• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.531-533
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• 1998

This paper proposes the method that estimate optimally the parameters of Fuzzy-PID controller using genetic Algorithm. The controller is desined with the proposed method, and then is applied to 3-phase induction motor. Simulation results show that proposed method is more excellent then FPID and PID.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.598-603
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• 2004

An optical head actuator of an optical disk drive consists of two servo mechanisms for the focusing and the tracking to acquire data from disk. As the rotational speed of the disk grows, the utilized lag-lead-lead compensator has known to be above its ability for precisely controlling the optical head actuator. To overcome the difficulty, this paper propose a new controller design method for optical head actuator based fuzzy proportional-integral-derivative (PID) control and the genetic algorithm(GA). It employs a two-stage control structure with a fuzzy PI and a fuzzy PD control and is optimized by the GA to yield the suboptimal fuzzy PID control performance. It is shown the feasibility of the proposed method through a numerical tracking actuator simulation.

• Proceedings of the KIEE Conference
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• 1992.07b
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• pp.1242-1244
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• 1992

This Paper deals with a Auto-Tuning Fuzzy PID Controller used in real time and its application for induction motor. The control strategy of the controller is able to develop and improve automatically. The new Auto-Tuning Fuzzy PID Control algorithm which modifies the fuzzy control decision table is presented in this paper. It can automatically refine an initial approximate set of fuzzy rules. The possibility of applying fuzzy algorithms in faster response, and more accurate was compared with other industrial processes, such as AC Motor driver. The performance of Proportional_Integral Derivative(PID) control and this fuzzy controllers is compared in terms of steady_state error, settling time, and response time. And then, Limitations of fuzzy control algorithms are also described.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.11
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• pp.599-609
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• 2000

The new design methodology of a hybrid fuzzy controller by means of the genetic algorithms is presented. First, a hybrid fuzzy controller(HFC) related to the optimal estimation of control parameters is proposed. The control input for the system in the HFC combined PID controller with fuzzy controller is a convex combination of the FLC's output and PID's output by a fuzzy variable, namely, membership function of weighting coefficient. Second, an auto-tuning algorithms utilizing the simplified reasoning method and genetic algorithms is presented to automatically improve the performance of hybrid fuzzy controller. Especially, in order to auto-tune scaling factors and PID parameters of HFC using GA, three kinds of estimation modes such as basic, contraction, and expansion mode are effectively utilized. The proposed HFC is evaluated and discussed to show applicability and superiority with the and of three representative processes.

• Journal of Electrical Engineering and Technology
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• v.7 no.5
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• pp.724-729
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• 2012

A fuzzy PID controller design method is proposed for precise robust control of DC-DC buck converters. The PID parameters are determined reflecting on the common control engineering knowledge that transient performances can be improved if the P and I gains are big and the D gain is small at the beginning. Different from the previous fuzzy control design methods, the proposed method requires no defuzzification module and the global stability of the proposed fuzzy control system can be guaranteed. The proposed fuzzy PID controller is implemented by using a low-cost 8-bit microcontroller, and simulation and experimental results are given to demonstrate the effectiveness of the proposed method.

• Journal of Advanced Marine Engineering and Technology
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• v.26 no.6
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• pp.638-645
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• 2002

This paper presents a scheme for integrating PID control, gain scheduling and emerging techniques in the field of artificial intelligence, such as fuzzy logic and genetic algorithms for the speed control of a marine diesel engine. At first, local PID controllers are designed based on a local model obtained at each speed mode, whose parameters are optimally tuned using a real-coded genetic algorithm. Then, fuzzy "if-then" rules combine the local controllers as a consequence part to implement fuzzy gain scheduling. To demonstrate the performance of the proposed fuzzy PID controller on overall operating conditions, a set of simulation works on B'||'&'||'W's 4L80MC diesel engine are carried out.t.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.207-209
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• 1995

The PID controller is widely used due to its fast response and robustness. But its performance is not so good compared with modem controllers such as adaptive, robust, fuzzy, neural controller. Therefore, it is natural to replace PID controller by modem controllers. But, the problem is that modem controller can not be easily applied to the real time process. Hence, this paper proposes such a structure that PID controller and Self-Learning Fuzzy Controller(SLFC) are in parallel with each other. The parameter of SLFC will be updated by gradient descent method using neuro - identifier. The usefulness of this hybrid controller will be proved by simulation results.

• Journal of Advanced Navigation Technology
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• v.17 no.1
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• pp.107-114
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• 2013

In this paper, we propose controller to control the acceleration of unmanned aircraft turbojet engine. The high-gain observer to estimate the rotational speed of compressor is used, and the turbojet engine controller applying fuzzy heuristic techniques and PID control algorithm are designed. fuzzy PID controller produces the flow control input to prevent the surge and flame-out phenomena at the acceleration and deceleration of the turbojet engine. The standard acceleration is set and the fuel flow control is defined by the fuzzy heuristic. Computer simulations are performed using MATLAB in order to verify the performance of the proposed controller.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.3
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• pp.218-226
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• 2003

Due to the friction characteristics of pump, cylinder packing and passenger car, in the elevation system actuated with hydraulic inverter, there exist dead zones. which cannot be controlled by a PID controller. To overcome the drawbacks, in this paper, we propose a new hybrid fuzzy-sliding mode control scheme, which controls the controller output between a sliding mode control output and a PID control output by fuzzy control method. The proposed hybrid control scheme achieves an improved control performance by using both controllers. We first propose a design method of the hybrid controller far a hydraulic system controlled by inverters, then propose a design method of a hybrid fuzzy-sliding mode centre] scheme. The effectiveness of the proposed control scheme is shown by simulation results, in which the proposed hybrid control method yields better control performance then the PID controlled scheme, not only in the zero-crossing speed region but also in the overall control region including steady-state region.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.1
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• pp.55-64
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• 2002

Due to the friction characteristics of cylinders and the rail of a passenger car, in the system actuated with hydraulic systems, there exist dead zones, which can not be controlled by a PID controller. In this paper, the friction characteristics of a cylinder is examined, which may cause the abrupt increase of the acceleration in the zero-crossing speed region. To overcome the drawbacks of a PID controlled hydraulic system, a zooming fuzzy logic controller is designed and finally an improved hybrid controller is Proposed. The proposed controller is composed of the PID controller and the zooming fuzzy controller. The effectiveness of the proposed control scheme is shown by simulation and experimental results, In which the proposed hybrid control method yields good control performance not only in the zero-crossing speed region but also In the overall control region including steady-state region.