Wonchul Kim

Stability analysis and stabilization of fuzzy state space models

Abstract A new stability test method for linguistic fuzzy state space models is proposed in this paper. This method allows the determination of stability of fuzzy models by applying the Lyapunov function to each rule. A gradient-based algorithm is suggested to simplify the stability tests. Using this algorithm, the Lyapunov equation can be updated towards the direction where the stability can be determined more correctly. An additional gradient-based stabilizing algorithm is also derived, which allows a systematic approach to find stabilizing controls by updating the Lyapunov equations towards the direction where unstable eigenvalues are decreased. Examples demonstrate the convenience of the stability test and the two suggested gradient-based algorithms.

Three-link planar arm control using reinforcement learning

In this paper, we apply reinforcement learning(RL) to control a 3-Dof manipulator. Learning is achieved by using an on-policy temporal difference(TD) learning. In order to control the manipulator, the TD agents are in charge of the movements of the robot by adjusting each angle. We first implement the SARSA algorithm by repeatedly updating a hash-table with the current and next state-action values, and the received rewards. However, since the conventional RL algorithms have issues of the heavy computational load, we propose RL algorithms applying multi-agents approach with an assumption and vector values for states. We state the result of the classical RL algorithm and compare it with our approach. For the simulation, we test a three-link planar arm for two cases: positioning the end-effector to a fixed goal point and random goal points. The simulation results show that the robot completes the mission successfully with the improvement in the computational load.

Mistuning Intensity Effect to Optimization of Mistuning Pattern for Bladed Disk

??일반적으로 터보 기계에서 mistuning은 구조적, 기하학적인 면에서의 blade와 blade 사이의 미소한 특성의 차이를 의미하며, 이러한 미소한 차이가 강제 진동 시, 발생하는 진동 에너지가 몇 개의 blade 또는 하나의 blade에 집중되어 매우 큰 진동을 야기 시킬 수 있다는 사실이 여러 논문들에 언급되고 있다. 또한 mistuning에 대한 blade 시스템의 강제진동응답의 감도를 줄이기 위하여, intentional mistuning개념을 설계단계에 도입하려고 하는 연구도 진행되고 있다. 따라서 본 논문에서는 두 가지 형태의 blade만을 사용하여 bladed disk의 강제진동응답을 최소화 할 수 있는 intentional mistuning의 pattern 최적화에 미치는 mistuning intensity 영향을 조사하였고 최적화 알고리즘으로 유전알고리즘을 사용하였다.