Myung-Ok So

Traversability analysis for navigation of unmanned robots

In this study, a framework for navigation of unmanned robots by combining information extraction from terrain maps with regional traversability and speed assessment is presented. The proposed method extracts the slope and roughness of a terrain patch along four heading directions and then uses them to evaluate the level of difficulty associated with the traversal. The slope is estimated through curved surface fitting incorporating the least squares method. The roughness is obtained using the fractal-based analysis together with another two RMS metrics. As navigation systems can cope with imprecision and uncertainty of input data, we modify and extend the Serajipsilas fuzzy-based measures to assess the traversability and speed of each patch for path planning. The proposed method is tested on both fractal and real terrains to verify its effectiveness.

RCGA-Based States Observer Design of Container Crane concerned with Design Specification

Construction of large-scale container ports with the productivity improvements in container cranes shortened time of staying port to increase the level of service it harbors efforts accelerated. About container crane system exerted on the input, which is designed to look good performance considering the states feedback control system. The states observer designed of container cranes state variables that are expected to measurement noise or particular measurement signal. In the status of existing research, the feedback gain matrix and the state observer gain matrix are searched by being separated solving. But the feedback gain matrix and the state observer gain matrix are searched by RCGAs at once that be used robust search method in this paper.

Slope and Roughness Extraction Method from Terrain Elevation Maps

Recently, the interests in the development and application of unmaned robots are increasing in various fields including surveillance and reconnaissance, planet exploration, and disaster relief Unmaned robots are usually controlled from distance using radio communications but they should be equipped with an autonomous travelling function to cope with unexpected terrains and obstacles. This means that they should be able to evaluate terrain’s characteristics quantitatively using mounted sensors so as to traverse harsh natural terrains autonomously. For this purpose, this paper presents a method for extracting terrain information, that is, slope and roughness from elevation maps as a prior step of traversability analysis. Slope is extracted using the curve fitting based on the least squares method and roughness using three metrics and their weighted average. The effectiveness of the proposed method is verified on both a fractal map and the world model map of a real terrain.

Design of a PID-type Autopilot Concerned with Propulsive Energy of Ship

The PID controller type autopilot is applied to support shipmaneuvering for course-keeping and heading control. A control constants of autopilot system should be evaluated by promoting energy loss (fuel consumption) from the view point of economic efficiency of the ship. This paper is obtained control constants of autopilot system from the RCGA pursued the minimum energy loss. In addition, the controller which is designed involves a constrained optimization problem. The performance of the proposed method is demonstrated through a set of simulation.

Speed Control of Marine Gas Turbine Engine using Nonlinear PID Controller

요 약 : 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.

Design of Fuzzy PD+I Controller Based on PID Controller

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.

RCGA-Based State Observer Design for Container Cranes

This paper presents a scheme for designing a state observer for container cranes. If the system is completely observable with a given set of outputs, then it is possible to determine the states that are not directly measured. We consider the reduced-order states observer with only trolley position detection and with trolley position and container angle detection. The gain matrix of the each state observer is adjusted using a RCGAs. A set of simulation works is carried out to demonstrate the effectiveness of the proposed scheme.

RCGA-Based State Feedback Control for Seesaw Systems

Generally. most of the physical systems affected by disturbance or incomplete knowledge are complex and highly nonlinear. To control under these circumstances. many researches are ongoing in modern control theory recently. But the researches need apparatuses. which can verify the controller for being not damaged the real plant. In this paper. therefore. a seesaw system is considered control system to analyze and apply the control theory. A seesaw system consists of a moving cart on the rail and seesaw frame made to demonstrate the effectiveness of the control theory. The system has balancing and positioning problems. and the driving force is applied on the DC motor of cart. but not on the pivot. The purpose of control is to maintain an equilibrium of seesaw frame in spite of an allowable disturbance. Computer simulations are given to illustrate the control performance of the proposed scheme.

Experimental Data based-Parameter Estimation and Control for Container Crane

In this paper, we presents a scheme for the parameter estimation and optimal control scheme for apparatus of container crane system. For parameter estimation, first, we construct the open loop of the container crane system and estimate its parameters based on input-output data, a real-coded genetic algorithm(RCGA) and the model adjustment technique. The RCGA plays an important role in parameter estimation as an adaptive mechanism. For controller design, state feedback gain matrix is searched by another RCGA and the estimated model. The performance of the proposed methods are demonstrated through a set of simulation and experiments of the experimental apparatus.

Design of a Model-Based Fuzzy Controller for Container Cranes

In this paper, we present the model-based fuzzy controller for container cranes which effectively performs set-point tracking control of trolley and anti-swaying control under system parameter and disturbance changes. The first part of this paper focuses on the development of Takagi-Sugeno (T-S) fuzzy modeling in a nonlinear container crane system. Parameters of the membership functions are adjusted by a RCGA to have same dynamic characteristics with nonlinear model of a container crane. In the second part, we present a design methodology of the model-based fuzzy controller. Sub-controllers are designed using LQ control theory for each subsystem in fuzzy model and then the proposed controller is performed with the combination of these sub-controllers by fuzzy IF-THEN rules. In the results of simulation, the fuzzy model showed almost similar dynamic characteristics compared to the outputs of the nonlinear container crane model. Also, the model-based fuzzy controller showed not only the fast settling time for the change in parameter and disturbance, but also stable and robust control performances without any steady-state error.