• Journal of the Society of Disaster Information
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• v.18 no.4
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• pp.699-705
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• 2022

Purpose: Sequence control is widely used by being applied to manufacturing, distribution, construction, and automation in the medical industry. With the development of the fourth industry, artificial intelligence convergence technology in the control field is becoming an important factor in the industry. In particular, it is required to evaluate the safety and innovation of facilities where microprocessors and artificial intelligence are fused to existing systems and develop reliable equipment, so it is intended to develop equipment for educational purposes and drive the development of the field. Method: The self-developed all-in-one artificial intelligence controller module is a device that combines artificial intelligence capabilities with existing sequence and PLC control circuits. As the performance evaluation items of this equipment, the recognition ability of motion, voice, text, color, etc. and the stability and reliability of the circuit were evaluated. Conclusion: After designing the sequence and PLC circuit, the performance evaluation items of the integrated integrated artificial intelligence controller module were all satisfied, and there was no problem in the safety and reliability of the circuit.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1254-1256
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• 1996

Design methods for sequence flow controllers play an important role in industrial automation. To design a flexible, reusable, and maintainable control software has become a key issue nowadays. Petri net has been emerging as an important tool to provide an integrated solution for modeling, analysis, simulation, and control of industrial automated systems recently. This paper describes an international standard of programming languages for programmable logic controllers, IEC 1131-3 SFC( Sequential Function Chart), and the sequence flow control method for an SFC using a Petri net-like model.

• Nuclear Engineering and Technology
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• v.55 no.1
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• pp.37-44
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• 2023

Using the Kalman filtering technique, we propose a novel method for estimating the missing video frames to monitor the activities inside the control room of a nuclear power plant (NPP). The purpose of this study is to reinforce the existing security and safety procedures in the control room of an NPP. The NPP control room serves as the nervous system of the plant, with instrumentation and control systems used to monitor and control critical plant parameters. Because the safety and security of the NPP control room are critical, it must be monitored closely by security cameras in order to assess and reduce the onset of any incidents and accidents that could adversely impact the safety of the NPP. However, for a variety of technical and administrative reasons, continuous monitoring may be interrupted. Because of the interruption, one or more frames of the video may be distorted or missing, making it difficult to identify the activity during this time period. This could endanger overall safety. The demonstrated Kalman filter model estimates the value of the missing frame pixel-by-pixel using information from the frame that occurred in the video sequence before it and the frame that will occur in the video sequence after it. The results of the experiment provide evidence of the effectiveness of the algorithm.

• International Journal of Control, Automation, and Systems
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• v.1 no.4
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• pp.444-452
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• 2003

An integration system with multi-measurement sets can be realized via combined application of a centralized and federated Kalman filter. It is difficult for the centralized Kalman filter to remove a failed sensor in comparison with the federated Kalman filter. All varieties of Kalman filters monitor innovation sequence (residual) for detection and isolation of a failed sensor. The innovation sequence, which is selected as an indicator of real time estimation error plays an important role in adaptive mechanism design. In this study, the centralized Kalman filter with adaptive measurement fusion is introduced by means of innovation sequence. The objectives of adaptive measurement fusion are automatic isolation and recovery of some sensor failures as well as inherent monitoring capability. The proposed adaptive filter is applied to the GPS/SDINS integration system with an additional sensor. Simulation studies attest that the proposed adaptive scheme is effective for isolation and recovery of immediate sensor failures.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.9
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• pp.836-843
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• 2000

A sequence planning method is proposed to reduce the assembly time of gantey-type chip mounters with single head. The overall path of the chip mounter is divided into forward and backward path, and formulate the optimization problem is formulated as an transpoetation problem and an Euler's tour problem. The transportation alforithm is applied to find optimal backward path, and Euler's tour algorithm used to generate an assembly sequence. Simulation results are presented to verify the usefulness of the proposed method.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3067-3069
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• 1999

In this paper, A bit processor for controlling sequence logic was implemented, using a FPGA. This processor consists of program memory interface. I/O interface, parts for instruction fetch and decode, registers, ALU, program counter and etc. This FPGA is able to execute sequence instruction during program fetch cycle, because of divided bus system, program bus and data bus. Also this bit processor has instructions set that 16bit or 32bit fixed width, so instruction decoding time and data memory interface time was reduced. This FPGA was synthesized by pASIC 2 SpDE and Synplify-Lite synthesis tool of Quick Logic company. The final simulation for worst cases was successfully performed under a Verilog HDL simulation environment. And the FPGA programmed for an 84 pin PLCC package. Finally, the benchmark was performed to prove that Our FPGA has better performance than DSP(TMS320C32-40MHz) for the sequence logic control of PLC.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.429-434
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• 2013

This paper proposes a CPSO (Cooperative Particle Swarm Optimization)-based MPC (Model Predictive Control) scheme to deal with formation control problem of multiple nonholonomic mobile robots. In a distributed MPC framework, each robot needs to optimize control input sequence over a finite prediction horizon considering control inputs of the other robots where their cost functions are coupled by the state variables of the neighboring robots. In order to optimize the control input sequence, a CPSO algorithm is adopted and modified to fit into the formation control problem. Experiments are performed on a group of nonholonomic mobile robots to demonstrate the effectiveness of the proposed CPSO-based MPC for multi-robot formation.

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.2
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• pp.69-80
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• 1999

A genetic algorithm to determine the optimal signal sequence and double cycle pattern is described. The signal sequence and double cycle pattern are used as the input for TRANSYT to find optimal signal timing at each junction in the area traffic networks, In the genetic process, the partially matched crossover and simple crossover operators are used for evolution of signal sequence and double cycle pattern respectively. A special conversion algorithm is devised to convert the signal sequence into the link-stage assignment for TRANSYT. Results from tests using data from an area traffic network in Leicester region R are given.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.832-835
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• 1987

This paper proposes a new method of generating binary random sequences using a randomly sampled M-sequence. In this paper two methods of sampling are proposed. Expected values of the autocorrelation function of the sequence generated by these methods are calculated theoretically. From the results of computer simulation, it is shown that using these methods, we can get binary random sequences which have good random properties.

• Journal of Power Electronics
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• v.12 no.3
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• pp.495-502
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• 2012

This paper presents an improved grid voltage control strategy for wind farms with doubly-fed induction generators (DFIGs) connected to distribution networks based on an analysis of the operation limits of DFIG systems. A modified reactive power limit calculation method in different operation states is proposed and a reactive power control strategy during grid voltage dips/rises is further discussed. A control strategy for compensating unbalanced grid voltage, based on DFIG systems, by injecting negative sequence current into the grid through the grid side converter (GSC) is proposed. In addition, the negative current limit of the GSC is discussed. The distribution principle of the negative sequence current among the different DFIG systems in a wind farm is also introduced. The validity of the proposed voltage control strategy is demonstrated by Matlab/Simulink simulations. It is shown that the stability of a wind farm and the power grid can be improved with the proposed strategy.