For motor controller designers, building a simulation environment is not a difficult process. After verifying the controller by simulation, it is common to select 20kHz for the current control loop, 1kHz for the speed loop, and 100Hz for the position loop when implementing the actual HW embedded system. This is because maximized cycles (20kHz) for each control loop are unnecessary in control theory and are a waste of cost and HW resources. However, in a simulation environment, each loop will often have the same control cycle (20kHz maximum). This is because we think it is unnecessary to reflect this part in the simulation. In this paper, it is shown that the difference in the sampling time of each control loop makes a big difference in the simulation result, and as a solution, it is proposed to apply LPF to the position loop output stage. In the process, the reasons for the differences were analyzed, and the effect of LPF, the reason for application, and the feasibility of implementation were proved by actual software coding.

선박 발전기의 여자기는 출력 단자 전압을 일정하게 유지하기 위하여 여자전류 제어를 통해 자속을 조정한다. 여자기 내부에 있는 전압제어기는 통상적으로 비례 적분 제어방식이 사용되는데 게인과 시정수에 의해 결정되는 응답 특성은 적절치 못한 설정값에 의 해 원하지 않는 출력을 내며 이로 인해 선내 전력의 품질과 안정성을 떨어뜨릴 수 있다. 본 논문에서는 IEEE에서 제공하는 AC4A 타입의 여자기 모델을 통해 얻을 수 있는 안정적인 입출력 데이터를 활용하여 신경망 회로를 학습시킨 후 기존의 비례 적분 제어방식의 전압제 어기를 학습된 신경망 회로 제어기로 대체하여 시뮬레이션을 수행하였다. 그 결과 기존 대비 최대 9.63%까지 오버슈팅이 개선되었으며, 안정적인 응답 특성에 대한 우수성을 확인하였다.

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.

Controller modeling is essential for the design. It allows various control techniques to be simulated in advance, and various interpretations can be performed. If this is not the case, we need to reverse engineering in the real system developed by others. In this paper, controller modeling was reversely designed using the frequency test results of the target system. First, the characteristic equation of the target equipment was based on and a block diagram was assumed. Thereafter, controller variables were estimated using the frequency test results for each of the four control loops. In addition, time response simulations were performed using the estimated controller modeling. This method is thought to be of great help to reverse engineering in situations where there is completed equipment but no controller modeling.

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 describes the design of H-infinity controller for robust control of a DC motor system. The suggested controller can ensure robustness against disturbance and model uncertainty by minimizing H-infinity norm of the transfer function from exogenous input to performance output and applying the small gain theorem. In particular, the controller was designed to reduce the effects of disturbance and model uncertainty simultaneously by formalizing these problems as a mixed sensitivity problem. The validity of the proposed controller was demonstrated by computer simulations and real experiments. Moreover, the effectiveness of the proposed controller was confirmed by comparing its performance with PI controller, which was tested under the same experimental condition as the H-infinity controller.

This paper proposes a model predictive controller of robot manipulators using a genetic algorithm to secure the best performance by performing parameter optimization with the genetic algorithm. Genetic algorithm is a natural evolutionary process modeled as a computer algorithm and has excellent performance in global optimization, so it is useful for tuning control parameters. The sliding mode controller and inverse dynamics controller are included in the lower part of the model prediction controller to minimize the problems caused by non-linearity and uncertainty of the robot manipulator. The performance superiority of the proposed method as described above has been confirmed in detail through a simulation study.

This is the research report concerned with the new stability concept and designing the controller of the time periodic systems. The periodic systems which is governed by time is very common in various type of dynamic systems. For example, the satellite is the large scale and the experimental test equipment as pendulum is also time periodic systems. The motion of the systems during the time interval is running repeatedly. While this periodic systems is running, the dynamic stability is important to behave the appropriate motion of the system's function. This research propose the new stability approach based on Lyapunov theorem which is analyzing the system's stability adapting the specific energy function. And also this research introduces the developing numerical procedures to retain the stability of time periodic system. Finally, the result of this research is very useful to judge the stability and design the controller of time periodic system.

