• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.2
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• pp.403-410
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• 1999

A conventional PID controller has poor performance when it applied to systems with unknown deadzones. To solve this problem, this paper proposes PID controller using two layered-fuzzy logic. The structure of controller is reconstructed with fuzzy compensator and fuzzy tuner on the conventional PID controller. Our proposed control scheme shows superior transient and steady-state performance compared to conventional PID controller. The scheme is robust to variations in deadzone nonlinearities as well as the steady-state gain of the plant. The performance of the developed controller is verified through simulation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1998.05a
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• pp.96-101
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• 1998

많은 분야에서 널리 사용되고 있는 PID 제어기의 형태는 오차를 갖는 폐루프 시스템으로 구성되며, PID 제어기는 비례, 적분, 미분 제어기로 나누어진다. PID 제어기의 형태가 여러 가지로 제안되고 있지만 보다 중요한 것은 PID 제어기의 파라미터들을 어떻게 적절히 정하느냐 하는 파라미터 조정 문제이다. 실제로 산업 현장에 설치되어 있는 PID 제어기는 대부분 숙련된 기술자에 의해 수동 조작에 의한 시행 착오(trial and error) 법으로 동조되고 있다. 이 경우는 많은 노력과 시간이 소비되고, 외란(disturbance)이 첨가될 경우 적절히 동조된다는 보장도 없다. 본 논문에서는 이러한 문제를 해결하고자 신경회로망을 이용하여 PID 제어기의 파라미터를 동조하는 제어 방법을 제안하였다. 단일 뉴런으로 구성하여 구조가 간단하고, 학습에 의한 성능 개선이 가능하다. 오차 역전파(Error Back-Propagation) 알고리즘에 의하여 PID 파라미터가 되는 가중치를 자동 동조하는 방법이다. 제안한 방식의 유용성을 보이기 위해 DC 서보 모터와 비선형 시스템인 단일 관절 매니퓰레이터를 대상으로 시뮬레이션을 하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.3
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• pp.536-544
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• 2011

In this paper, a controller for two wheeled inverted pendulum type robot is designed to have more stable balancing capability than conventional controllers. Traditional PID control structure is chosen for the two wheeled inverted pendulum type robot, and proper gains for the controller are obtained for specified user's weights using trial-and-error methods. Next a neural network is employed to generate PID controller gains for more stable control performance when the user's weight is arbitrarily selected. Through simulation studies we find that the designed controller using the neural network is superior to the conventional PID controller.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.6
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• pp.15-22
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• 2005

In this paper, we propose a PID-PD controller and its tuning method to be modified form of PID controller that consist of the affine set of PID and PI-PD controller by analyzing relation between these controllers. The proposed tuning method controls the closed-loop system to locate between the step responses of system controlled by PID and PI-PD controller. The controller is designed by the optimum tuning method to minimize the proposed specific cost functions. Its effectiveness is examined by the case studies and their analysis.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.127-134
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• 2005

This paper proposes a nonlinear fuzzy PID controller with variable parameters to improve slow rising time and divergence occurred by limited input spaces and a resultant limited control input during fuzzification in a fuzzy PID controller with fixed parameters, and describes the design principle and tracking performance of a proposed fuzzy PID controller. The parameters of a proposed controller are adjusted by the stability conditions derived from 'small gain theorem' and satisfy the BIBO stability of overall control system.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.3
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• pp.186-192
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• 2009

PID controllers are simple in structure and easy for implementation. However, they may produce large overshoots and over-oscillatory responses. Combining PID control with other control techniques often results in advanced hybrid schemes that are able to improve pure PID controllers. This paper proposes hybrid controller for position control system of servo motor. The proposed controller is composed of a subcontroller and a parallel PID controller. The subcontroller improves the transient system performance while the PID controller is mainly responsible for the steady-state system performance. A very promising advantage of this hybrid scheme, in terms of controller synthesis, is that the subcontrollers and controller components can be designed separately. Systematic design methods for various controller components are developed. The proposed hybrid scheme is applied to a DC motor position servo system. The effectiveness of the proposed controller is verified through the computer simulation results.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.68-68
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• 2000

This paper presents a fuzzy modified PID controller that uses linear fuzzy inference method. In this structure, the proportional and derivative gains vary with the output of the system under control. 2-input PD type fuzzy controller is designed to obtain the varying gains. The proposed fuzzy PID structure maintains the same performance as the general-purpose linear PID controller, and enhances the tracking performance over a wide range of input. Numerical simulations and experimental results show the effectiveness of the fuzzy PID controller in comparison with the conventional PID controller.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.8
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• pp.1811-1817
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• 2014

In this paper, a PID controller with interpolated gains by use of neural networks is proposed for the formation control problem that following robots track a leading robot with constant distances and angles when there are changes in the mass of the following robot. The whole control system is composed of a kinematic controller and a dynamic controller considering the robot dynamics. The dynamic controller is the PID controller with varying gains, and the proper gains are obtained for some representative masses of the follower robot by the genetic algorithm. Neural networks is trained using the genetic algorithm with the gain data obtained in the previous step. The trained neural network determines optimal PID gains for a random mass of following robot. Simulation studies show that for arbitrary masses of the tracking robot, the PID controller with interpolated gains by the trained neural network has better tracking performance than that of the PID controller with fixed gains.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.5
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• pp.56-61
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• 2000

Robust control for DC motor is needed according to the highest precision of industrial automation. However, when a motor control system with PID controller has an effect of load disturbance, it is very difficult to guarantee the robustness of control systems.In this paper, PID-Expert hybrid control method for motor control system as a compensation method solving this problem is presented. If PID control system is stable, the Expert controller is idle. if the error hits the boundary of the constraint, the Expert controller begins operation to force the error back to the constraint set. The disturbance effect decrease remarkably, robust speed control of DC motor using PID-Expert Hybrid controller is demonstrated by the simulation.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.699-703
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• 1991

A magnetic levitation system with hybrid magnets, which is composed of permanent magnets and electromagnets, consumes less power than the conventional attraction type system. In this paper, we propose PID controller and PID-Fuzzy controller for hybrid magnet. We first present "constant gap" control technology with PID controller. Secondly, "zero power" control technology with PID-Fuzzy hybrid controller is presented.roller is presented.