This work studied the feasibility of digitalizing the analog Ex-Core Neutron Flux Monitoring System (ENFMS) being used for APR1400 nuclear power plants (NPPs) and as to which strategies and steps must be taken. A fission chamber neutron flux detection and instrumentation model were designed. Its accuracy was evaluated and proven by comparing the model data with data gathered from tests and plant operations. A conceptual design was proposed through a combined structure that digitalizes only part of the system. The detector signal pre-amplification remains in analog form while the other functions such as reactor power calculation as well as signal conditioning and processing will be digitalized. Simulations showed that the true mean squared voltage (MSV) of the digitalized ENFMS maintained a linear relationship between real and estimated reactor power in the wide range compared to averaged magnitude squared value of analog ENFMS. Extended Kalman Filter (EKF) was also utilized for estimating reactor power and reactor period from measurement signals that are contaminated with gamma ray interaction and electric noise. This study proved that the ENFMS can be successfully digitalized as proposed wherein all functional and performance requirements are satisfied. Simulations results demonstrated that the functions and performance can be improved through the use of digital processing algorithms such as EKF and MSV.

Look into the nuclear power plant of Wolsong currently, it is controlled in order to required operating pressure with PI controller. PI controller has a simple structure and satisfy design requirements to gain setting. However, It is difficult to control without changing the gain from produce changes in parameters such as loss of the valves and the pipes. To solve these problems, the dynamic change of the PI controller gain, or to compensate for the PI controller output is desirable to configure the controller. The aim of this research and development in the parameter variations can be controlled to a stable controller design which is reduced an error and a vibration. Proposed PI/NN control techniques is the PI controller and the neural network controller that combines a parallel and the neural network controller part is compensated output of the controller for changes in the parameters were designed to be robust. To directly evaluate the controller performance can be difficult to test in real processes to reflect the characteristics of the process. Therefore, we develope the simulator model using the real process data and simulation results when compared with the simulated process characteristics that showed changes in the parameters. As a result the PI/NN controller error and was confirmed to reduce vibrations.

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This paper addressed obstacle avoidance problem of a quadrotor in outdoor environment. Path planning was finished by employing classical Dijkstra algorithm and the controller of the quadrotor adopted integral backstepping method. In order to get a smooth trajectory with time optimal and acceleration constraints properties, quantic polynomials were utilized to generate trajectory file. The scheme is particularly practical and useful because of its small computation burden and feasibility. Simulations have been done to verify the performance of the whole system. As a result, the quadrotor successfully tracked the path without any collision with obstacles except that there are some small error in the final part of position tracking performance (±1m) and some small delay in the attitude tracking about 0.3 ms. In conclusion, the proposed method showed acceptable performance for quadrotor obstacle avoidance.