연안 해역에서 소형 선박의 프로펠러 고장으로 인한 사고가 지속적으로 발생하고 있다. 특히, 해상부유물(폐그물 및 로프 등)에 의하여 선박 프로펠러가 감기는 사고가 빈번히 일어나고 있다. 선박 프로펠러 감김 사고는 동력 상실로 인한 선박의 운항 지연 및 표류로 인한 1차 사고와 프로펠러에 감긴 로프을 제거하기 위한 잠수 작업등으로 인한 2차 사고의 우려가 있다. 이러한 빈번한 프로펠러 감김 사 고에도 불구하고 문제를 해결할만한 적절한 도구가 없어 선박을 육상으로 인양하여 수리하거나, 잠수부가 직접 선박 아래로 잠수하여 문제를 해결하고 있는 실정이다. 이에 따라, 최근 선박 프로펠러 감김 사고를 예방하기 위해 프로펠러 샤프트에 로프절단장치를 일부 소형 선박에 장착하고 있으나 비교적 높은 설치비용 및 시간이으로 인하여 원활하게 적용되어지지 않는 것으로 판단된다. 본 연구에서는 이러한 문제점을 해결하기 위해 기계톱 원리를 이용한 간단한 구조를 가진 수중절단기 기구 설계 및 제어기 개발을 수행하였다. 수중절단 기의 톱날은 직선왕복동작을 위해 유성기어와 크랭크핀을 사용함으로써 긴 행정을 가질 수 있도록 하였다. 또한 수중절단기는 소형 선박에 비치되어있는 배터리를 이용하여 작동시킬 수 있도록 하였다. 또한, 비전문가인 사용자가 보다 편리하고 안전하게 사용할 수 있도록 역전류 방지 및 속도제어회로를 적용하여 편리성 및 안정성을 확보하였다.

Robot manipulators are highly nonlinear system with multi-inputs multi-outputs, and various control methods for the robot manipulators have been developed to acquire good trajectory tracking performance and improve the system stability lately. The computed torque controller has nonlinear feedforward control elements and so it is very effective to control robot manipulators. If the control gains of the computed torque controller is adjusted according the payload, then more precise control performance is attained. This paper extends the conventional computed torque controller in the joint space to the Cartesian space, and optimize the control gains for some specified payloads in both joint and Cartesian spaces using genetic algorithms. Also a neural network is employed to have proper control gains for arbitrary payloads using generalization properties of the neural network. Computer simulation results show that the proposed control system for robot manipulators has excellent performance in various conditions.

The model predictive controller performance of the mobile robot is set to an arbitrary value because it is difficult to select an accurate value with respect to the controller parameter. The general model predictive control uses a quadratic cost function to minimize the difference between the reference tracking error and the predicted trajectory error of the actual robot. In this study, we construct a predictive controller by transforming it into a quadratic programming problem considering velocity and acceleration constraints. The control parameters of the predictive controller, which determines the control performance of the mobile robot, are used a simple weighting matrix Q, R without the reference model matrix Ar by applying a quadratic cost function from which the reference tracking error vector is removed. Therefore, we designed the predictive controller 1 and 2 of the mobile robot considering the constraints, and optimized the controller parameters of the predictive controller using a genetic algorithm with excellent optimization capability.

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.

The predictive control system using model-based predictive control is a very effective way to optimize the present inputs considering the states and future errors of the reference trajectory, but it has a drawback in that a control input matrix must be repeatedly calculated with a long calculation time at every sampling for minimizing future errors in a predictive interval. In this study, we applied the neural network simulating the predictive control method for the trajectory tracking control of the mobile robot to reduce complex control method and computation time which are the disadvantage of predictive control. In addition, the neural network showed excellent performance by the generalization even for a different reference trajectory. Therefore, The controller is designed by modeling the model-based predictive control gains for the reference trajectory using a neural networks. Through the computer simulation, the proposed control method showed better performance than the general predictive control method.

The purpose of this study is to accurately estimate the wind-induced responses of a tall building structure for using the estimated responses in the process of calculating the optimal force of an active control device. Kalman filter was used for the estimation process and a 3-storied model structure on a shaking table was tested for the verification of the estimation accuracy. The system matrices of the model were constructed based on the mode parameters obtained by the system identification. The estimated displacement matched up well with the measured one. Finally, the wind-induced responses of a real 39-storied building structure excited by the typhoon MUIFA were estimated.