• Journal of Navigation and Port Research
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• v.35 no.3
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• pp.227-233
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• 2011

This paper presents the tracking and stabilization problem of a night vision system for marine surveillance. Both a hardware system and software modules are developed to control azimuth and elevation axes independently with compensation for ship motion. A two degree of freedom(2DOF) PID controller is designed and its parameters are tuned using a real-coded genetic algorithm(RCGA). Simulation demonstrates the effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 2000.07e
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• pp.129-131
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• 2000

The moving vehicle with disturbances has the 6 degree of freedom motion in the pitching, Yawing, and rolling directions of two independent axes. The control system in such a moving vehicle has to perform disturbance rejection. This paper present PID controller with disturbance rejection function, low sensitivity filter and notch filter for bending frequency rejection. The performance of a designed system has been certified by the simulation and experiment and experiment results.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.3
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• pp.188-199
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• 2014

Although the fuzzy logic controller is superior to the proportional integral derivative (PID) controller in motor control, the gain tuning of the fuzzy logic controller is more complicated than that of the PID controller. Using mathematical analysis of the proportional derivative (PD) and fuzzy logic controller, this study proposed a design method of a fuzzy logic controller that has the same characteristics as the PD controller in the beginning. Then a design method of a fuzzy logic controller was proposed that has superior performance to the PD controller. This fuzzy logic controller was designed by changing the envelope of the input of the of the fuzzy logic controller to nonlinear, because the fuzzy logic controller has more degree of freedom to select the control gain than the PD controller. By designing the fuzzy logic controller using the proposed method, it simplified the design of fuzzy logic controller, and it simplified the comparison of these two controllers.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2006.06a
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• pp.107-108
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• 2006

This paper presents the design of a night vision system for vessels. Both a hardware system and software modules for stabilization control are developed. In order to stabilize each control axis, the two-degree of freedom(TDF) PID controller is designed and its parameters are tuned using a real-coded genetic algorithm(RCGA). Simulation demonstrates the effectiveness of the proposed system.

• International Journal of Automotive Technology
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• v.4 no.4
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• pp.181-191
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• 2003

Since the nonlinearity and uncertainties which inherently exist in vehicle system need to be considered in active suspension control law design, this paper proposes a new control strategy for active vehicle suspension systems by using a combined control scheme, i.e., respectively using a genetic algorithm (GA) based self-tuning PID controller and a fuzzy logic controller in two loops. In the control scheme, the PID controller is used to minimize vehicle body vertical acceleration, the fuzzy logic controller is to minimize pitch acceleration and meanwhile to attenuate vehicle body vertical acceleration further by tuning weighting factors. In order to improve the adaptability to the changes of plant parameters, based on the defined objectives, a genetic algorithm is introduced to tune the parameters of PID controller, the scaling factors, the gain values and the membership functions of fuzzy logic controller on-line. Taking a four degree-of-freedom nonlinear vehicle model as example, the proposed control scheme is applied and the simulations are carried out in different road disturbance input conditions. Simulation results show that the present control scheme is very effective in reducing peak values of vehicle body accelerations, especially within the most sensitive frequency range of human response, and in attenuating the excessive dynamic tire load to enhance road holding performance. The stability and adaptability are also showed even when the system is subject to severe road conditions, such as a pothole, an obstacle or a step input. Compared with conventional passive suspensions and the active vehicle suspension systems by using, e.g., linear fuzzy logic control, the combined PID and fuzzy control without parameters self-tuning, the new proposed control system with GA-based self-learning ability can improve vehicle ride comfort performance significantly and offer better system robustness.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2569-2571
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• 2000

In the vehicle steering system, we can consider two methods to steer the vehicle. One is a front wheel steering(FWS), the other is a four wheel steering(4WS). The four wheel steering method has been recently introduced to improve the steering performance. In this paper, we present a design of the four wheel steering controller. First, we constructed the neural network two degree of freedom PID controller to control the 4WS system. Then we compared the performance of conventional PID controller with our proposed controller in terms of yaw rate and side slip velocity. The computer simulation results show that 4WS system controlled by the proposed controller has well driving performances than the other.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.9
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• pp.839-845
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• 2013

A CSTR (Continuous Stirred Tank Reactor) is a highly nonlinear process with varying parameters during operation. Therefore, tuning of the controller and determining the transition policy of controller parameters are required to guarantee the best performance of the CSTR for overall operating regions. In this paper, a methodology employing the 2DOF (Two-Degree-of-Freedom) PID controller, the anti-windup technique and a fuzzy gain scheduler is presented for the temperature control of the CSTR. First, both a local model and an EA (Evolutionary Algorithm) are used to tune the optimal controller parameters at each operating region by minimizing the IAE (Integral of Absolute Error). Then, a set of controller parameters are expressed as functions of the gain scheduling variable. Those functions are implemented using a set of "if-then" fuzzy rules, which is of Sugeno's form. Simulation works for reference tracking, disturbance rejecting and noise rejecting performances show the feasibility of using the proposed method.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.10a
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• pp.123-128
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• 2006

This paper presents the design of a surveillance night vision system for marine ships. Both a hardware system and software modules for tracking control are developed. In order to control each control axis with compensation for ship motion, the two-degree of freedom(TDF) PID controller is designed and its parameters are tuned using a real-coded genetic algorithm(RCGA). Simulation demonstrates the effectiveness of the proposed system.

• Journal of Advanced Marine Engineering and Technology
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• v.19 no.1
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• pp.60-70
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• 1995

In the field of marine transportation the energy saving is one of the most important factors for profit. In order to reduce the fuel oil consumption the ship's propulsion efficiency must be increased as much as possible. The propulsion efficiency depends upon a combination of an engine and a propeller. The propeller has better efficiency as lower rotational speed. This situation led the engine manufacturers to design the engine that has lower speed, longer stroke and a small number of cylinders. Consequently the variation of rotational torque became larger than before because of the longer delay-time in the fuel oil injection process and an increased output per cylinder. As this new trends the conventional mechanical-hydrualic governors for engine speed control have been replaced by digital speed controllers which adopted the PID control or the optimal control algorithm. But these control algorithms have not enough robustness to suppress the variation of the delay-time and the parameter pertubation. In this paper we consider the delay-time and the perturbation of engine parameters as the modeling uncetainties. Next we design the controller which has zero offset in steady state engine speed, based on the two-degree-of-freedom control theory and $\mu$-synthesis. Thd validity of the controller is investigated through the response simulation. We use a personal computer and an analog computer as the digital controller and the engine (plant) part respectively. And, we certify that the designed controller maintains its performance even though the engine parameters may vary.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.346-349
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• 2003

For a traveling crane, various control methods such as neural network predictive control and TDOFPID(Two Degree of Freedom Proportional Integral Derivative) are studied. So in this paper, we proposed improved navigation method to reduce transfer time and sway with anti-collision path for avoiding collision in its movement to the finial coordinate. And we constructed the NNPPID(Neural Network Predictive PID) controller to control the precise move and speedy navigation. The proposed predictive control system is composed of the neural network predictor, TDOFPID controller, and neural network self-tuner. We analyzed ASC(Automated Stacking Crane) system and showed some computer simulations to prove excellence of the proposed controller than other conventional controllers.