• Smart Structures and Systems
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• v.22 no.1
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• pp.81-94
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• 2018

Automatic Generation Control (AGC) has functionally controlled the interchange power flow in order to suppress the dynamic oscillations of frequency and tie-line power deviations as a perturbation occurs in the interconnected multi-area power system. Furthermore, Flexible AC Transmission Systems (FACTS) can effectively assist AGC to more enhance the dynamic stability of power system. So, Static Synchronous Series Compensator (SSSC), one of the well-known FACTS devices, is here applied to accurately control and regulate the load frequency of multi-area multi-source interconnected power system. The research and efforts made in this regard have caused to introduce the Fractional Order Proportional Integral Derivative (FOPID) based SSSC, to alleviate both the most significant issues in multi-area interconnected power systems i.e., frequency and tie-line power deviations. Due to multi-objective nature of aforementioned problem, suppression of the frequency and tie-line power deviations is formularized in the form of a multi-object problem. Considering the high performance of Multi Objective Bees Algorithm (MOBA) in solution of the non-linear objectives, it has been utilized to appropriately unravel the optimization problem. To verify and validate the dynamic performance of self-defined FOPID-SSSC, it has been thoroughly evaluated in three different multi-area interconnected power systems. Meanwhile, the dynamic performance of FOPID-SSSC has been accurately compared with a conventional controller based SSSC while the power systems are affected by different Step Load Perturbations (SLPs). Eventually, the simulation results of all three power systems have transparently demonstrated the dynamic performance of FOPID-SSSC to significantly suppress the frequency and tie-line power deviations as compared to conventional controller based SSSC.

• Ocean Systems Engineering
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• v.6 no.3
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• pp.265-287
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• 2016

The change of the global performance of a turret-moored FPSO (Floating Production Storage Offloading) with DP (Dynamic Positioning) control is simulated, analyzed, and compared for two different internal turret location cases; bow and midship. Both collinear and non-collinear 100-yr GOM (Gulf of Mexico) storm environments and three cases (mooring-only, with DP position control, with DP position+heading control) are considered. The horizontal trajectory, 6DOF (degree of freedom) motions, fairlead mooring and riser tension, and fuel consumptions are compared. The PID (Proportional-Integral-Derivative) controller based on LQR (linear quadratic regulator) theory and the thrust-allocation algorithm which is based on the penalty optimization theory are implemented in the fully-coupled time-domain hull-mooring-riser-DP simulation program. Both in collinear and non-collinear 100-yr WWC (wind-wave-current) environments, the advantage of mid-ship turret is demonstrated by the significant reduction in heave at the turret location due to the minimal coupling with pitch mode, which is beneficial to mooring and riser design. However, in the non-collinear WWC environment, the mid-turret case exhibits unfavorable weathervaning characteristics, which can be reduced by employing DP position and heading controls as demonstrated in the present case studies. The present study also reveals the plausible cause of the failure of mid-turret Gryphon Alpha FPSO in milder environment than its survival condition.

• Journal of Advanced Navigation Technology
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• v.20 no.3
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• pp.226-231
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• 2016

Researching and developing mobile robot are quite important. Autonomous driving of mobile robot is important in various working environment. For its autonomous driving, mobile robot detects obstacles and avoids them. Purpose of this thesis is to analyze kinematics model of the mobile robot and show the efficiency of type-2 fuzzy self-tuning PID controller used for controling steering angle. Type-2 fuzzy is more flexible in verbal expression than type-1 fuzzy because it has multiple values unlike previous one. To compare these two controllers, this paper conduct a simulation by using MATLAB Simulink. The result shows the capability of type-2 fuzzy self-tuning PID is effective.

• Journal of Biosystems Engineering
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• v.31 no.3 s.116
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• pp.203-208
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• 2006

This study was conducted to improve the control performance of a current variable-rate controller for granular fertilizers. Simulation model was developed. Optimized proportional, integral and derivative gains were determined by simulation model using 2nd order PID gain learning algorithm, and these control gains were evaluated through the field tests. Important results of this study are as follows; 1. Principles of pre-existing variable-rate application of granular fertilizers were investigated. 2. Simulation model of a PID controller that could simulate the control system was developed by using Matlab/Simulink program. The program was to determine PID control coefficients through the simulation model and 2nd order PID gain learning algorithm. 3. PID control coefficients obtained from the simulation were applied to the developed model. When the step input was given, Maximum overshoot were 1.96%, rise time were 0.05 sec, settling time were 0.06 sec and steady state error were 0.21 % respectively. 4. The simulation model was verified through field tests. The errors of maximum overshoot were 10%, rise time were 0.11 sec, settling time were 0.40 sec and steady state error were 8% because of loads and noises. Rise time was decreased to one third of that of the pre-existing system. 5. If the speed of a fertilizing machine is $0.3{\sim}0.6\;m/s$ and the maximum rotation speed of a discharging roller is 64 rpm, rise time would be 0.26 sec and fertilizing machine would cover the distance of $0.07{\sim}0.15\;m$ with settling time of 0.4 sec, fertilizing machine would cover the distance of $0.12{\sim}0.24\;m$.

