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Yoon Ho Choi

Researcher at Pusan National University

Publications -  240
Citations -  3872

Yoon Ho Choi is an academic researcher from Pusan National University. The author has contributed to research in topics: Lyapunov stability & Control theory. The author has an hindex of 28, co-authored 232 publications receiving 3465 citations. Previous affiliations of Yoon Ho Choi include Kyonggi University & Samsung.

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Adaptive Dynamic Surface Control for Stabilization of Parametric Strict-Feedback Nonlinear Systems With Unknown Time Delays

TL;DR: The robust stabilization method via the dynamic surface control (DSC) is proposed for uncertain nonlinear systems with unknown time delays in parametric strict-feedback form and it is proved that all the signals in the closed-loop system are semiglobally uniformly bounded.
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Adaptive Neural Sliding Mode Control of Nonholonomic Wheeled Mobile Robots With Model Uncertainty

TL;DR: This brief proposes an adaptive neural sliding mode control method for trajectory tracking of nonholonomic wheeled mobile robots with model uncertainties and external disturbances and derives online tuning algorithms for all weights of SRWNNs and proves that all signals of a closed-loop system are uniformly ultimately bounded.
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A Simple Adaptive Control Approach for Trajectory Tracking of Electrically Driven Nonholonomic Mobile Robots

TL;DR: This paper proposes a simple adaptive control approach for path tracking of uncertain nonholonomic mobile robots incorporating actuator dynamics, and adopts the adaptive control technique to treat all uncertainties and derive adaptation laws from the Lyapunov stability theory.
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Anti-proliferating effects of ginsenoside Rh2 on MCF-7 human breast cancer cells

TL;DR: The data suggest that G-Rh2 inhibited the growth of MCF-7 cells, by inducing protein expression of p21 and reducing the protein levels of cyclin D which resulted in the down-regulation ofcyclin/Cdk complex kinase activity, decreasing phosphorylation of pRb, and inhibiting E2F release.
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Integral Q-learning and explorized policy iteration for adaptive optimal control of continuous-time linear systems

TL;DR: The proposed Q-learning scheme evaluates the current value function and the improved control policy at the same time, and are proven stable and convergent to the LQ optimal solution, provided that the initial policy is stabilizing.