• ETRI Journal
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• v.35 no.6
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• pp.1168-1171
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• 2013

We propose an improvement of particle swarm optimization (PSO) based on the stabilization of particle movement (PM). PSO uses a stochastic variable to avoid an unfortunate state in which every particle quickly settles into a unanimous, unchanging direction, which leads to overshoot around the optimum position, resulting in a slow convergence. This study shows that randomly located particles may converge at a fast speed and lower overshoot by using the proportional-integral-derivative approach, which is a widely used feedback control mechanism. A benchmark consisting of representative training datasets in the domains of function approximations and pattern recognitions is used to evaluate the performance of the proposed PSO. The final outcome confirms the improved performance of the PSO through facilitating the stabilization of PM.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.772-776
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• 1997

For a robot to perfom more versatile tasks, it is invitable for the robot's end-effector to come into contact with its environment. In thos case, to achieve better performance, it is necessary to properly control the contact force between the robot and the environment. In thos work, hybrid control theory is studied and is verified through experiment using a 3 DOF robot. In the experiment, two position/force controllers are used. Fist, proportional-integral-derivative controller is used as the controller for both position and force. Second, computed-torque method is used as the position controller, and proportional-integral-derivative controller is used as the force controller. For a proper modeling used in computed-torque method, the friction torque is measured by experiment, and compensation method is studied. The hybrid control method used in this experiment effectively control the contact force between the end-effector and the environment for various types of jobs.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.6
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• pp.433-439
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• 2004

The Helicopter Simulator System is non-linear and complex. Futhermore, because of absence of its accurate mathematical model, it is difficult to control accurately its attitudes such as elevation angle and azimuth one. Therefore, we proposed a Hybrid GA-PID WAVENET(Genetic Algorithm Proportional Integral Derivative Wavelet Neural Network)control technique to control efficiently these angles. The proposed Hybrid GA-PID WAVENET is made through the following process. First, the WAVENET fundamental functions are defined. And their dilation and translation values are adjusted by GA to construct the optimal WAVENET controller. Secondly, the proportional, integral, and derivative gain coefficients of PR controller are tuned optimally. Finally, WAVENET controller which has a good transient characteristic and GA-PE controller which has a good steady state characteristic is adequately combined in hybrid type. Through the computer simulations, it is proved that the Hybrid GA-PE WAVENET control technique has a more excellent dynamic response than PID control technique and GA-PID one.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.1
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• pp.10-15
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• 2004

We present a state-space approach to make non-square linear systems strictly passive by using an input-dimensional parallel feedforward compensator. A necessary and sufficient condition for the existence of the parallel feedforward compensator is given by the static output feedback formulation, which enables to utilize linear matrix inequality. By modifying the structure of the compensator the additional technical assumption in the previous result [1] is removed. The effectiveness of the proposed method is illustrated by some numerical examples which can be stabilized by the proportional-derivative (PD) and proportional-derivative-integral (PID) control laws. The proposed control scheme can successfully replace the measurements of derivative terms in the control laws.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.7
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• pp.673-679
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• 2015

In this study, the nondominated sorting genetic algorithm (NSGA-II) is used to obtain the optimized proportional-integral-derivative (PID) gain value that can quickly recover the motion of a quadcopter after a disturbance. Prior to PID control, the four-rotor quadcopter interval was defined using computational fluid dynamics (CFD). Through the definition of this model, the PID control algorithm was generated. To construct a response surface model, D-optimal programming was used for the generation of experimental points. For this purpose, a gain value that satisfies both the roll and altitude PID gain values is obtained. Using the NSGA-II, the gain value of shorten time of the quadcopter motion control can be optimized.

• 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 Korea Society of Industrial Information Systems
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• v.21 no.4
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• pp.21-30
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• 2016

In a single-phase power factor correction (PFC), the standard cascaded control algorithm using a proportional-integral-derivative (PID) controller has two main drawbacks: an inability to track sinusoidal current reference and low harmonic compensation capability. These drawbacks cause poor power factor and high harmonics in grid current. To improve these drawbacks, this paper uses a proportional-integral-derivative-resonant (PIDR) controller which combines a type-III PID with proportional-resonant (PR) controllers in the PFC. Based on a small signal model of the PFC, the type-III PID controller was implemented taking into account the bandwidth and phase margin of the PFC system. To adopt the PR controllers, the spectrum of inductor current of the PFC was analyzed in frequency domain. The hybrid PIDR controller were simulated using PSCAD/EMTDC and implemented on a 3 kW PFC prototype hardware. The performance results of the hybrid PIDR controller were compared with those of an individual type-III PID controller. Both controllers were implemented successfully in the single-phase PFC. The total harmonic distortion of the proposed controller were much better than those of the individual type-III PID controller.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.8
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• pp.87-95
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• 2007

In this paper, we analyzed the mr detection and the stability of the object tracking system by an adaptive stereo object hacking using region-based MAD(Mean Absolute Difference) algorithm and the modified PID(Proportional Integral Derivative)-based pan/tilt controller. That is, in the proposed system, the location coordinates of the target object in the right and left images are extracted from the sequential stereo input image by applying a region-based MAD algorithm and the configuration parameter of the stereo camera, and then these values could effectively control to pan/tilt of the stereo camera under the noisy circumstances through the modified PID controller. Accordingly, an adaptive control effect of a moving object can be analyzed through the advanced system with the proposed 3D robot vision, in which the possibility of real-time implementation of the robot vision system is also confirmed.

• Journal of Power Electronics
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• v.17 no.6
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• pp.1577-1586
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• 2017

The Proportional-Integral-Derivative (PID) controller is still the most widespread control strategy in the industry. PID controllers have gained popularity due to their simplicity, better control performance and excellent robustness to uncertainties. This paper presents the optimal tuning of a PID controller for domestic induction heating systems with a series resonant inverter for controlling the induction heating power. The objective is to design a stable and superior control system by tuning the PID controller with a derivative filter (PIDF) through Fuzzy logic. The paper also compares the performance of the Fuzzy PIDF controller with that of a Ziegler-Nichols PID controller and a fine-tuned PID controller with a derivative filter. The system modeling and controllers are simulated in MATLAB/SIMULINK. The results obtained show the effectiveness and superiority of the proposed Fuzzy PID controller with a derivative filter.

• 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.