• Journal of Electrical Engineering and Technology
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• 제13권1호
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• pp.460-467
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• 2018

Metaheuristic optimization approach has become the new framework for control synthesis. The main purposes of the control design are command (input) tracking and load (disturbance) regulating. This article proposes an optimal proportional-integral-derivative (PID) controller design for the DC motor speed control system with tracking and regulating constrained optimization by using the cuckoo search (CS), one of the most efficient population-based metaheuristic optimization techniques. The sum-squared error between the referent input and the controlled output is set as the objective function to be minimized. The rise time, the maximum overshoot, settling time and steady-state error are set as inequality constraints for tracking purpose, while the regulating time and the maximum overshoot of load regulation are set as inequality constraints for regulating purpose. Results obtained by the CS will be compared with those obtained by the conventional design method named Ziegler-Nichols (Z-N) tuning rules. From simulation results, it was found that the Z-N provides an impractical PID controller with very high gains, whereas the CS gives an optimal PID controller for DC motor speed control system satisfying the preset tracking and regulating constraints. In addition, the simulation results are confirmed by the experimental ones from the DC motor speed control system developed by analog technology.

• 한국조명전기설비학회지:조명전기설비
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• 제6권4호
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• pp.60-68
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• 1992

In this paper, an implementation approach of Fuzzy Position Controller for DC servo motor which requires the faster and more accurate dynamics is presented. Fuzzy position controller implemented with 80286 microprocessor and DT 2801 board consists of an adjustment routine of optimal scale factors and a Fuzzy inference routine of optimal control signals. Comparison to conventional PD controllers, the control performances of proposed Fuzzy controller such as reaching time, overshoot, and disturbance adaptability are substantially improved.

• 융합정보논문지
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• 제11권2호
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• pp.124-129
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• 2021

본 논문에서는 절대 안정도를 보장하는 최적의 제어기 설계에 대해 제안하였다. 논문의 적용 순서는 지연시간의 포함여부를 판단하고, 지연시간이 포함되었을 경우 Pade 근사법을 통해서 지연시간을 근사화 한다. 그 다음 공정모델과 제어기 전달함수에 대한 개루프 전달함수를 구하며, Routh-Hurwitz 판별법에 의해서 절대 안정도 구간을 계산한다. 마지막 단계에서는 앞 단계에서 구한 구간을 활용하여 유전자 알고리즘으로 최적의 PID 제어파라미터 값을 구한다. 그 결과 제안 된 방법은 안정성이 보장되며, 최적의 제어기를 설계하여 기존의 방법보다 성능 지표에서 우월함을 확인하였다. 향후 지연시간에 대한 보상방법이 연구된다면 더욱 좋은 성능지표를 얻을 것으로 판단된다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.358-363
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• 2003

Optimal tuning plays an important role in operations or tuning of the complex process such as the main steam temperature of the thermal power plant. However, it is very difficult to maintain the steam temperature of power plant using conventional optimization methods, since these processes have the time delay and the change of the dynamic characteristics in the reheater. Up to the present time, the Pm controller has been used. However, it is not easy to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error. This paper suggests immune algorithm based tuning technique for PID Controller on steam temperature process with long dead time and its results are compared with genetic algorithm based tuning technique.

• 제어로봇시스템학회논문지
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• 제12권5호
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• pp.425-430
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• 2006

To meet an increasing demand for high performance in gun dynamic plant, both a precise and a fast response positioning are strongly required for the gun servo system. A mode switching control(MSC) scheme, which includes a fine stabilizing controller, fast positioning one and a switching function, is widely used to meet this requirement. Stabilization is performed through PID controller, while a time optimal control method is used for target designation. In this paper, a modified PTOS(Proximate Time Optimal Servomechanism) algorithm is derived so as to accommodate the damping term in the gun plant model. Also, applying a mode switching strategy, the bumpless transfer is made possible when the controller switches from PTOS to PID. To show the effectiveness of the overall control system, simulation results are given including the gun dynamics.

