• The Transactions of the Korean Institute of Power Electronics
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• v.22 no.1
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• pp.60-66
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• 2017

This paper presents the design of a proportional-integral (PI)-proportional-derivative (PD) position controller without using a speed controller in motor drive systems. Unlike the existing PI-PD position controller design methods, the proposed controller is designed by reducing the entire position control system to a second-order transfer function. Thus, the gain values for the PI-PD position controller can be determined easily by a given bandwidth of the position controller. The PI-PD position controller designed by the proposed method is adopted for position control in an interior permanent magnet synchronous motor drive system to confirm the validity of the proposed design method. The effectiveness of the proposed design method is confirmed through experiments.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.795-797
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• 1998

This paper suggests a design method of the optimal PD control system having robust performance. This PD control system is designed by applying genetic algorithm(GA) with reference model to the optimal determination of proportional(P) gain and derivative(D) gain that are given by PD servo controller. These proportional and derivative gains are simultaneously optimized in the search domain guaranteeing the robust performance of closed-loop system. This PD control system is applied to the fuel-injection control system of diesel engine and compared with ${\mu}$ -synthesis control system for robust performance. The effectiveness of this PD control system is verified by computer simulation.

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.101-108
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• 1996

A new speed controller based on the fuzzy algorithm with hierarchical structure is presented. The input variables of the controller are speed error and its derivative(change of error), where the output variable is the change of torque current command. Several comparisons were performed with conventional PI (proportional plus integral) controller and proposed controller. These controllers are applied to the laboratory model drive system with 2.2kW induction motor. Some simulation and experimental results show that the speed controller using fuzzy algorithm is more robust than the conventional PI controller.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.9
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• pp.863-868
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• 2011

This paper presents a method to achieve a synchronous positioning objective for a dual-cylinder electro-hydraulic system with friction characteristics. The control system consists of a VSC (Variable Structure Controller) for each of the hydraulic cylinders and a PID (Proportional-Integral-Derivative) feedback controller. The PID controller is used for controlling the non-synchronous error generated by both cylinders when motion synchronization is carried out. To enhance the position-tracking performance of the individual cylinders friction characteristics is modeled in model, based on the estimated friction force. The simulation and experimental results show that the proposed method can effectively achieve the objective of position synchronization in the dualcylinder electro-hydraulic system, with maximum synchronization error with ${\pm}2\;mm$.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.1
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• pp.40-46
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• 1999

A self-tuning FPID(Fuzzy Proportional Intergral Derivative) controller fo load frequency control of 2-area power systemis proposed in this paper. The paramters of the proposed self-tuning FPID controller are self-tuned by the proposed fuzzy inference technique. Therefore in this paper the fuzzy inference technique of PID gains using PSGM(Product Sum Gravity Method) is presented and is applied to the load frequency control of 2-area power system. The computer simulation results show that the proposed controller give better more control characteristics than convention-al PID, FLC under load changes.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.7
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• pp.791-799
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• 2006

The aim of this paper is to design an adaptive speed control system of a marine diesel engine by fusion of hard computing based proportional integral derivative (PID) control and soft computing based fuzzy control methods. The model of a marine diesel engine is considered as a typical non oscillatory second order system. When its model and the actual marine diesel engine ate not matched, it is hard to control the speed of the marine diesel engine. Therefore, this paper proposes two methods in order to obtain the speed control characteristics of a marine diesel engine. One is an efficient method to determine the PID control parameters of the nominal model of a marine diesel engine. Second is a reference adaptive speed control method that uses a fuzzy controller and derivative operator for tracking the nominal model of the marine diesel engine. It was found that the proposed PID parameters adjustment method is better than the Ziegler & Nichols' method, and that a model reference adaptive control is superior to using only PID controller. The improved control method proposed here, could be applied to other systems when a model of a system does not match the actual system.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.940-947
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• 2022

Meta-heuristic algorithms have found their place in optimization problems. Henry gas solubility optimization (HGSO) is one of the newest population-based algorithms. This algorithm is inspired by Henry's law of physics. To evaluate the performance of a new algorithm, it must be used in various problems. On the other hand, the optimization of the proportional-integral-derivative (PID) gains for load-following of a nuclear power plant (NPP) is a good challenge to assess the performance of HGSO. Accordingly, the power control of a pressurized water reactor (PWR) is targeted, based on the point kinetics model with six groups of delayed-neutron precursors. In any optimization problem based on meta-heuristic algorithms, an efficient objective function is required. Therefore, the integral of the time-weighted square error (ITSE) performance index is utilized as the objective (cost) function of HGSO, which is constrained by a stability criterion in steady-state operations. A Lyapunov approach guarantees this stability. The results show that this method provides superior results compared to an empirically tuned PID controller with the least error. It also achieves good accuracy compared to an established GA-tuned PID controller.

• Journal of Communications and Networks
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• v.6 no.2
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• pp.133-146
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• 2004

Recently, many active queue management (AQM) algorithms have been proposed to address the performance degradation. of end-to-end congestion control under tail-drop (TD) queue management at Internet routers. However, these AQM algorithms show performance improvement only for limited network environments, and are insensitive to dynamically changing network situations. In this paper, we propose an adaptive queue management algorithm, called PID-controller, that uses proportional-integral-derivative (PID) feedback control to remedy these weak-Dalles of existing AQM proposals. The PID-controller is able to detect and control congestion adaptively and proactively to dynamically changing network environments using incipient as well as current congestion indications. A simulation study over a wide range of IP traffic conditions shows that PID-controller outperforms other AQM algorithms such as Random Early Detection (RED) [3] and Proportional-Integral (PI) controller [9] in terms of queue length dynamics, packet loss rates, and link utilization.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.404-407
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• 1992

In this thesis, the algorithm of Fuzzy Logic Control(FLC) is applied to the Nonlinear system to implement a system response. Proportional-Integral-Derivative(PID) controller is also used to control the various systems. Look-up table is applied to decide the control input, and the other look-up table is added for saving memories and inference time. Generally, FLC input variables are error(E) and error derivative($\Delta$E). In this algorithm. another Input variable error's second derivative($\Delta^2$E) is added for Robust Fine control.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.5
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• pp.360-366
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• 1987

The design problem of optimal constant PIDM (proportional-integral-derivative and measurable variable) feedback controller for linear time-invariannt systems is investigated with the time-weighted quadratic performance index. Necessary conditions for an optimality of the controller are derived and an algorithm for computing the optimal feedback gain is presented. It is shown via example that the design mithod using the time-weighted quadratic performance index improves the transient responses of the closed-loop system.