• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.5
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• pp.315-322
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• 2004

A direct adaptive state-feedback controller for highly nonlinear systems is proposed. This paper considers uncertain or ill-defined nonaffine nonlinear systems and employs a static fuzzy logic system (FLS). The employed FLS estimates. and adaptively cancels an unknown plant nonlinearity using its proved universal approximation property. A control law and adaptive laws for unknown fuzzy parameters and bounding constant are established so that the whole closed-loop system is stable in the sense of Lyapunov. The tracking error is guaranteed to be uniformly asymptotically stable rather than uniformly ultimately bounded with the aid of an additional robustifying control term. No a priori knowledge of an upper bound on an lumped uncertainty is required.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.402-408
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• 2017

This paper deals with a robust ${\mathfrak{H}}_{\infty}$ controller design problem for waypoints tracking of large displacement unmanned underwater vehicles (LDUUVs) in Takagi-Sugeno fuzzy form. The LDUUV model uses a rudder to control its horizontal motion. We determine the order of waypoints based on their priorities and consider only surge force. A fuzzy controller in state-feedback form is taken and its design condition of is represented in terms of linear matrix inequalities. A numerical simulation is included to show the effectiveness of the theoretical development.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.10
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• pp.47-57
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• 2006

The paper is proposed maximum torque control of SynRM drive using adaptive teaming mechanism-fuzzy neural network(ALM-FNN) controller and artificial neural network(ANN). The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $^i{_d}$ for maximum torque operation is derived. The proposed control algorithm is applied to SynRM drive system controlled ALM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verify the effectiveness of the ALM-FNN and ANN controller.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1271-1276
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• 1990

The paper describes and presents the experimental results of a fuzzy control scheme applied to an electric power system. The fuzzy control scheme which was recently proposed by T. Hiyama and T. Nakano [1] is implemented on a digital processor with A/D and D/A converters and is tested on our laboratory system. The results show that the proposed fuzzy controller with optimal settings of its parameters gives better performance than the PSS (Power System Stabilizer) optimally adjusted. The problems encountered throughout the experiment are also discussed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.274-279
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• 2005

For high-speed fuzzy control systems, an important problem is the improvement of speed for the fuzzy inference, particularly in the consequent part and the defuzzification stage. This paper introduces an algorithm to map real values of the fuzzy membership functions in the consequent part onto an integer grid, as well as a method of eliminating the unnecessary operations of the zero items in the defuzzification stage, allowing a center of gravity method to be implemented with only integer additions and one integer division. A VHDL implementation of the system is presented. The proposed system shows approximately an order of magnitude increase in speed as compared with conventional methods while introducing only a minimal error and can be used in many fuzzy controller applications.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.458-460
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• 1998

The drum level control is initiated by 1-element manual control, and then the control mode is changed to 1-element automatic control mode. Finally, the drum level control is changed to 3-element automatic control mode by the logic based on pre-defined threshold of main steam flow. In terms of plant automation, the automatic 1-element control mode is required from the start-up of boiler. In this paper, the fuzzy controller is adopted for automatic 1-element control of drum level from start-up. It is suggested that the fuzzy controller is used in 1-element control, and the fuzzy-PI cascade controller is used in 3-element control. Finally, the validity of suggested control scheme is shown via simulation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.423-426
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• 2005

In this paper, we proposed a PID tuning algorithm by the fuzzy set theory to improve the performance of the PID controller. The new tuning algorithm for the PID controller has the initial value of parameter Kp, $\tau_{I}$, $\tau_{D}$. by the Ziegler-Nichols formula that uses the ultimate gain and ultimate period from a relay tuning experiment. We will get the error and the error rate of plant output corresponding to the initial value of parameter and fnd the new proportion gain(Kp) and the integral time ($\tau_{I}$) from fuzzy tuner by the error and error rate of plant oueut as a membership function of fuzzy theory. This fuzzy auto tuning algorithm for PID controller considerably reduced the overshoot and rise time as compared to any other PID controller tuning algorithms. And in real parametric uncertainty systems, it constitutes an appreciable improvement of performance. The significant property of this algorithm is shown by simulation

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.12
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• pp.1101-1105
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• 2012

This study proposes a method for improvement of PD type fuzzy controller. The method includes self tuner using gradient algorithm that is one of the optimization algorithms. The proposed controller improves simple Takagi-Sugeno type FLC (Fuzzy Logic Control) system. The simple Takagi-Sugeno type FLC system changes nonlinear characteristic to linear parameters of consequent membership function. The simple FLC system could control the system by calibrating parameter of consequent membership function that changes the system response. While the determination on parameter of the simple FLC system works well only partially, the proposed method is needed to determine parameters that work for overall response. The simple FLC system doesn't predict the response characteristics. While the simple FLC system works just like proportional part of PID, our system includes derivative part to predict the next response. The proposed controller is constructed with P part and D part FLC system that characteristic parameter on system response is changed by self tuner for effective response. Since the proposed controller doesn't include integral part, it can't eliminate steady state error. So we include a gain to eliminate the steady state error.

• International Journal of Precision Engineering and Manufacturing
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• v.3 no.1
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• pp.66-75
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• 2002

The crane operation used fur transporting heavy loads causes a swinging motion with the loads due to the crane\`s acceleration and deceleration. This sway causes the suspension ropes to leave their grooves and can cause serious damage. Ideally, the purpose of a crane system is to transport loads to a goal position as soon as possible without any oscillation of the rope. Currently, cranes are generally operated based on expert knowledge alone, accordingly, the development of a satisfactory control method that can efficiently suppress object sway during transport is essential. The dynamic behavior of a crane shows nonlinear characteristics. When the length of the rope is changed, a crane becomes a time-varying system thus the design of an anti-sway controller is very difficult. In this paper, a nonlinear dynamic model is derived for an industrial overhead crane whose girder, trolley, and hoister move simultaneously. Furthermore, a fuzzy logic controller, based on expert experiments during acceleration, constant velocity, deceleration, and stop position periods is proposed to suppress the swing motion and control the position of the crane. Computer simulation is then used to test the performance of the fuzzy controller with the nonlinear crane model.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.8
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• pp.193-202
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• 1999

Crane operation for transporting heavy loads causes swinging motion at the loads due to crane's acceleration and deceleration. This sway causes the suspension ropes to leave their grooves and leads to possibility of serious damages. So, this swing of the objects is a serious problem and the goal of crane system is transporting to a goal position as soon as possible without the oscillation of the rope. Generally crane is operated by expert's knowledge. Therefore, a satisfactory control method to supress object sway during transport is indispensible. The dynamic behavior of the crane shows nonlinear characteristics. when the length of the rope is changed the crane is time varying system and the design of anti-sway controller is very difficult. In this paper, the nonlinear dynamic model for the industrial overhead crane whose girder, trolley and hoister move simultaneously is derived. and the Fuzzy logic controller based on the expert experiments during acceleration, constant velocity, deceleration and stop position period is proposed to supress the swing motion and control the position of the crane. The performance of the fuzzy controller for the nonlinear crane model is simulated on the personal computer.