• 한국생산제조학회지
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• 제20권5호
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• pp.589-597
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• 2011

In this paper, optimal tuning of a cross-coupled controller linked with the feedforward controller and the disturbance observer is studied to improve contouring and tracking accuracy as well as robustness against disturbance. Previously developed integrated design and optimal tuning methods are applied for developing the robust tuning method. Strict mathematical modeling of the multivariable system is formulated as a state-space equation. Identification processes of the servomechanism are conducted for mechanical servo models. An optimal tuning problem to minimize both the contour error and settling time is formulated as a nonlinear constrained optimization problem including the relevant controller parameters of the servo control system. Constraints such as relative stability, robust stability and overshoot, etc. are considered for the optimization. To verify the effectiveness of the proposed optimal tuning procedure, linear and circular motion experiments are performed on the xy-table. Experimental results confirm the control performance and robustness despite the variation of parameters of the mechanical subsystems.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.225-228
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• 2002

When the fuzzy logic controller (FLC), which is designed based on the plant model, is applied to the real control system, satisfactory control performance may not be attained due to modeling errors from the plant model. In such cases, the control parameters of the controller must be adjusted to enhance control performance. Until now, the trial and error method has been used, consuming much time and effort. To resolve such problem, response surface methodology (RSM), a new method of adjusting the control parameters of the controller, is suggested. This method is more systematic than the previous trial and error method, and thus optimal solutions can be provided with less tuning. First, the initial values of the control parameters were determined through the plant model and the optimization algorithm. Then, designed experiments were performed in the region around the initial values, determining the optimal values of the control parameters which satisfy both the rise time and overshoot simultaneously.

• Journal of Mechanical Science and Technology
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• 제17권1호
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• pp.40-47
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• 2003

In this paper, we constructed the analytic model of control valve as a function of electric and geometric parameters, and analyzed the influence of the design parameters on the dynamic characteristics. For improving the dynamic characteristics, optimal design is conducted by applying sequential quadratic programming method to the analytic model. This optimal design aims to minimize the response time and maximize force efficiency. By this procedure, control valve can be designed to have fast response in motion.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제1권1호
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• pp.95-103
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• 2001

The purpose of Introducing a combined cycle with gas turbine in power plants is to reduce losses of energy, by effectively using exhaust gases from the gas turbine to produce additional electricity or process. The efficiency of a combined power plant with the gas turbine increases, exceeding 50%, while the efficiency of traditional steam turbine plants is approximately 35% to 40%. Up to the present time, the PID controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain without any experience, since the gain of the PID controller has to be manually tuned by trial and error procedures. This paper focuses on the neural network tuning of the 2-DOF PID controller with a combined 2-DOF parameter (NN-Tuning 2-DOF PID controller), for optimal control of the Gun-san gas turbine generating plant in Seoul, Korea. In order to attain optimal control, transfer function and operating data from start-up, running, and stop procedures of the Gun-san gas turbine have been acquired and a designed controller has been applied to this system. The results of the NN-Tuning 2-DOF PID are compared with the PID controller and the conventional 2-DOF PID controller tuned by the Ziegler-Nichols method through experimentation. The experimental results of the NN-Tuning 2-DOF PID controller represent a more satisfactory response than those of the previously-mentioned two controllers.

• Journal of Advanced Marine Engineering and Technology
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• 제23권4호
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• pp.480-487
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• 1999

In this paper we propose a neural network precompensated PID(NNP PID) controller for load frequency control of 2-area power system. While proportional integral derivative(PID) controllers are used in power system they have many problems because of high nonlinearities of the power system So a neural network-based precompensation scheme is adopted into a conventional PID controller to obtain a robust control to the nonlinearities. The applied neural network precompen-sator uses an error back-propagation learning algorithm having error and change of error as inputand considers the changing component of forward term of weighting factor for reducing of learning time. Simulation results show that the proposed control technique is superior to a conventional PID controller and an optimal controller in dynamic responses about load disturbances. The pro-posed technique can be easily implemented by adding a neural network precompensator to an existing PID controller.