• Journal of Institute of Control, Robotics and Systems
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• v.16 no.2
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• pp.120-125
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• 2010

This paper proposes an intelligent PID/Fuzzy control system for two humanoid robots to transport objects stably. When a robot transports an object while walking, a whole body system of a robot may not be stable due to vibration or external factors from a different departure speed error and a body movement of walking robots. Therefore, it is necessary to measure the horizontal and vertical locations and speeds of object, then calibrate the difference of departure speed between robots with PID/Fuzzy control. The results of simulation with two robots indicated that a proposed controller makes robots to transport an object stably.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.71-74
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• 2002

본 논문에서는 유전알고리즘(GA)을 이용한 PID계수 자동조정기법에 관한 DC 서보 모터 속도 제어기 설계를 목적으로 한다. DC 서보 모터는 수많은 제어용 기계나 로봇 등의 응용분야에 사용되고 있고 이러한 분야에서 제어기 파라미터들의 선택이 사용자의 전문적인 지식을 요구하게 된다. 따라서 일반적인 공정 기술자들은 시행착오에 의해 제어기 파라미터들을 계속적으로 반복 조절해 나가야 한다. 이와 같이 동적 시스템의 변화나 외란에 대하여 파라미터 계수를 자동 조정해야 할 경우 유전알고리즘을 사용함으로써 보다 정밀하고 최적화된 파라미터 계수값을 추종함에 따라 그 성능을 높일 수 있다. 본 논문에서는 DC 모터의 동특성을 분석하여 얻은 동특성 모델링으로부터 응답 특성이 빠르고 속도 정밀도가 향상된 구동제어가 가능한 제어기를 설계하고 이를 PID제어기와 비교 평가하였다.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.1
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• pp.8-17
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• 2002

This paper suggests that the immune algorithm can effectively be used in tuning of a PID controller. The artificial immune network always has a new parallel decentralized processing mechanism for various situations, since antibodies communicate to each other among different species of antibodies/B-cells through the stimulation and suppression chains among antibodies that form a large-scaled network. In addition to that, the structure of the network is not fixed, but varies continuously. That is, the artificial immune network flexibly self-organizes according to dynamic changes of external environment (meta-dynamics function). However, up to the present time, models based on the conventional crisp approach have been used to describe dynamic model relationship between antibody and antigen. Therefore, there are some problems with a less flexible result to the external behavior. On the other hand, a number of tuning technologies have been considered for the tuning of a PID controller. As a less common method, the fuzzy and neural network or its combined techniques are applied. However, in the case of the latter, yet, it is not applied in the practical field, in the former, a higher experience and technology is required during tuning procedure. In addition to that, tuning performance cannot be guaranteed with regards to a plant with non-linear characteristics or many kinds of disturbances. Along with these, this paper used immune algorithm in order that a PID controller can be more adaptable controlled against the external condition, including moise or disturbance of plant. Parameters P, I, D encoded in antibody randomly are allocated during selection processes to obtain an optimal gain required for plant. The result of study shows the artificial immune can effectively be used to tune, since it can more fit modes or parameters of the PID controller than that of the conventional tuning methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.239-245
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• 2012

This paper proposes a novel optimum design method for the PID controller of magnetic levitation-based Rail-Guided Vehicle(RGV) by a genetic algorithm using clone selection method and a new performance index function with performances of both time and frequency domain. Generally, since an attraction type levitation system is intrinsically unstable and requires a delicate controller that is designed considering overshoot and settling time, it is difficult to completely satisfy the desired performance through the methods designed by conventional performance indexes. In the paper, the conventional performance indexes are analyzed and then a new performance index for Maglev-based RGV is proposed. Also, an advanced genetic algorithm which is designed using clonal selection algorithm for performance improvement is proposed. To verify the proposed algorithm and the performance index, we compare the proposed method with a simple genetic algorithm and particle swarm optimization. The simulation results show that the proposed method is more effective than conventional optimization methods.

