Gas turbine engines are widely used as prime movers of generator and propulsion system in warships. This study addresses the problem of designing a DS-based PID controller for speed control of the LM-2500 gas turbine engine used for propulsion in warships. To this end, we first derive a dynamic model of the LM-2500 using actual sea trail data. Next, the PRC (process reaction curve) method is used to approximate the first-order plus time delay (FOPTD) model, and the DS-based PID controller design technique is proposed according to approximation of the time delay term. The proposed controller conducts set-point tracking simulation using MATLAB (2016b), and evaluates and compares the performance index with the existing control methods. As a result of simulation at each operating point, the proposed controller showed the smallest in , which means that the rpm does not change rapidly. In addition, IAE and IAC were also the smallest, showing the best result in error performance and controller effort.

In this study, the load fluctuation of the main engine is considered to be a disturbance for the jacket coolant temperature control system of the low-speed two-stroke main diesel engine on the ships. A nonlinear PID temperature control system with satisfactory disturbance rejection performance was designed by rapidly transmitting the load change value to the controller for following the reference set value. The feed-forwarded load fluctuation is considered the set points of the dual loop control system to be changed. Real-coded genetic algorithms were used as an optimization tool to tune the gains for the nonlinear PID controller. ITAE was used as an evaluation function for optimization. For the evaluation function, the engine jacket coolant outlet temperature was considered. As a result of simulating the proposed cascade nonlinear PID control system, it was confirmed that the disturbance caused by the load fluctuation was eliminated with satisfactory performance and that the changed set value was followed.

This paper proposes a fusion controller combing an anti-windup PID controller and BELBIC (Brain Emotional Learning Based Intelligent Controller) for controlling the position and vibration of a robot system having a single flexible manipulator. A finite element model of the flexible manipulator is developed. The reliability of it is verified by comparing the natural frequencies computed using the finite-element method with the experimentally measured ones. An MSC.ADAMS computational model of the robot system is interfaced with the proposed controller in MATLAB/Simulink, for carrying out a simulation. The simulation is performed with various references inputs and endpoint masses. The effectiveness and robustness of the proposed controller for control of the position and vibration of the flexible manipulator is shown through the simulation.

Recently, a study on reducing the weight of the robot arm, which enables a high-speed operation and enables reducing the energy consumption has been actively carried out. A lightweight robot arm is hard to control because it behaves like a flexible body rather than a rigid body. This paper proposes a controller which combines a PID controller and a fuzzy logic controller for control the position and vibration of the flexible robot arm. In order to show the effectiveness of the proposed controller, MSC.ADAMS computational model which incorporates the finite element flexible robot arm model is developed, and is used for performing simulations. Simulations are carried out with two reference inputs, and three end masses. Simulation results show that the proposed controller controls the position and vibration of the flexible robot arm adaptively without being affected by the reference input and the end mass.

가스터빈 기관은 우주항공, 발전 플랜트뿐만 아니라 해상운송 분야에 사용되는 원동기로서 매우 중요한 역할을 하고 있다. 그러나 그 구조가 복잡하고 연소과정에서 시간지연 요소가 포함되어 있어 가스터빈 기관을 잘 제어할려면 정교한 수학적 모델링이 필요하다. 본 논문 에서는 가스터빈 기관의 주요 구성품인 가스발생기, PLA 액추에이터, 미터링 밸브에 대한 모델링 기법을 설명한다. 또한, 가스터빈 기관의 시 운전 데이터를 기초로 몇 가지 정상상태 때의 동작점에서 서브모델을 구하고, 각 서브모델에 대해 비선형 비례적분미분 제어기를 설계하여 기 관의 속도를 제어하는 방법을 제안한다. 제안하는 비선형 제어기는 비선형 함수로 구현되는 3가지 이득을 사용한다. 비선형 제어기의 파라미터 는 제어시스템의 목적함수를 최소화하는 관점에서 실수코딩 유전자알고리즘으로 동조한다. 제안한 방법은 가스터빈 기관에 적용하고 시뮬레이 션을 실시하여 그 유효성을 확인한다.

Since fuzzy controllers are nonlinear, it is more difficult to set the controller gains and to analyse the stability compared to conventional PID controllers. This paper proposes a fuzzy PD+I controller for tracking control which uses a linear fuzzy inference(product-sum-gravity) method based on a conventional linear PID controller. In this scheme the fuzzy PD+I controller works similar to the control performance as the linear PD plus I(PD+I) controller. Thus it is possible to analyse and design an fuzzy PD+I controller for given systems based on a linear fuzzy PD controller. The scaling factors tuning scheme, another topic of fuzzy controller design procedure, is also introduced in order to fine performance of the fuzzy PD+I controller. The scaling factors are adjusted by a real-coded genetic algorithm(RCGA) in off-line. The simulation results show the effectiveness of the proposed fuzzy PD+I controller for tracking control problems by comparing with the conventional PID controllers.