• Journal of Aerospace System Engineering
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• v.11 no.1
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• pp.14-21
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• 2017

A Linear parameterized Sigma-Pi neural network (SPNN) is applied to a tilt-duct unmanned aerial vehicle (UAV) which has a very large longitudinal stability ($C_{L{\alpha}}$). It is uncontrollable by a proportional, integral, derivative (PID) controller due to heavy stability. It is shown that the combined inner loop and outer loop of SPNN controllers could overcome the sluggish longitudinal dynamics using a method of dynamic inversion and pseudo-control to compensate for reference model error. The simulation results of the way point guidance are presented to evaluate the performance of SPNN in comparison to a PID controller.

• Journal of Ocean Engineering and Technology
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• v.29 no.3
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• pp.270-282
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• 2015

A submerged body moving near the free surface needs to maintain its attitude and position to accomplish missions. It is necessary to validate the performance of a designed controller before a sea trial. The hydrodynamic coefficients of maneuvering are generally obtained by experiments or computational fluid dynamics, but these coefficients have uncertainty. Environmental loads such as the wave exciting force and suction force act on the submerged body when it moves near the free surface. Thus, a controller for the submerged body should be robust to parameter uncertainty and environmental loads. In this paper, the six-degree-of-freedom equations of motions for the submerged body are constructed. The suction force is calculated using the double Rankine body method. An adaptive control method based on an artificial neural network and proportional-integral-derivative control are used for the depth controller. Simulations are performed under various depth and speed conditions, and the results show the effectiveness of the designed controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.355-367
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• 2007

This paper proposes a design method of the PI(Proportional-Integral)+D(Derivative) controller using self-tuning of the design variables and controller gains. The used fuzzy PI+D controller is the approximated conventional continuos time linear PI+D controller and the used fuzzification method is the fuzzy single tone and the adapted defuzzification method is the simplified tenter of gravity. Fuzzy estimation result would be calculated in the other function elements from the classified fuzzy variables and the result determined by the design variables decides the controller gains. As a result, the proposed method shows the capability of the high speed tuning and can be applied to the case of input variables with many fuzzy partitions and also can bring out the advantage to reduce the reconstruction(digital sampling reconstruction) error. Most simulation results show that this controller makes much bettor efficiency and improvement by using design variables and controller gains.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.63 no.4
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• pp.290-294
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• 2014

PID(Proportional, Integral, Derivative) controller is the most popular process controllers in nuclear power plants. The optimized parameter setting of the process controller contributes to the stable operation and the efficiency of the operating nuclear power plants. PID parameter setting is tuned when new process control systems are installed or current process control systems are changed. When the nuclear plant is shut down, a lot of PID tuning methods such as the Trial and Error method, Ultimate Oscillation method operation, Ziegler-Nichols method, frequency method are used to tune the PID values. But inadequate PID parameter setting can be the cause of the unstable process of the operating nuclear power plant. Therefore the results of PID parameter setting should be simulated, optimized and finally verified. This paper introduces the simulation method of PID tuning to optimize the PID parameter setting and confirms them of the actual PID controller in the operating nuclear power plants. The simulation method provides the accurate process modeling and optimized PID parameter setting of the multi-loop control process in particular.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.23 no.12
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• pp.782-790
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• 2011

Typical temperature control methods of a cooler for machine tools are hot-gas bypass and compressor variable speed control. The hot-gas bypass system has been widely used to control the cooler temperature in many general industrial fields. On the contrary, the compressor variable speed control is focused on special fields such as aerospace and high precision machine tools which need high precision control. The variable speed control system usually has two control variables such as target temperature and superheat. In other words, the variable speed control system is basically multi-input multi-output(MIMO) system. In spite of MIMO system, the proportional integral derivative(PID) feedback control methodology that based on single-input single-output (SISO) system is generally used for designing the variable speed control system. Therefore, it is inevitable to describe transfer functions for dynamic behaviors of every controlled variables and decide the PID gains with tremendous iteration process. Moreover, the designed PID gains do not provide optimum system performances. To solve these problems, high performance controller design method based on a state space model is suggested in this paper. An optimum controller is designed to minimize both control errors and energy inputs. This method was more simple to describe dynamic behaviors and easier to design the cooler controller which is MIMO system.

• Journal of the Society of Naval Architects of Korea
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• v.54 no.2
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• pp.102-112
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• 2017

Many studies on dynamic positioning control algorithms using fixed feedback gains have been carried out to improve station keeping performance of dynamically positioned vessels. However, the control algorithms have disadvantages in that it can not cope with changes in environmental disturbances and response characteristics of vessels motion in real time. In this paper, the Fuzzy Gain Scheduling - PID(FGS - PID) control algorithm that can tune PID gains in real time was proposed. The FGS - PID controller that consists of fuzzy system and a PID controller uses weighted values of PID gains from fuzzy system and fixed PID gains from Ziegler - Nichols method to tune final PID gains in real time. Firstly, FGS - PID controller, control allocation algorithm, FPSO and environmental disturbances were modeled using Matlab/Simulink to evaluate station keeping performance of the proposed control algorithm. In addition, simulations that keep positions and a heading angle of vessel with wind, wave, current disturbances were carried out. From simulation results, the FGS - PID controller was confirmed to have better performances of keeping positions and a heading angle and consuming power than those of the PID controller. As a consequence, the proposed FGS - PID controller in this paper was validated to have more effectiveness to keep position and heading angle than that of PID controller.