This paper presents the new three-level optimal control scheme for the large scale nonlinear systems, which is based on fast walsh transform. It is well known that optimization for nonlinear systems leads to the resolution of a nonlinear two point boundary value problem which always requires a numerical iterative technique for their solution. However, Three-level costate coordination can avoid two point boundary condition in subsystem. But this method also has the defect that must solve high order differential equation in intermediate level. The proposed method makes use of fast walsh transform, therefore, is simple in computation because of solving algebra equation instead of differential equation.

This paper uses the distributed heating thin metal moving at constant velocity which are modeled as distributed parameter systems, and applies the Paley order of Walsh functions to high order partial differential equations and matrix partial differential equations. This thesis presents a new algorithm which usefully exercises the optimal control in the distributed parameter systems. In this paper, the excellent consequences are found without using the existing decentralized control or hierarchical control method.

Recently conventional artificial intelligence(AI) approaches have been employed to build action selectors for the autonomous mobile robot(AMR). However, in these approaches, the decision making process to choose an action from multiple competence modules is still an open question. Many researches have been focused on the reactive planning systems such as the biological immune system. In this paper, we attempt to construct an action selector for an AMR based on the artificial immune network and internet. The information from vision sensors is used for antibody. We propose a learning method for artificial immune network using evolutionary algorithm to produce antibody automatically. The internet environment for an AMR action selector shows the usefulness of the proposed learning artificial immune network application.

In this paper, we propose a probabilistic tabu search strategy for function optimization. It is composed of two procedures, one is Basic search procedure that plays a role in local search, and the other is Restarting procedure that enables to diversify search region. In basic search procedure, we use Belief space and Near region to create neighbors. Belief space is made of high-rank neighbors to effectively restrict searching space, so it can improve searching time and local or global searching capability. When a solution is converged in a local area, Restarting procedure works to search other regions. In this time, we use Probabilistic Tabu Strategy(PTS) to adjust parameters such as a reducing rate, initial searching region etc., which makes enhance the performance of searching ability in various problems. In order to show the usefulness of the proposed method, the PTS is applied to the minimization problems such as De Jong functions, Ackley function, and Griewank functions etc., the results are compared with those of GA or EP.

The term 'silent period(SP)' refers to a transitory, relative or absolute decrease electromyography(EMG) activity, evoked in the midst of an otherwise sustained contraction. Masseteric SP is elicited by a tap on the chin during isometric contraction of masseter muscle. In this paper, a new EMG signal generation model including SP in masseter muscle is proposed. This work is based on the anatomical structure of trigeminal nerve system that related on temporomandibular joint(TMJ) dysfunction. And it was verified by comparing the real EMG signals including SP in masseter muscle to the simulated signals by the proposed model. Through this studies, it was shown that SP has relation to variable neurophysiological phenomena. A proposed model is based on the control system theory and DSP(Digital Signal Processing) theory, and was simulated using MATLAB simulink. As a result, the proposed SP model generated EMG signals which are similar to real EMG signal including normal SP and an abnormal extended SP. This model can be applied to the diagnosis of TMJ dysfunction and can effectively explain the origin of extended SP.

The computerized cardiac analysis system, which acquires and analyzes the electrical activation signal propagating along the surface of the heart, is indispensible equipment for the open heart surgery and electrical cardiac study. In this paper, the design requirement and the electrical circuit analysis are performed to construct the multi-channel cardiac activation pre-amplifier necessary for a signal conditioning circuit. The general 64 channel configuration is expanded into 128 channels to enhance the spatial resolution on the mapped surface of the heart. The 128 channels pre-amplifier consists of input circuit, differential amplifier, right leg driven circuit and isolation part. It has distinct features; high voltage protection, leakage current limitation, isolation and the maximization of common mode rejection ratio with respect to the half-cell potential difference due to different electrode materials. The final pre-amplifier circuit is assembled with 8 boards, each of which composing of 16 channels.