Yun Jong Choi

Parametric interpolation using sampled data

Trajectory in high-speed precision machining requires very small feed-rate fluctuation and contour error, which can be achieved with parametric interpolation. Since it is impossible to exactly compute the arc-length of a general parametric curve, the conventional parametric interpolation obtains a parameter through a real-time update. Thus it cannot be used with a preplanned feed-rate profile, which restricts its applications. To overcome such a problem, the proposed algorithm estimate parameters using tabulated parameter and length data. The simulations show the proposed method useful with smaller contour error and acceptable feed-rate fluctuation comparable to the second order real-time parametric interpolation.

Jerk limited velocity profile generation for high speed industrial robot trajectories

Abstract Trapezoidal velocity profiles are no longer sufficient for recent high speed industrial robots involved in precision works. Most of the recently developed trajectory generation algorithms have adopted jerk limited profiles, where computation of the coefficients is intricate. The previous algorithms have attempted either to obtain suboptimal solutions or to solve the problem in an iterative manner which complicates on-line implementation. This paper presents analytic solutions to the computational problem. The solutions presented are derived from the simultaneous equations for displacement condition and peak velocity condition, where jerk, acceleration and velocity constraints are resolved. By including only the low-order polynomial equations that can be evaluated analytically, the proposed algorithm is readily implementable on the fly.

Improved global stability conditions of the tuning parameter in FAST TCP

In this letter, we present a correction of the theorem for the global stability of FAST TCP developed by Koo et al. in 2008. Furthermore, an analysis is carried out to determine an improved parameter condition for global stability than the existing conditions in the literature. The parameter condition is verified by the ns-2 simulation.

Guaranteed Cost Fuzzy Controller Design for Nonlinear Systems with Input Saturation

Nonlinear systems can be divided into two parts: a nonlinear part related to the input and another part not related to that. In the fields of fuzzy control, one generally has tried to use common fuzzy weighting functions for modeling two parts, simultaneously. However, in general, the direct selection of common fuzzy weighting functions is difficult and the rough selection of those can lead to the conservative results. To overcome these, in this paper, we present a Takagi-Sugeno (TS) fuzzy model with different fuzzy weighting functions for two parts and a guaranteed cost fuzzy controller for the system with input saturation.

Stabilization of 2-D Linear Parameter-Varying Systems using Parameter-Dependent Lyapunov Function: An LMI Approach

Abstract This paper proposes a parameter-dependent state-feedback controller for the 2-D discrete linear parameter-varying (LPV) system with the Fornasini-Machesini (FM) first model. To find the stabilizing conditions of the system, we first transform the closed-loop system to a Roesser-type model, and then derive the conditions to linear matrix inequalities (LMIs) using a parameter-dependent Lyapunov function (PDLF) and a relaxation technique. The simulation results show that the designed controller is valid and the system asymptotically converges to the origin.