• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.1871-1880
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• 2011

In this paper, a controller for two wheeled inverted pendulum robot, i.e., Segway type robot that is a convenient and easily handled vehicle is designed to have more stable balancing and faster velocity control compared to the conventional method. First, a widely used PID control structure is applied to the two wheeled inverted pendulum robot and proper PID control gains for some specified weights of users are obtained to get accurate balancing and velocity control by use of experimental trial-and-error method. Next, neural network is employed to generate appropriate PID control gains for arbitrarily selected weight. Here the PID gains based on the trial-and-error method are used as training data. Simulation study has been carried out to find that the performance of the designed controller using the neural network is more excellent than the conventional PID controller in terms of faster balancing and velocity control.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.12 no.4
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• pp.70-74
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• 1998

Robust control for DC motor is needed according to the highest precision of industrial automation. However, when a motor control system with PID contoller has an effect of load disturbance, it is very difficult to guarantee the robustness of control system. In this paper, PID-supervision hybrid control methods for motor control system (without the supervisory controller) is stable in the sense that the error is inside the constraint set, the supervisory control is idle. If the error hits the boundary of the constraint, the supervisory controller beings operation to force the error back to the constraint set. We prove that the PID-supervision hybrid control system is globally stable in the sense that the error is guaranteed to be within the tolerance limits specified by the system designer.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.1
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• pp.1-10
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• 2003

This paper is concerned with the fuzzy control scheme and PID controller for the vibration suppression control of a cantilever beam equipped with a laser sensor and an electromagnetic actuator. The PID controller is being widely used in industrial applications. However, it is difficult to determine the appropriate PID gains in nonlinear systems and systems with time variant characteristic and so on. In this paper, we design the fuzzy based PID controller of which output gains are adjusted automatically and the designed controller is applied to active vibration control of a cantilever beam using electromagnetic actuator with strong nonlinearity. The tuning PID parameters of proposed controller are determined by using Fuzzy algorithm. Effectiveness and performance of the designed controller are verified by both simulation and experiment results. Experimental results demonstrate that better control performance can be achieved in comparison with the PID cotroller.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.503-509
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• 2014

In this paper, a PID controller with adaptive neural network compensator is proposed to control the formations of mobile robot. The control system is composed of a kinematic controller based on the leader-following robot and dynamic controller for considering the dynamics of the mobile robot. The dynamic controller is constituted by a PID controller and the adaptive neural network compensator for improving the performance and compensating the change in dynamic characteristics. Simulation results show the performance of the PID controller and the neural network compensator for the circular trajectory and linear trajectory. And it is verified that by improving the performance of a PID controller via the adaptive neural network compensator, the following robot's tracking performance is improved.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.120-125
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• 2005

In this paper, We propose the fuzzy controller for the gain tuning of PID controller The proposed controller doesn't use the crisp output error and rule tables though with a fuzzy inference process in forward fuzzifier, New Fuzzy PID Controller assigns relations and ranges of two variables of PID gain parameters. These new gain parameters are calculated by the fuzzy inference with max-min ranges of Kp and Kd. The Ki parameter is computed automatically between Kp and Kd parameter Is calculated by Ziegler-Nickels tuning rules. Finally we experimented the propose controller by the hydraulic servo motor control system. We can obtained desired results through the good control characteristics.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.1
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• pp.52-58
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• 2005

Among various modern control theories, PID control has been well used for several decades. PID algorithms need some tuning methods which are used for selecting PID parameters. But in some cases various kinds of performance indices are used instead of well-known tuning rules, and so variable type of performance index must be tested so that controllers, output characteristics and disturbance rejection property meet some specifications. In this paper, linear conbinational type of performance index using error signal, time, control input and robustness is used to the PID control of air conditioning system. By use of the 2 DOF PID parmeters minimizing perfromacne index controllers, output characteristics and robustness properties are analyzed. Simulations are done by use of MATLAB with Simulink.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.88-95
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• 2006

PID controllers, which have been widely used in industry, have a simple structure and robustness to modeling error. But They we difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose a nonlinear adaptive PID controller based on a cell-mediated immune response and a gradient descent learning. This algorithm has a simple structure and robustness to system parameters variation. To verify performances of the proposed nonlinear adaptive PID controller, the speed control of nonlinear DC motor is performed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system parameters variation.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.5
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• pp.29-38
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• 1998

This paper proposes the neural network self-tuning PID controller for the load frequency control of 2- areas power system, namely, the prompt convergence of frequency and tie-line power flow deviation. The neural network applied to computer simulation consists of neurons of two inputs, ten hiddens and tliree outputs layer. Neurons of two inputs layer receive the error and its change rate of the system and cutputs layer consists of three neurons for the parameters of the PID controller. The simulation results shows that the proposed neural network self-tuning PID controller is superior to conventional control t~:chniques(Optimal, PID) in dynamic response and control performance.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.957-966
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• 2023

In this paper, we propose a new real-time adaptive PID temperature control technique. This is a technique that prevents overshoot by introducing a model that represents the control object. To prevent excessive integration that causes overshoot, integral control adjusts the integral gain to track the heat loss of the model in real time. In the conventional PID control, the integration was dependent on proportional control and the gain was fixed to a constant. As a result, applying two gains that mismatch each other could cause excessive overshoot. However, the proposed adaptive control actively eliminates overshoot so that the integral control amount does not always exceed the heat loss. The cause of overshoot in PID control is integration. Basically, proportional control does not cause overshoot. Therefore, according to the proposed technique, adaptive PID control without the need for tuning experiments can be realized.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.99-100
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• 2016

드론이나 이동형 촬영장비에 장착된 카메라로부터 깨끗하고 안정된 영상을 획득하기 위해서는 짐벌시스템의 안정화기 설계가 필요하다. 짐벌시스템은 카메라 모듈을 지지하는 구조와 외부로 부터의 진동을 차단하면서 정확한 각도를 추종하는 안정화기로 구성된다. 이동형 촬영장비나, 비행중인 드론에는 매우 다양한 주파수 성분의 진동이 발생되는데, 이러한 진동을 제어하기 위하여 6자유도 운동방정식을 유도하고, 이 중에서 본 논문에서는 일반적으로 rolling, pitching, yawing 운동에 대해서는 PID 제어기를 사용하여 안정화를 제어하기만, 카메라종류나 짐벌시스템 구조가 바뀔 때 마다 PID 파라미터를 변경해야 되는 경우가 빈번하다. 본 논문에서는 이런 문제점을 개선하기 새로이 제기된 제어 기법인 지적 PID(intelligent PID) 제어를 통하여 진동제어를 수행하여 짐벌시스템의 안정화를 위한 제어기법을 제안하고자 한다.