• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.155-164
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• 2006

This paper focuses on a new optimization technique of a fuzzy logic based proportional integral (FLPI) load frequency controller by the multiple tabu search (MTS) algorithm. Conventionally, the membership functions and control rules of fuzzy logic control are obtained by trial and error method or experiences of designers. To overcome this problem, the MTS algorithm is proposed to simultaneously tune proportional integral gains, the membership functions and control rules of a FLPI load frequency controller in order to minimize the frequency deviations of the interconnected power system against load disturbances. The MTS algorithm introduces additional techniques for improvement of the search process such as initialization, adaptive search, multiple searches, crossover and restart process. Simulation results explicitly show that the performance of the proposed FLPI controller is superior to conventional PI and FLPI controllers in terms of overshoot and settling time. Furthermore, the robustness of the proposed FLPI controller under variation of system parameters and load change are higher than that of conventional PI and FLPI controllers.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.10
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• pp.1297-1302
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• 2014

This paper presents modern optimization methods for determining the optimal parameters of proportional-integral-derivative (PID) controller for coupled tank systems. The main objective is to obtain a fast and stable control system for coupled tank systems by tuning of the PID controller using the Particle Swarm Optimization algorithm. The result is compared in terms of system transient characteristics in time domain. The obtained results using the Particle Swarm Optimization algorithm are also compared to conventional PID tuning method like the Ziegler-Nichols tuning method, the Cohen-Coon method and IMC (Internal Model Control). The simulation results have been simulated by MATLAB and show that tuning the PID controller using the Particle Swarm Optimization (PSO) algorithm provides a fast and stable control system with low overshoot, fast rise time and settling time.

• Journal of Power Electronics
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• v.16 no.1
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• pp.205-216
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• 2016

The manufacturing sector resorts to automation to increase production and homogeneity of products during mass production, without increasing scarce, expensive, and unreliable manpower. Automation in the form of multiple robotic arms that handle materials in all directions in different stages of the process is proven to be the best way to increase production. This paper thoroughly investigates robotic single-arm movements, that is, 360° vertical rotation, with the help of a brushless DC motor, controlled by a fuzzy proportional-integral-derivative (PID) controller. This paper also deals with the design and performance of the fuzzy-based PID controller used to control vertical movement against the limited scope of conventional PID feedback controller and how the torque of the arm is affected by the fuzzy PID controller in the four quadrants to ensure constant speed and accident-free operation despite the influence of gravitational force. The design was simulated through MATLAB/SIMULINK and integrated with dSPACE DS1104-based hardware to verify the dynamic behaviors of the arm.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.123-133
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• 2023

Active queue management (AQM) is a leading congestion control system, which can keep smaller queuing delay, less packet loss with better network utilization and throughput by intentionally dropping the packets at the intermediate hubs in TCP/IP (transmission control protocol/Internet protocol) networks. To accelerate the responsiveness of AQM framework, proportional-integral-differential (PID) controllers are utilized. In spite of its simplicity, it can effectively take care of a range of complex problems; however it is a lot complicated to track down optimal PID parameters with conventional procedures. A few new strategies have been grown as of late to adjust the PID controller parameters. Therefore, in this paper, we have developed a Squirrel search based PID controller to dynamically find its controller gain parameters for AQM. The controller gain parameters are decided based on minimizing the integrated-absolute error (IAE) in order to ensure less packet loss, high link utilization and a stable queue length in favor of TCP networks.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.503-510
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• 2021

This study intends to apply the mathematical method of fractional order differentiation to a controller that controls the response of the system. Therefore, we design integrator for the fractional index by converting it into discrete time to construct a controller. The IP controller composes an integral controller for errors and the proportional controller applies only the system output. The controller is designed by using the fractional order integrator to the integral controller of the IP controller. First, the performance of the PI controller and the IP controller is compared, and the designed controller is applied to the speed control of the motor. As a result, the motor output speed was uniformed and precise control performance could be obtained. It was confirmed that the speed error in the steady state is within 0.1 [%], and it has precise and uniform speed control performance without overshoot.

• 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.

• 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 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 Power Electronics
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• v.11 no.1
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• pp.45-50
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• 2011

This paper proposes a method for comparing and evaluating anti-windup proportional-integral (PI) control strategies. The so-called PI plane is used and its coordinate is composed of the error and the integral state. In addition, an anti-windup PI controller with integral state prediction is proposed. The anti-windup scheme can be easily analyzed and evaluated on the PI plane in detail. Representative anti-windup methods are experimentally applied to the speed control of a vector-controlled induction motor driven by a pulse width modulated (PWM) voltage-source inverter (VSI). The experimental results compare the anti-windup PI controllers. It is empathized that the initial value of the integral state at the beginning of the linear range dominates the control performance in terms of overshoot and settling time.

• Journal of Drive and Control
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• v.18 no.4
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• pp.52-58
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• 2021

The variable structure controller is designed such that in sliding mode, the system moves along the switching plane in the vicinity of the switching plane, thus it is robust because it is not affected by the parameter fluctuations of the plant. However, a controller based on a variable structure may not meet the desired performance when it is commanded to track any input or is exposed to disturbances. This study proposes a sliding mode controller that follows the IVSC (Integral Variable Structure Control) approach with ELO (Extended Luenberger observer) to solve this problem. The proposed sliding mode control is applied to the velocity control of the hydraulic motor. The sliding plane was determined by the pole placement, and the control input was designed to ensure the existence of the sliding mode. The feasibility of modeling and controller are reviewed by comparing with conventional proportional-integral control through computer simulation using MATLAB software and experimenting on the cases of significant plant parameter fluctuations and disturbances.