In this paper, we present an nonlinear PID controller with network based compensator which consists of a conventional PID controller that controls the linear components and neuro-compensator that controls the output errors and nonlinear components. This controller is based on the Harris's concept where he explained that the adaptive controller consists of the PID control term and the disturbance compensating term. The resulting controller's architecture is also found to be very similar to that of Wang's controller. This controller adds a self-tuning ability to the existing PID controller without replacing it by compensating the output errors through the neuro-compensator. Various simulations and comparative studies have proven that the proposed nonlinear PID controller produces superior results to other existing PID controllers. When applied to an actual magnetic levitation system which is known to be very nonlinear, it has also produced an excellent results.

A low cost lighting system for line-scan cameras has been developed with 3-phase power. When exposure time of line-scan camera is shorter than fluctuation period of illumination, the average gray value of each acquired 1-D image varies. Detecting defects on the objects's surface under such illuminating environment is very difficult. The proposed lighting system is composed of low-cost fluorescent lights based on 3-phase power. The specially designed lighting pack and the properly selected lighting position enable to get the rippleless lighting. The principle of the proposed lighting system has been explained analytically. The lighting system has been tested for fabric inspection with line-scan camera and it's efficacy has been proved.

Until now, all of the port goods are transported manually by container transporter in the port. Recently there are a lot of studies about unmanned vehicle driven automatically. In terms of the vehicle automation, the control of steering and velocity on vehicle systems is very important part in container transporter. In common sense, vehicle systems have lots of nonlinear parameters so we have many difficulties in designing the optimal controller of them. In this paper, we present a design of the TDOF PID controller using a hybrid schematic algorithm to control the steering system optimally. We used the single-track model to pre-test the designed controller before appling to AGV. We also used the ES(evolutionary strategy) and SA(simulated annealing) algorithms to construct the hybrid tuning algorithm for parameters of controller. Finally, we had the computer simulation to verify that our designed controller has better performance than the other one.

This paper deals with the control of the lateral motion of a mobile vehicle. A mobile vehicle using in this experiment is able to adapt many unmanned automatic driving system, for example, like a automated product transporting system. This vehicle is consist of the two servomotors. One is used to accelerate this vehicle and the another is used to change this lateral direction. An adaptive fuzzy logic controller(AFLC) is designed and applied to a experimental mobile vehicle in order to achieve the control of the lateral direction. An adaptive fuzzy logic controller(AFLC) is designed and applied to a experimental mobile vehicle in order to achieve the control of the lateral motion of the vehicle. Therefore, the main aim of this paper is investigate the possibility of applying adaptive fuzzy control algorithms to a microprocessor-based servomotor controller which requires faster and more accurate response compared with many other industrial processes. Fuzzy control rules are derived by modelling an expert's driving actions. Experiments are performed using a mobile vehicle with sensing units, a microprocessor and a host computer.

One of the basic assumptions in the static gait design for a walking robot is that the weight of leg should be negligible compared to that of body, so that the total gravity center is not affected by swing of a leg. Based on the ideal assumption of zero leg-weight, conventional static gait has been simply designed for the gravity center of body to be inside the support polygon, consisting of each support leg's tip position. In case that the weight of leg is relatively heavy, however, while the gravity center of body is kept inside the support polygon, the total gravity center of walking robot can be out of the polygon due to weight of a swinging leg, which causes instability in walking. Thus, it is necessary in the static gait design of a real robot a compensation scheme for the fluctuation in the gravity center. In this paper, a body impedance control is proposed to obtain the total gravity center based on foot forces measured from load cells of a real walking robot and to adjust its position to track the pre-designed trajectory of the corresponding ideal robot's body center. Therefore, the walking stability is secured even in case that the weight of leg has serious influence on the total gravity center of robot.

In discuss how the existing study results that decide optimum release time are rational and reasonable, considering the cost and reliability simultaneously in this paper. As a study method this paper examines the proposed results and their methodologies centering around the existing related papers for the general cost-reliability optimal release policies, especially their limitation for the derived results.

We propose two new types multi-stage blind clustering equalizers for QAM demoulation, which are called a complex classification algorithm(CCA) and a radial basis function algorithm(RBFA). The CCA uses a clustering technique based on the joint gaussian probability function and computes separately the real part and imaginary part for simple implementation as well as less computation. In order to improve the performance of CCA, the Dual-Mode CCA(DMCCA) incorporates the CCA tap-updating mode with the decision-directed(DD) mode. The RBFA reduces the number of cluster centers through three steps using the classification technique of RBF and then updates the equalizer taps for QAM demodulation. Test results on 16-QAM confirm that the proposed algorithms perform better the conventional multi-state equalizers in the senses of SER and MSE under multi-path fading channel.

A new large-scale network geometric analysis is introduced. For a large-scale circuit, it must be analyzed with a geometric diagram and figure. So many equations are induced from a geometric loop-node diagram. The results are arranged into a simple matrix, of course. In case of constructing a network diagram, it is not easy to handle voltage and current sources together. Geometric loop analysis is related to voltage sources, and node analysis is to current sources. The reciprocal transfer is possible only to have series or parallel impedance. If not having this impedance, in order to obtain equivalent circuit, many equations must be derived. In this paper a loop-reduction method is proposed. With this method current source branch is included into the other branch, and disappears in circuit diagram. So the number of independent circuit equations are reduced as much as that of current sources. The number is not (b-n+1), but (b-n+1-p). Where p is the number of current sources. The reduction procedure is verified with a geometric principle and circuit theory. A resultant matrix can be constructed directly from this diagram structure, not deriving circuit equations. We will obtain the last results with the help of a computer.