• Journal of KIEE
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• v.10 no.1
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• pp.16-22
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• 2000

The Main role of the gas turbine lies in the utilization of waste heat which may be found in exhaust gases from the gas turbine or at some other points of the process to produce additional electricity. Up to date, the PID controller has been used to operate under such difficult conditions, but since the gain of PID controller manually experience. In this paper parameter separation type 2-DOF PID controllers are proposed based on the gas turbine control system. Gas turbine transfer function is achieved from operation data of Gun-san gas turbine and Tuning algorithms of parameter separation type 2-DOF PID controller is ANFIS. Results represents satisfactory response.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.135-138
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• 1997

In this paper, Tuning method of the parameter P.I.D of the 2DOG-PID controller for having a required response to the disturbance and the setpoint is studied by the neural network. This algorithms is simulated in the level control of the steam generator and the flow control system, and resulting represents than the conventional PID controller.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.2
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• pp.136-144
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• 2014

The existing conventional motion controller does not perform well in the presence of nonlinear properties, uncertain factors, and servo lag phenomena of industrial actuators. Hence, a feasible and effective fuzzy self-tuning proportional integral derivative (PID) and feed-forward control scheme is introduced to overcome these problems. In this design, a fuzzy tuner is used to tune the PID parameters resulting in the rejection of the disturbance, which achieves better performance. Then, both velocity and acceleration feed-forward units are added to considerably reduce the tracking error due to servo lag. To verify the capability and effectiveness of the proposed control scheme, the hardware configuration includes digital signal processing (DSP) which plays the main role, dual-port RAM (DPRAM) to guarantee rapid and reliable communication with the host, field-programmable gate array (FPGA) to handle the task of the address decoder and receive the feed-back encoder signal, and several peripheral logic circuits. The results from the experiments show that the proposed motion controller has a smooth profile, with high tracking precision and real-time performance, which are applicable in various manufacturing fields.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.2
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• pp.113-118
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• 2010

This paper proposed an ECAM (Electronic cam) control system which has simple and general structure. The proposed cam controller adopted the linear and polynomial curve-fitting method to generates a smooth cam profile curve function. Smooth motion trajectory of master actuator guarantees the good performance of slave motion and has an important effect on the interpolation quality of ECAM. The auto-tuning PID velocity controller was applied to overcome the uncertainties in ECAM, and the gains of the controller are updated continuously to ensure the consistency of system performance under varying working conditions. The robustness of system against the varying load torque disturbances and noises is guaranteed by using the load torque disturbance observer to suppress the disturbance on master actuator. The velocity compensator was applied to compensate the degradation of performance of slave motion caused from the varying driving speed of master motion. The stability and validity of the proposed ECAM control system was verified by simulation results.

• Journal of Mechanical Science and Technology
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• v.18 no.7
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• pp.1074-1085
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• 2004

There are many intermediate web guides in cold rolling mills process such as CRM (cold rolling mill), CGL (continuous galvanizing line), EGL (electrical galvanizing line) and so on. The main functions of the web guides are to adjust the center line of the web (strip) to the center line of the steel process. So they are called CPC (center position control). Rapid process speed cause large deviation between the center position of the strip and the process line. Too much deviation is not desirable. So the difference between the center position of the strip and the process line should be compensated. In general, the center position control of the web is obtained by the hydraulic driver and electrical controller. In this paper, we propose modelling and several controller designs for web-guide systems. We model the web and guide by using geometrical relations of the guide ignored the mass and stiffness of the web. To control the systems, we propose PID controllers with their gains tuned by the Ziegler-Nichols method, the H$\_$$\infty$/ controller model-matching method, and the coefficient diagram method (CDM). CDM is modified for high order systems. The results are verified by computer simulations.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.699-701
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• 2004

This paper proposes the algorithm of servo- writing based on feedback error learning neural networks. The controller consists of feedback controller using PID and feedforward controller using gaussian radial basis function network. Because the RBFNs are trained by on-line rule, the controller has adaptation capability. The performance of the proposed controller is compared to that of conventional PID controller. Proposed algorithm shows better performance than PID controller.