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Novel Adaptive Particle Filter Using Adjusted Variance and Its Application
임묘택,박상혁,김영중 제어·로봇·시스템학회 2010 International Journal of Control, Automation, and Vol.8 No.4
Precise estimation of the position of robots, which is essential in mobile robotics, is difficult to achieve. However, particle filter shows great promise in this area. The number of samples used in this study is closely related to the operation time in particle filtering. The main issue in real-time implementation with regard to particle filter is to reduce the operation time, which led to the development of the adaptive particle filter (APF). We propose a new APF which adjusts the variance and then uses the gradient data to generate samples near the high likelihood region. The experiment results show that the new APF performs better, in terms of the total operation time and sample set size, than the standard particle filter and the APF using Kullback-Leibler distance sampling.
임묘택,송문규,최현덕,안춘기 제어·로봇·시스템학회 2016 International Journal of Control, Automation, and Vol.14 No.1
This paper addresses the new output-feedback H∞ control problem for active half-vehicle suspensionsystems with time-varying input delay. By introducing multi-objective synthesis, a new dynamic output-feedbackH∞ controller is designed such that the closed-loop suspension system is asymptotically stable with guaranteedrobust performance in the H∞ sense. The proposed controller is formulated in terms of linear matrix inequality(LMI) based on the auxiliary function-based integral inequality method and the reciprocally convex approach. Anew delay-dependent sufficient condition for the desired controller offers a wider range of control input delay. Numerical examples are provided to validate the effectiveness of the proposed design method.
Fuzzy H∞ FIR Filtering for T–S Fuzzy Systems with Quantization and Packet Dropout
이창주,임묘택 제어·로봇·시스템학회 2018 International Journal of Control, Automation, and Vol.16 No.3
This paper proposes a new fuzzy H∞ finite impulse response (FIR) filter with quantization and packet dropout for Takagi–Sugeno (T–S) fuzzy systems with external disturbance. The measurements are quantized by a logarithmic quantizer and then transmitted from the plant to the filter imperfectly due to random packet loss described by the Bernoulli random process. The proposed fuzzy H∞ FIR filter is in the form of fuzzy-basis-independent linear matrix inequalities (LMIs) that guarantee H∞ performance. Two simulation examples are given to illustrate the effectiveness and robustness of the proposed fuzzy H∞ FIR filter.
Obstacle Avoidance Path Planning based on Output Constrained Model Predictive Control
김지창,배동성,임묘택 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.11
Image processing and control technologies have been widely studied and autonomous vehicles have become an active research area. For autonomous driving, it is essential to generate a safe obstacle avoidance path considering the surrounding environment. This paper devised an algorithm based on a real-time output constrained model predictive control for obstacle avoidance path planning in high speed driving situations. The proposed algorithm was compared with the normal model predictive control algorithm by simulation, including operation times to verify robustness for high speed driving situations. We used the ISO 2631-1 comfort level standard to quantify driver comfort fo r both cases.