Intelligent Cruise Control system, ICC, is a driver assisting system for controlling relative speed and distance between two vehicles in the same lane. The ICC may be considered as an extension of a traditional cruise control, not only keeping a fixed speed of the vehicle, but correcting the speed also to that of a slower one ahead. This paper presents a real-time self-tuning fuzzy control algorithm to develop ICC. The self-tuning fuzzy control law is adopted to reduce the effects of nonlinearities of the vehicle and various road environments. In the self-tuning algorithm an interior penalty method is applied to preserve the inherent order of membership functions and is modified as an on-line algorithm for real time application. Via simulations, the performance of the suggested control algorithm is compared with a PID and a fuzzy control without self-tuning. The suggested control algorithm is implemented on PRV III and the results of the test driving on a local road are given.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.11
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• pp.1663-1668
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• 2017

A BLDC motor with higher number of phases has several advantages, compared to the conventional three-phase BLDC motors. It can reduce the commutation torque ripple and the iron loss without increasing the voltage per phase and increase the reliability and power density. Higher number of phases increase the torque-per-ampere ratio for the same machine volume and output power by widening the electrical conduction period. In this paper, the proposed seven-phase BLDC motor drive system is made into several functional modular blocks, so that it can be easily extended to other ac motor applications: back-EMF block, hysteresis current control block, pwm inverter block, phase current block, and speed/torque control block. Also in a system of BLDC motor drive, the PI controller has been widely used in the speed controller because of the simple implementation. To obtain a good speed response in a general drive system using the PI controller, the high bandwidth of a controller is established. therefore, in this paper, a Fuzzy controller is applied to the 7-phase BLDC motor drive system in order to improve the speed control performance. The Fuzzy controller is compared with a conventional PI controller through the experiment with respect to speed dynamic responses. These experimental results show that the Fuzzy controller of the 7-phase BLDC motor drive system is superior over the conventional PI controller. The algorithm using the Fuzzy controller can improve a comfortable ride in the field of high performance 7-phase BLDC motor drive applications.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.178-182
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• 1995

In this paper, the fuzzy approximator and nonlinear inversion control scheme are considered. An adaptive nonlinear control is proposed based on the speed gradient algorithms proposed by Fradkov. This proposed control scheme is that three types of adaptive law is utilized to approximate the unknown function f by fuzzy logic system in designing the nonlinear inversion controller for the nonlinear system. In order to reduce the approximation errors, the differences of nonlinear function and fuzzy approximator, another three types of adaptive law is also introduced and the stability of proposed control scheme are proven with SG algorithm.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.2
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• pp.98-106
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• 2006

This paper proposes to position and speed control of interior Permanent magnet synchronous motor(IPMSM) drive without mechanical sensor. Also, this paper develops a adaptive fuzzy controller based fuzzy logic control for high performance of PMSM drives. In the proposed system, fuzzy control is used to implement the direct controller as well as the adaptation mechanism. A Gopinath observer is used for the mechanical state estimation of the motor. The observer was developed based on nonlinear model of IPMSM, that employs a d-q rotating reference frame attached to the rotor. A Gopinath observer is implemented to compute the speed and position feedback signal. The validity of the proposed scheme is confirmed by various response characteristics.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2464-2466
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• 2000

When linear PI controller is used in speed control of induction motor, there happen some weaks which is very difficult to find optimal control gain at time of changing speed and load. In this paper, Fuzzy system incorporated with PI controller is proposed in order to that defects. PI gain is calculated by theoretical basis and fuzzy control is translated human expert's knowledge and experiences into rules numerically. Also it modifies and compensates PI gains in realtime. As comparing the motor characteristics of proposed fuzzy-PI speed controller to PI speed controller of a Vector controlled induction motor system in the increasing load torque and speed change during start and stop, The simulation results show robust and good performance.

• Proceedings of the KIEE Conference
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• 2002.11d
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• pp.224-227
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• 2002

This paper is proposed new fuzzy controller for speed control of induction motor drive. New fuzzy controller take out appropriate amounts of accumulated control input according to fuzzily described situations in addition to the incremental control input calculated by conventional direct fuzzy controller. The structures of the proposed controller is motivated by the problems of direct fuzzy controller. Proposed controller fuzzily clear out integrated quantifies according to situation. This paper attempts to provide a thorough comparative insight into the behavior of induction motor drive with direct and new fuzzy speed controller. The validity of the comparative results is confirmed by simulation results for induction motor drive system.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.5
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• pp.338-344
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• 2004

This paper presents a sensorless speed control of a DC servo motor using a fuzzy-sliding observer in the presences of load disturbances. A fuzzy-sliding observer is proposed in order to estimate the speed of a motor rotor. First, a sliding observer is used to estimate the derivative of the armature current directly using the armature current mesured in the DC servo motor. Second, the optimal gain of the Luenberger observer is set up using the fuzzy control. Experimental results show the good performance in the DC servo motor system with the proposed fuzzy-sliding observer.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.3
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• pp.173-183
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• 1998

In this paper, an auto-tuning method for fuzzy controller's membership functions based on the neural network is presented. The neural network emulator offers the path which reforms the fuzzy controller's membership functions and fuzzy rule, and the reformed fuzzy controller uses for speed control of induction motor. Thus, in the case of motor parameter variation, the proposed method is superior to a conventional method in the respect of operation time and system performance. 32bit micro-processor DSP(TMS320C31) is used to achieve the high speed calculation of the space voltage vector PWM and to build the self-learning fuzzy control algorithm. Through computer simulation and experimental results, it is confirmed that the proposed method can provide more improved control performance than that PI controller and conventional fuzzy controller.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.217-224
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• 2005

Generally, the underwater flight vehicle (UFV) depth control system operates with the following problems: it is a multi-input multi-output (MIMO) system because the UFV contains both pitch and depth angle variables as well as multiple control planes, it requires robustness because of the possibility that it may encounter uncertainties such as parameter variations and disturbances, it requires a continuous control input because the system that has reduced power consumption and acoustic noise is more practical, and further, it has the speed dependency of controller parameters because the control forces of control planes depend on the operating speed. To solve these problems, an adaptive fuzzy sliding mode controller (AFSMC), which is based on the decomposition method using expert knowledge in the UFV depth control and utilizes a fuzzy basis function expansion (FBFE) and a proportional integral augmented sliding signal, is proposed. To verify the performance of the AFSMC, UFV depth control is performed. Simulation results show that the AFSMC solves all problems experienced in the UFV depth control system online.

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.3
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• pp.282-289
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• 2005

This paper proposes a fuzzy neural network controller based on the vector control for interior permanent magnet synchronous motor(IPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability This paper does not oかy presents speed control of IPMSM using neuro-fuzzy control(NFC) but also speed estimation using artificial neural network(ANN) 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. Thus, it is presented the theoretical analysis as well as the analysis results to verify the effectiveness of the proposed method in this paper.