Jong-Tae Lim

Stabilization of Approximately Feedback Linearizable Systems Using Singular Perturbation

We consider a stabilization problem of approximately feedback linearizable systems. We introduce a perturbation parameter by applying high-gain feedback and use both the feedback linearization method and the singular perturbation method for the controller design. Through this, we can overcome the rigorous conditions of the feedback linearization method and can reduce the dimension of the slow model of the singularly perturbed system.

Nonlinear Control of an Electromagnetic Levitation System Using High-gain Observers for Mmagnetic Bearing Wheels

In this paper, we develop a functional test model for magnetic bearing wheels. The functional test model is an electromagnetic levitation system that has three degree of freedom, which consists of one axial suspension from gravity and two axes gimbaling capability to small angels. A nonlinear controller with high-gain observers is proposed and the real-time experiment results show that the rotor is accurately levitated at the desired position and well-balanced, which is a suitable result for the potential use an magnetic bearing wheels. Also, the proposed scheme exhibits better performance when it is compared with the conventional PID control method.

On pattern classification of EMG signals for walking motions

We present a method to calssify electromyogram (EMG) signals which are utilized as control signals for a patient-responsive walker-supported system for paraplegics. Patterns of EMG signals for different walking motions are classified via adequate filtering, real EMG signal extraction, AR-modeling, and a modified self-organizing feature map (MSOFM). In particular, a data-reducing extraction algorithm is employed for real EMG signals. Moreover, MSOFM classifies and determines the results automatically using a fixed map. Finally, the experimental results are presented for validation.

Adaptive control of a class of feedforward and non-feedforward nonlinear systems

We propose a switching-based adaptive state feedback controller for a class of nonlinear systems that have uncertain nonlinearity. The base of the proposed conditions on the nonlinearity is the feedforward form, then it is extended via a nonlinear function containing all the states and the control input. As a result, more generalized systems containing feedforward and nonfeedforward terms are allowed as long as the ratio condition of the nonlinear function is satisfied. Moreover, the information on the growth rate of nonlinearity is not required a priori in our control scheme.