• Title/Summary/Keyword: MDPS Software

Search Result 4, Processing Time 0.016 seconds

MDPS Analysis Software Development (MDPS 해석 소프트웨어 개발)

  • Jang, Bongchoon;Kim, Joung-Hoon;Yang, Sung-Mo
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.15 no.9
    • /
    • pp.5480-5486
    • /
    • 2014
  • Complete novel software for MDPS for the simulation and analysis is proposed for steering engineers. The software, MSAS, which can provide the functionality for MDPS Simulation, Analysis & Synthesis, is based on the steering system model, vehicle model and control logic. As the suppliers provide the control logic as a black box, this software is capable of using any type of black box logic or white box control logic that can be developed by logic designers. In addition, this software will be synthesized with the suppliers' s-function control logic and RMDPS together.

Destructive Test of a BLDC Motor Controller Utilizing a Modified Classification Tree Method (변형된 Classification Tree Method를 이용한 BLDC 모터제어기 파괴 시험)

  • Shin, Jae Hyuk;Chung, Ki Hyun;Choi, Kyung Hee
    • KIPS Transactions on Software and Data Engineering
    • /
    • v.3 no.6
    • /
    • pp.201-214
    • /
    • 2014
  • In this paper, we propose a test case generation method adequate to destructive test of the BLDC(Brush Less Direct Current) motor controller used for the MDPS(Motor Driven Power Steering) system embedded in an automobile. The proposed method is a modified CTM(Classification Tree Method). CTM generates test cases assuming that all inputs are equally important. Therefore, it is very hard to generate test cases for extreme situations. To overcome the drawback and generate test cases specialized for destructive test. a modified CTM that compensates the limitation of traditional CTM is proposed. The proposed method has an advantage that it can intensively generate the test scenarios adequate to extreme situations by combining the test cases generated by the transitional CTM the while keeping the merit of the traditional CTM. The test scenarios for destructive test for the MDPS system embedded in a commercial automobile are generated utilizing the proposed method. The effectiveness of the proposed algorithm is verified through the test.

Unified Control of Independent Braking and Steering Using Optimal Control Allocation Methods for Collision Avoidance (전(全)방향 충돌 회피를 위한 액츄에이터 최적 분배 알고리즘)

  • Kim, Kyuwon;Kim, Beomjun;Yi, Kyongsu
    • Journal of Auto-vehicle Safety Association
    • /
    • v.5 no.2
    • /
    • pp.11-16
    • /
    • 2013
  • This paper presents a unified control algorithm of independent braking and steering for collision avoidance. The desired motion of the vehicle in the yaw plane is determined using the probabilistic risk assessment method based on target state estimation. For the purpose of coordinating the independent braking and steering, a non-linear vehicle model has been developed, which describes the vehicle dynamics in the yaw plane in both linear and extended non-linear ranges of handling. A control allocation algorithm determines the control inputs that minimize the difference between the desired and actual vehicle motions, while satisfying all actuator constraints. The performance of the proposed control algorithm has been investigated via computer simulations conducted using the vehicle dynamics software CARSIM and Matlab/Simulink.

Efficient Approximation of State Space for Reinforcement Learning Using Complex Network Models (복잡계망 모델을 사용한 강화 학습 상태 공간의 효율적인 근사)

  • Yi, Seung-Joon;Eom, Jae-Hong;Zhang, Byoung-Tak
    • Journal of KIISE:Software and Applications
    • /
    • v.36 no.6
    • /
    • pp.479-490
    • /
    • 2009
  • A number of temporal abstraction approaches have been suggested so far to handle the high computational complexity of Markov decision problems (MDPs). Although the structure of temporal abstraction can significantly affect the efficiency of solving the MDP, to our knowledge none of current temporal abstraction approaches explicitly consider the relationship between topology and efficiency. In this paper, we first show that a topological measurement from complex network literature, mean geodesic distance, can reflect the efficiency of solving MDP. Based on this, we build an incremental method to systematically build temporal abstractions using a network model that guarantees a small mean geodesic distance. We test our algorithm on a realistic 3D game environment, and experimental results show that our model has subpolynomial growth of mean geodesic distance according to problem size, which enables efficient solving of resulting MDP.