• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1209-1216
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• 2014

This paper copes with control design for unmanned aerial vehicle transportation system. Moving pendulum dynamics of slung-load system is derived using two methods: Udwadia-Kalaba equation and Newtonian approach. PID controller is applied to Udwadia-Kalaba equation model for structural consistency and linear quadratic Gaussian / Loop Transfer Recovery (LQG/LTR) technique is employed for Newtonian model with minimal state-space realization. Characteristics of PID and LQG/LTR controller are compared, and two controllers are combined to compensate the drawbacks of each other. Numerical simulation is set for two cases and conducted to evaluate performance of designed controllers. The result proves that combination of LQG/LTR and PID control performs stable and robust.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.831-836
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• 2011

The study described in this paper is aimed to maintain a constant output of wind turbine system via pitch control of wind turbine using Advanced PID(APID) controller. In order to improve dynamic response characteristic in terms of pitch angle and disturbance reject, the APID controller is developed. The structure of the APID is composed with derivative P controller and new type of integral control action. This new improved integral control has concept of error window and weight function concept. The performance of the APID control technique is compared with those of conventional ones via simulation. Simulation results show that the proposed method is effective and enhanced the dynamic performance of the system.

• 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.

• Nuclear Engineering and Technology
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• v.50 no.6
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• pp.877-885
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• 2018

Various controllers such as proportional-integral-derivative (PID) controllers have been designed and optimized for load-following issues in nuclear reactors. To achieve high performance, gain tuning is of great importance in PID controllers. In this work, gains of a PID controller are optimized for power-level control of a typical pressurized water reactor using particle swarm optimization (PSO) algorithm. The point kinetic is used as a reactor power model. In PSO, the objective (cost) function defined by decision variables including overshoot, settling time, and stabilization time (stability condition) must be minimized (optimized). Stability condition is guaranteed by Lyapunov synthesis. The simulation results demonstrated good stability and high performance of the closed-loop PSO-PID controller to response power demand.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.4
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• pp.480-487
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• 1999

In this paper we propose a neural network precompensated PID(NNP PID) controller for load frequency control of 2-area power system. While proportional integral derivative(PID) controllers are used in power system they have many problems because of high nonlinearities of the power system So a neural network-based precompensation scheme is adopted into a conventional PID controller to obtain a robust control to the nonlinearities. The applied neural network precompen-sator uses an error back-propagation learning algorithm having error and change of error as inputand considers the changing component of forward term of weighting factor for reducing of learning time. Simulation results show that the proposed control technique is superior to a conventional PID controller and an optimal controller in dynamic responses about load disturbances. The pro-posed technique can be easily implemented by adding a neural network precompensator to an existing PID controller.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.1
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• pp.136-144
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• 2004

In general a hydraulic system which uses a single rod hydraulic as an actuator is modeled as a nonlinear system and reveals uncertain Parameter characteristics such as the density variation of hydraulic oil and is subject to load variations and severe disturbances during operation. A variable design-parameter fuzzy PID controller is adopted to solve these undesirable internal and external problems and its effectiveness is verified through computer simulations for control performance and real time control possibility.

• Journal of Advanced Navigation Technology
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• v.26 no.2
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• pp.105-112
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• 2022

In this paper, unmanned underwater glider was designed for high-depth operation and adopted a bladder-type buoyancy controller for improving battery efficiency, and the motion controller controls the pitch angle by moving the internal mass battery. To improve the energy efficiency of the unmanned underwater glider, a layered PID controller that performs control by section was designed. Simulation program including 6-DOF motion equations and hydrodynamics coefficients of an unmanned underwater glider is constructed using Matlab/Simulink program. Control methods such as PID controller, sliding mode controller and layered PID controller were applied to the simulator to compare the dynamics performance and energy efficiency. As a result, the layered PID controller showed improved control performance compared to other controllers and improved energy efficiency of approximately 7.2% compared to PID controller.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.790-794
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• 1989

A novel control method involving an automatic tuning of digital PID controller parameters has been developed for better regulation of DO (dissolved oxygen) concentration in batch fermentation processes. Heuristic reasoning allows the PID controller to reach improved tuning decisions based upon the supervision of certain control performance indices in the same cognitive manner as in an expert control.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.7
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• pp.852-861
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• 2003

In this paper, in order to improve the disadvantages of the fixed design-parameter fuzzy PID controller. a new fuzzy PID controller named a variable design-parameter fuzzy PID controller is suggested. The main characteristic of the suggested controller is to adjust design-parameters of the controller by comparing magnitudes between fuzzy controller inputs at each sampling time when controller inputs are measured. As a result. all fuzzy input partitioned spaces converge within a time-varying normalization scale. and the resultant PID control action can always be applied precisely regardless of operating input magnitudes. In order to verify the effectiveness of the suggested controller. several a computer simulations for a nonlinear system are executed and the control parameters of the variable design-parameter fuzzy PID controller are throughly analyzed.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.8
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• pp.1299-1312
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• 2004

This paper suggests the simple form of a fuzzy PID controller and describes the design principle, tracking performance, stability analysis and changes of parameters of a suggested fuzzy PID controller. A fuzzy PID controller is derived from the design procedure of fuzzy control. It is well known that a fuzzy PID controller has a simple structure of the conventional PID controller but posses its self-tuning control capability and the gains of a fuzzy PID controller become nonlinear functions of the inputs. Nonlinear calculation during fuzzification, defuzzification and the fuzzy inference require more time in computation. To increase the applicability of a fuzzy PID controller to digital computer, a simple form of a fuzzy PID controller is introduced by the backward difference mapping and the analysis of the fuzzy input space. To guarantee the BIBO stability of a suggested fuzzy PID controller, ‘small gain theorem’ which proves the BIBO stability of a fuzzy PI and a fuzzy PD controller is used. After a detailed stability analysis using ‘small gain theorem’, from which a simple and practical method to decide the parameters of a fuzzy PID controller is derived. Through the computer simulations for the linear and nonlinear plants, the performance of a suggested fuzzy PID controller will be assured and the variation of the gains of a fuzzy PID controller will be investigated.